Abstract
Background
Chronic kidney disease (CKD) is a major public health problem affecting 13% of the global population. Prior research has indicated that CKD is associated with gut dysbiosis. Gut dysbiosis may lead to the development and/or progression of CKD, which in turn may in turn lead to gut dysbiosis as a result of uraemic toxins, intestinal wall oedema, metabolic acidosis, prolonged intestinal transit times, polypharmacy (frequent antibiotic exposures) and dietary restrictions used to treat CKD. Interventions such as synbiotics, prebiotics, and probiotics may improve the balance of the gut flora by altering intestinal pH, improving gut microbiota balance and enhancing gut barrier function (i.e. reducing gut permeability).
Objectives
This review aimed to evaluate the benefits and harms of synbiotics, prebiotics, and probiotics for people with CKD.
Search methods
We searched the Cochrane Kidney and Transplant Register of Studies up to 9 October 2023 through contact with the Information Specialist using search terms relevant to this review. Studies in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Registry Platform (ICTRP) Search Portal and ClinicalTrials.gov.
Selection criteria
We included randomised controlled trials (RCTs) measuring and reporting the effects of synbiotics, prebiotics, or probiotics in any combination and any formulation given to people with CKD (CKD stages 1 to 5, including dialysis and kidney transplant). Two authors independently assessed the retrieved titles and abstracts and, where necessary, the full text to determine which satisfied the inclusion criteria.
Data collection and analysis
Data extraction was independently carried out by two authors using a standard data extraction form. Summary estimates of effect were obtained using a random‐effects model, and results were expressed as risk ratios (RR) and their 95% confidence intervals (CI) for dichotomous outcomes, and mean difference (MD) or standardised mean difference (SMD) and 95% CI for continuous outcomes. The methodological quality of the included studies was assessed using the Cochrane risk of bias tool. Data entry was carried out by one author and cross‐checked by another. Confidence in the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.
Main results
Forty‐five studies (2266 randomised participants) were included in this review. Study participants were adults (two studies in children) with CKD ranging from stages 1 to 5, with patients receiving and not receiving dialysis, of whom half also had diabetes and hypertension.
No studies investigated the same synbiotic, prebiotic or probiotic of similar strains, doses, or frequencies. Most studies were judged to be low risk for selection bias, performance bias and reporting bias, unclear risk for detection bias and for control of confounding factors, and high risk for attrition and other biases.
Compared to prebiotics, it is uncertain whether synbiotics improve estimated glomerular filtration rate (eGFR) at four weeks (1 study, 34 participants: MD ‐3.80 mL/min/1.73 m², 95% CI ‐17.98 to 10.38), indoxyl sulfate at four weeks (1 study, 42 participants: MD 128.30 ng/mL, 95% CI ‐242.77 to 499.37), change in gastrointestinal (GI) upset (borborymgi) at four weeks (1 study, 34 participants: RR 15.26, 95% CI 0.99 to 236.23), or change in GI upset (Gastrointestinal Symptom Rating Scale) at 12 months (1 study, 56 participants: MD 0.00, 95% CI ‐0.27 to 0.27), because the certainty of the evidence was very low.
Compared to certain strains of prebiotics, it is uncertain whether a different strain of prebiotics improves eGFR at 12 weeks (1 study, 50 participants: MD 0.00 mL/min, 95% CI ‐1.73 to 1.73), indoxyl sulfate at six weeks (2 studies, 64 participants: MD ‐0.20 μg/mL, 95% CI ‐1.01 to 0.61; I² = 0%) or change in any GI upset, intolerance or microbiota composition, because the certainty of the evidence was very low.
Compared to certain strains of probiotics, it is uncertain whether a different strain of probiotic improves eGFR at eight weeks (1 study, 30 participants: MD ‐0.64 mL/min, 95% CI ‐9.51 to 8.23; very low certainty evidence).
Compared to placebo or no treatment, it is uncertain whether synbiotics improve eGFR at six or 12 weeks (2 studies, 98 participants: MD 1.42 mL/min, 95% CI 0.65 to 2.2) or change in any GI upset or intolerance at 12 weeks because the certainty of the evidence was very low.
Compared to placebo or no treatment, it is uncertain whether prebiotics improves indoxyl sulfate at eight weeks (2 studies, 75 participants: SMD ‐0.14 mg/L, 95% CI ‐0.60 to 0.31; very low certainty evidence) or microbiota composition because the certainty of the evidence is very low.
Compared to placebo or no treatment, it is uncertain whether probiotics improve eGFR at eight, 12 or 15 weeks (3 studies, 128 participants: MD 2.73 mL/min, 95% CI ‐2.28 to 7.75; I² = 78%), proteinuria at 12 or 24 weeks (1 study, 60 participants: MD ‐15.60 mg/dL, 95% CI ‐34.30 to 3.10), indoxyl sulfate at 12 or 24 weeks (2 studies, 83 participants: MD ‐4.42 mg/dL, 95% CI ‐9.83 to 1.35; I² = 0%), or any change in GI upset or intolerance because the certainty of the evidence was very low. Probiotics may have little or no effect on albuminuria at 12 or 24 weeks compared to placebo or no treatment (4 studies, 193 participants: MD 0.02 g/dL, 95% CI ‐0.08 to 0.13; I² = 0%; low certainty evidence).
For all comparisons, adverse events were poorly reported and were minimal (flatulence, nausea, diarrhoea, abdominal pain) and non‐serious, and withdrawals were not related to the study treatment.
Authors' conclusions
We found very few studies that adequately test biotic supplementation as alternative treatments for improving kidney function, GI symptoms, dialysis outcomes, allograft function, patient‐reported outcomes, CVD, cancer, reducing uraemic toxins, and adverse effects.
We are not certain whether synbiotics, prebiotics, or probiotics are more or less effective compared to one another, antibiotics, or standard care for improving patient outcomes in people with CKD. Adverse events were uncommon and mild.
Keywords: Adult; Child; Humans; Dysbiosis; Dysbiosis/complications; Dysbiosis/therapy; Indican; Prebiotics; Probiotics; Probiotics/therapeutic use; Renal Insufficiency, Chronic; Renal Insufficiency, Chronic/complications; Renal Insufficiency, Chronic/therapy; Synbiotics; Uremic Toxins
Plain language summary
Prebiotics (dietary fibre), probiotics (good bacteria) or synbiotics (prebiotics plus probiotics) for people with chronic kidney disease
Key messages
Chronic kidney disease (CKD) is a serious health problem that affects over 850 million people worldwide. People with kidney disease have an unhealthy balance of good and bad bacteria in their guts, called 'gut dysbiosis'. This imbalance arises because of the effects of reduced kidney function (retained toxic waste products, fluid retention causing the gut wall to swell), drugs frequently used in people with CKD (especially antibiotics), and dietary restrictions placed on people with CKD.
Gut dysbiosis can, in turn, cause or worsen CKD because bacteria can produce toxins that cross the bowel wall and damage the kidneys. Gut dysbiosis can also cause stomach problems (like bloating, cramping, constipation and diarrhoea) and reduce quality of life.
To improve the balance of the gut flora, good bacteria can be taken in tablets of high doses of prebiotics and probiotics. Prebiotics, or indigestible plant fibre, can encourage the growth of good bacteria. Synbiotics are a combination of prebiotics and probiotics. Some research suggests that taking high doses of the good bacteria can re‐balance the good bacteria in people's gut, thereby improving bowel symptoms and the conditions that lead to worsening of CKD.
What did we do?
We reviewed all of the evidence on synbiotics, prebiotics and probiotics to see whether they can improve outcomes in people who have CKD (all stages 1 to 5).
What did we find?
We found 45 studies randomising 2266 participants. Half of these looked at participants receiving dialysis (mostly haemodialysis), and the other half not receiving dialysis. Half also had diabetes and hypertension.
We are uncertain whether synbiotics, prebiotics, or probiotics improve bowel outcomes, quality of life, kidney toxin levels or kidney function.
The quality of the evidence that we found is low quality and very low certainty. All studies were conducted using moderate to poor‐quality methods with too few patients.
Summary
Currently, we do not have enough information from trials to know whether synbiotics, prebiotics or probiotics work to improve bowel symptoms, quality of life, kidney toxin levels, or kidney function in people with CKD. Ten studies are currently ongoing; therefore, it is possible that findings may change with the inclusion of these studies in future updates.
The evidence is up to date to 9 October 2023.
Summary of findings
Summary of findings 1. Synbiotic versus another synbiotic for people with chronic kidney disease.
Synbiotic versus another synbiotic for people with chronic kidney disease | |||||
Patient or population: people with CKD Setting: hospital or primary care Intervention: synbiotic 2 Comparison: synbiotic 1 | |||||
Outcomes | Anticipated absolute effects* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Certainty of the evidence (GRADE) | |
Risk with synbiotic 1 | Risk with synbiotic 2 | ||||
eGFR | ‐ | ‐ | ‐ | ‐ | ‐ |
Albuminuria or proteinuria | ‐ | ‐ | ‐ | ‐ | ‐ |
Indoxyl sulfate | ‐ | ‐ | ‐ | ‐ | ‐ |
Change in any GI upset or intolerance | ‐ | ‐ | ‐ | ‐ | ‐ |
Microbiota composition | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; CKD: chronic kidney disease; eGFR: (estimated) glomerular filtration rate; GI: gastrointestinal; RCT: randomised controlled trial; RR: risk ratio. | |||||
GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect. |
No data were reported for these outcomes under this comparison.
Summary of findings 2. Synbiotic versus prebiotic for people with chronic kidney disease.
Synbiotic versus prebiotic for people with chronic kidney disease | |||||
Patient or population: people with CKD Setting: hospital or primary care Intervention: synbiotic Comparison: prebiotic | |||||
Outcomes | Anticipated absolute effects* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Certainty of the evidence (GRADE) | |
Risk with prebiotic | Risk with synbiotic | ||||
eGFR (mL/min) Follow‐up: 4 weeks |
CKD stage 3Ga (transplant) | ‐ | 34 (1) | ⊕⊝⊝⊝ very low1 | |
The mean eGFR was 3.8 mL/min lower (17.98 lower to 10.38 higher) with synbiotic compared prebiotic | |||||
Albuminuria or proteinuria | ‐ | ‐ | ‐ | ‐ | ‐ |
Indoxyl sulfate (ng/mL) Follow‐up: 4 weeks |
CKD stage G5D | ‐ | 42 (1) | ⊕⊝⊝⊝ very low1 | |
The mean indoxyl sulfate was 128.3 ng/mL higher (242.77 lower to 499.37 higher) with synbiotic compared prebiotic | |||||
Change in any GI upset (borborygmi) Follow‐up: 4 weeks |
CKD stage 3Ga (transplant) | RR 15.26 (0.99 to 236.23) | 34 (1) | ⊕⊝⊝⊝ very low1 | |
0 per 1,000 | 0 per 1,000 (0 to 0) | ||||
Change in any GI upset (GSRS total index) Follow‐up: 12 months |
CKD stage 3 to 4 | 56 (1) | ⊕⊝⊝⊝ very low1 | ||
The mean change in any GI upset was 0.00 (0.27 lower to 0.27 higher) with synbiotic compared prebiotic | |||||
Microbiota composition | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CI: confidence interval; CKD: chronic kidney disease; eGFR: estimated glomerular filtration rate; GI: gastrointestinal; RR: risk ratio; RCT: randomised controlled trial | |||||
GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect. |
1 Downgraded twice for serious risk of bias, and once for sparse or small study data.
Summary of findings 3. Prebiotic versus another prebiotic for people with chronic kidney disease.
Prebiotic versus another prebiotic for people with chronic kidney disease | |||||
Patient or population: people with CKD Setting: hospital or primary care Intervention: prebiotic 2 Comparison: prebiotic 1 | |||||
Outcomes | Anticipated absolute effects* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Certainty of the evidence (GRADE) | |
Risk with prebiotic 1 | Risk with prebiotic 2 | ||||
eGFR (mL/min) Follow‐up: 12 weeks |
CKD stage 3 to 5 (non‐dialysis) | ‐ | 50 (1) | ⊕⊝⊝⊝ very low1 | |
The mean eGFR was 0 mL/min lower (1.73 lower to 1.73 higher) with prebiotic 2 compared to prebiotic 1 | |||||
Albuminuria or proteinuria | ‐ | ‐ | ‐ | ‐ | ‐ |
Indoxyl sulfate (μg/mL) Follow‐up: 6 weeks |
CKD stage G5D with diabetes | ‐ | 64 (2) | ⊕⊝⊝⊝ very low1 | |
The mean indoxyl sulfate was 0.2 μg/mL lower (1.01 lower to 0.61 higher) with prebiotic 2 compared to prebiotic 1 | |||||
Change in any GI upset or intolerance Follow‐up: 4 weeks |
CKD stage G5D with diabetes | ‐ | 24 (1) | ⊕⊝⊝⊝ very low1 | |
Burping | The mean burping was 0.17 higher (0.5 lower to 0.84 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Cramping | The mean cramping was 0.17 lower (0.5 lower to 0.16 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Distension | The mean distension was 0.33 higher (0.04 lower to 0.7 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Flatulence | The mean flatulence was 1 higher (0.25 higher to 1.75 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Nausea | The mean nausea was 0 (0 to 0 ) with prebiotic 2 compared to prebiotic 1 | ||||
Reflux | The mean reflux was 0 (0.5 lower to 0.5 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Rumblings | The mean rumblings was 0.5 higher (0.14 lower to 1.14 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Microbiota composition Follow‐up: 4 weeks |
CKD stage G5D with diabetes | ‐ | 24 (1) | ‐ | |
Actinobacteria | The mean Actinobacteria was 1.26 lower (4.46 lower to 1.94 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Bacteriodetes | The mean Bacteriodetes was 3.23 higher (8.24 lower to 14.7 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Proteobacteria | The mean Proteobacteria was 0.11 higher (1.61 lower to 1.83 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Firmicutes | The mean Firmicutes was 2.44 lower (14.19 lower to 9.31 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Synergistetes | The mean Synergistetes was MD 0.25 lower (0.89 lower to 0.39 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Verrucomicrobia | The mean Verrucomicrobia was 0.96 higher (1.36 lower to 3.28 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Faecal acetate | The mean faecal acetate was 69.91 lower (203.95 lower to 64.13 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Faecal propionate | The mean faecal propionate was 19.35 lower (63.87 lower to 25.17 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Faecal butyrate | The mean faecal butyrate was 11.04 lower (39.57 lower to 17.49 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Faecal total short‐chain fatty acids | The mean faecal total short‐chain fatty acids were 104.71 lower (293.34 lower to 83.92 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Faecal total short‐chain fatty acids | The mean faecal total short‐chain fatty acids were 104.71 lower (293.34 lower to 83.92 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Faecal indoles | The mean faecal indoles were 2.71 higher (69.78 lower to 75.2 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Faecal P‐cresol | The mean faecal p‐cresol was 28.84 higher (105.07 lower to 162.75 higher) with prebiotic 2 compared to prebiotic 1 | ||||
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CKD: chronic kidney disease; CI: confidence interval; eGFR: estimated glomerular filtration rate; GI: gastrointestinal; RR: risk ratio; RCT: randomised controlled trial | |||||
GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect. |
1 Downgraded twice for serious risk of bias, and once for sparse or small study data.
Summary of findings 4. Prebiotic versus probiotic for people with chronic kidney disease.
Prebiotic versus probiotic for people with chronic kidney disease | |||||
Patient or population: people with CKD Settings: hospital or primary care Intervention: prebiotic Comparison: probiotic | |||||
Outcomes | Illustrative comparative risks* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Quality of the evidence (GRADE) | |
Assumed risk | Corresponding risk | ||||
Risk with probiotic | Risk with prebiotic | ||||
eGFR | ‐ | ‐ | ‐ | ‐ | ‐ |
Albuminuria or proteinuria | ‐ | ‐ | ‐ | ‐ | ‐ |
Indoxyl sulfate | ‐ | ‐ | ‐ | ‐ | ‐ |
Change in any GI upset or intolerance | ‐ | ‐ | ‐ | ‐ | ‐ |
Microbiota composition | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CKD: chronic kidney disease; CI: confidence interval; eGFR: estimated glomerular filtration rate; GI: gastrointestinal; RCT: randomised controlled trial | |||||
GRADE Working Group grades of evidence High quality: Further research is very unlikely to change our confidence in the estimate of effect. Moderate quality: Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate. Low quality: Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate. Very low quality: We are very uncertain about the estimate. |
No data were reported for these outcomes under this comparison.
Summary of findings 5. Probiotic versus another probiotic for people with chronic kidney disease.
Probiotic versus another probiotic for people with chronic kidney disease | |||||
Patient or population: people with CKD Setting: hospital or primary care Intervention: probiotic 2 Comparison: probiotic 1 | |||||
Outcomes | Anticipated absolute effects* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Certainty of the evidence (GRADE) | |
Risk with probiotic 1 | Risk with probiotic 2 | ||||
eGFR (mL/min) Follow‐up: 8 weeks |
CKD stage G3 to G4 | ‐ | 30 (1) | ⊕⊝⊝⊝ very low1 | |
The mean eGFR was 0.64 mL/min lower (9.51 lower to 8.23 higher) with probiotic 2 than probiotic 1 | |||||
Albuminuria or proteinuria | ‐ | ‐ | ‐ | ‐ | ‐ |
Indoxyl sulfate | ‐ | ‐ | ‐ | ‐ | ‐ |
Change in any GI upset or intolerance | ‐ | ‐ | ‐ | ‐ | ‐ |
Microbiota composition | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CKD: chronic kidney disease; CI: confidence interval; eGFR: estimated glomerular filtration rate; GI: gastrointestinal; RR: risk ratio; RCT: randomised controlled trial | |||||
GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect. |
1 Downgraded twice for serious risk of bias, and once for sparse or small study data.
Summary of findings 6. Synbiotic versus placebo or no treatment for people with chronic kidney disease.
Synbiotic versus placebo or no treatment for people with chronic kidney disease | |||||
Patient or population: people with CKD Setting: hospital or primary care Intervention: synbiotic Comparison: placebo or no treatment | |||||
Outcomes | Anticipated absolute effects* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Certainty of the evidence (GRADE) | |
Risk with placebo or no treatment | Risk with synbiotic | ||||
eGFR (mL/min) Follow‐up: 6 or 12 weeks |
CKD stage G3b | ‐ | 98 (2) | ⊕⊝⊝⊝ very low1 | |
The mean eGFR was 1.42 mL/min higher (0.65 higher to 2.2 higher) with synbiotic than placebo or no treatment | |||||
Albuminuria or proteinuria | ‐ | ‐ | ‐ | ‐ | ‐ |
Indoxyl sulfate | ‐ | ‐ | ‐ | ‐ | ‐ |
Change in any GI upset or intolerance (GSRS) Follow‐up: 12 weeks |
CKD stage 3b | ‐ | 23 (1) | ⊕⊝⊝⊝ very low1 | |
Rumbling | The mean rumbling was 0.54 GSRS lower (0.77 lower to 0.31 lower) with synbiotic than placebo or no treatment | ||||
Hard stools | The mean hard stools was 0.09 GSRS lower (0.35 lower to 0.17 higher) with synbiotic than placebo or no treatment | ||||
Abdominal pain | The mean abdominal pain was 0.22 GSRS higher (0.02 lower to 0.46 higher) with synbiotic than placebo or no treatment | ||||
Constipation syndrome | The mean constipation syndrome was 0.17 GSRS lower (0.72 lower to 0.38 higher) with synbiotic than placebo or no treatment | ||||
Microbiota composition | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CKD: chronic kidney disease; CI: confidence interval; eGFR: estimated glomerular filtration rate; GI: gastrointestinal; RR: risk ratio; RCT: randomised controlled trial | |||||
GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect. |
1 Downgraded twice for serious risk of bias, and once for sparse or small study data.
Summary of findings 7. Prebiotic versus placebo or no treatment for people with chronic kidney disease.
Prebiotic versus placebo or no treatment for people with chronic kidney disease | |||||
Patient or population: people with CKD Setting: hospital or primary care Intervention: prebiotic Comparison: placebo or no treatment | |||||
Outcomes | Anticipated absolute effects* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Certainty of the evidence (GRADE) | |
Risk with placebo or no treatment | Risk with prebiotic | ||||
eGFR | ‐ | ‐ | ‐ | ‐ | ‐ |
Albuminuria or proteinuria | ‐ | ‐ | ‐ | ‐ | ‐ |
Indoxyl sulfate (mg/L) Follow‐up: 8 weeks |
CKD stage G5D | ‐ | 75 (2) | ⊕⊝⊝⊝ very low1 | |
The mean indoxyl sulfate was 0.14 mg/L lower (0.6 lower to 0.31 higher) with prebiotic than placebo or no treatment | |||||
Any change in GI upset or intolerance | ‐ | ‐ | ‐ | ‐ | ‐ |
Microbiota composition Follow‐up: 8 weeks |
CKD stage 5GD | ‐ | 44 (1) | ⊕⊝⊝⊝ very low1 | |
Faecalibacterium | The mean Faecalibacterium was 2.37 higher (0.23 higher to 4.51 higher) with prebiotic than placebo or no treatment | ||||
Parabacteroides | The mean Parabacteroides was 0.22 higher (0.06 higher to 0.38 higher) with prebiotic than placebo or no treatment | ||||
Bifidobacteria | The mean Bifidobacteria was 3.92 lower (9.83 lower to 1.99 higher) with prebiotic than placebo or no treatment | ||||
Ruminococcus | The mean Ruminococcus was 3.86 higher (0.32 lower to 8.04 higher) with prebiotic than placebo or no treatment | ||||
Prevotella | The mean Prevotella was 0.43 lower (1.45 lower to 0.59 higher) with prebiotic than placebo or no treatment | ||||
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CKD: chronic kidney disease; CI: confidence interval; eGFR: estimated glomerular filtration rate; GI: gastrointestinal; RR: risk ratio; RCT: randomised controlled trial | |||||
GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect. |
1 Downgraded twice for serious risk of bias, and once for sparse or small study data.
Summary of findings 8. Probiotic versus placebo or no treatment for people with chronic kidney disease.
Probiotic versus placebo or no treatment for people with chronic kidney disease | |||||
Patient or population: people with CKD Setting: hospital or primary care Intervention: probiotic Comparison: placebo or no treatment | |||||
Outcomes | Anticipated absolute effects* (95% CI) | Relative effect (95% CI) | No. of participants (RCTs) | Certainty of the evidence (GRADE) | |
Risk with placebo or no treatment | Risk with probiotic | ||||
eGFR (mL/min) Follow‐up: 8, 12 or 15 weeks |
CKD stage 1 with type 2 diabetes mellitus | ‐ | 40 (1) | ⊕⊝⊝⊝ very low1 | |
The mean eGFR was 12.1 mL/min higher (4.19 higher to 20.01 higher) with probiotic than placebo or no treatment | |||||
CKD stage 3A with diabetes and hypertension | ‐ | 28 (1) | |||
The mean eGFR mL/min was 0.4 higher (4.15 lower to 4.95 higher) with probiotic than placebo or no treatment | |||||
CKD stage G5D with diabetes and hypertension | ‐ | 60 (1) | |||
The mean eGFR was 0.02 mL/min higher (0.63 lower to 0.67 higher) with probiotic than placebo or no treatment | |||||
Albuminuria (g/dL) Follow‐up: 12 or 24 weeks |
CKD stage G5D | ‐ | 33 (1) | ⊕⊕⊝⊝ low2 | |
The mean albuminuria was 0 g/dL (0.19 lower to 0.19 higher) with probiotic than placebo or no treatment | |||||
CKD stage G5D with diabetes and hypertension | ‐ | 160 (3) | |||
The mean albuminuria was 0.03 g/dL higher (0.1 lower to 0.16 higher) with probiotic than placebo or no treatment | |||||
Proteinuria (mg/dL) Follow‐up: 12 or 24 weeks |
CKD stages 1 to 5 with diabetic nephropathy | ‐ | 60 (1) | ⊕⊝⊝⊝ very low1 | |
The mean albuminuria was 15.6 g/dL (34.3 lower to 3.1 higher) with probiotic than placebo or no treatment | |||||
Indoxyl sulfate (mg/dL) Follow‐up: 12 or 24 weeks |
CKD stage G5D | ‐ | 33 (1) | ⊕⊝⊝⊝ very low1 | |
The mean indoxyl sulfate was 6 mg/dL lower (15.02 lower to 3.02 higher) with probiotic than placebo or no treatment | |||||
CKD stage G5D with diabetes and hypertension | ‐ | 50 (1) | ⊕⊝⊝⊝ very low1 | ||
The mean indoxyl sulfate was 3.14 mg/dL lower (10.26 lower to 3.98 higher) with probiotic than placebo or no treatment | |||||
Change in any GI upset or intolerance (abdominal pain/diarrhoea) Follow‐up: 12 weeks |
CKD stage G5D | RR 2.13 (0.21 to 21.22) | 33 (1) | ⊕⊝⊝⊝ very low1 | |
59 per 1,000 | 125 per 1,000 (12 to 1,000) | ||||
Change in any GI upset or intolerance (constipation) Follow‐up: 12 weeks |
CKD stage G5D | RR 3.18 (0.14 to 72.75) | 33 (1) | ⊕⊝⊝⊝ very low1 | |
0 per 1,000 | 0 per 1,000 (0 to 0) | ||||
Microbiota composition | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft function | ‐ | ‐ | ‐ | ‐ | ‐ |
Graft infection | ‐ | ‐ | ‐ | ‐ | ‐ |
*The risk in the intervention group (and its 95% CI) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). CKD: chronic kidney disease; CI: confidence interval; eGFR: estimated glomerular filtration rate; GI: gastrointestinal; RR: risk ratio; RCT: randomised controlled trial | |||||
GRADE Working Group grades of evidence High certainty: we are very confident that the true effect lies close to that of the estimate of the effect. Moderate certainty: we are moderately confident in the effect estimate: the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different. Low certainty: our confidence in the effect estimate is limited: the true effect may be substantially different from the estimate of the effect. Very low certainty: we have very little confidence in the effect estimate: the true effect is likely to be substantially different from the estimate of effect. |
1 Downgraded twice for serious risk of bias, and once for sparse or small study data.
2 Downgraded twice for serious risk of bias.
Background
Description of the condition
Chronic kidney disease
Chronic kidney disease (CKD) is defined as abnormalities of kidney structure or function, present for three months with implications for health (KDIGO 2013). The current classification for CKD has five stages (Appendix 1) classified based on two markers: (1) evidence of kidney damage (presence of proteinuria, microalbuminuria, or structural abnormality) and (2) the sustained impairment of estimated glomerular filtration rate (eGFR) for at least three months. Stages 1 to 3 are considered to be early CKD, at which point patients may have no or limited symptoms (with only urine or blood tests detecting the presence of kidney abnormality). Patients with CKD stages 4 and 5 have advanced‐stage kidney disease and may require or undergo dialysis or transplantation (KDIGO 2013).
The global prevalence of CKD is high, affecting 11% to 13% of the population (Hill 2016). In 2017, an estimated 1.23 million people died from kidney failure, a 33.7% increase from 2007 (GBD 2017). CKD predisposes the patient to a wide range of complications, including cardiovascular disease (CVD), infection, and cancer. Often CKD does not display symptoms until the disease is advanced (Jha 2013) and is therefore often considered to be underestimated as a comorbidity, making the exact prevalence and burden difficult to calculate.
The gut microbiome
The human microbiome is the collective genomes of the micro‐organisms in a particular environment (Valdes 2018) and is of emerging high interest in chronic disease research. The human gut microbiota includes fungi, bacteria, archaea, protozoa, and viruses that all interact with each other and the host to affect the health and physiology of the host (Azad 2018). The human intestine contains more than 10 billion micro‐organisms, and the microbial composition changes from person to person, along both the digestive tract and within the urinary and kidney environments (Aron‐Wisnewsky 2016). Recent culture‐independent studies that use high‐throughput sequencing have indicated that any microbial imbalances (otherwise known as gut dysbiosis or leaky gut) may be associated with cardiometabolic diseases in the long term (such as allergy, asthma, inflammatory bowel disease, celiac disease, systemic lupus erythematosus, arthritis, CKD, diabetes, obesity, and CVD) (Aron‐Wisnewsky 2016; Bromberg 2015).
In people with advanced stages of CKD, uraemia and metabolic acidosis alter the biochemical milieu, promoting disturbances in gut microbiota, the community or micro‐organisms themselves (Valdes 2018) and the intestinal barrier (Mafra 2019). These disturbances, referred to as gut dysbiosis, are further exacerbated by fluid retention with intestinal wall oedema, dietary restrictions and exposure to pharmacologic agents (particularly antibiotics) (Sampai‐Maia 2016). Gut dysbiosis, in turn, frequently leads to gastrointestinal (GI) symptoms (Chan 2020) and has, in turn, been linked with the progression of CKD, in particular, the production of putative uraemic toxins (e.g. indoxyl sulfate, p‐cresol sulfate, phenylacetylglutamine, trimethylamine‐N‐oxide, kynurenine), increased gut permeability, and transmural movement of bacteria and endotoxins leading to inflammation and oxidative stress (Beerepoot 2016; Cao 2022; Cremon 2018; Lehto 2018; Luyckx 2018).
Description of the intervention
Early observational and intervention studies have been investigating food‐intake patterns and various synbiotic interventions (antibiotics, prebiotics, or probiotics) to measure the effects on microbiota in treating cardiometabolic diseases, in particular CKD (Aron‐Wisnewsky 2016).
Prebiotics
The International Scientific Association for Probiotics and Prebiotics (Gibson 2017) defines prebiotics as substrates, or non‐digestible dietary substances, that are selectively utilised and fermented within the small intestine by host micro‐organisms. Modifying or diversifying the host microbiota may induce a health benefit to the host.
Most types of prebiotics are subsets of carbohydrate groups and mostly oligosaccharide carbohydrates (Davani‐Davari 2019).
Fructans: inulin and fructo‐oligosaccharides (stimulate the enrichment of native probiotics Lactobacilli and Bifidobacteria)
Galacto‐oligosaccharides (also known as trans‐galacto‐oligosaccharides): (stimulate the enrichment of native probiotics Lactobacilli, Bifidobacteria, Enterobacteria, Bacteroidetes, and Firmicutes)
Starch and glucose‐derived oligosaccharides: resistant starch, polydextrose
Other oligosaccharides: pectic‐oligosaccharide (from the polysaccharide pectin)
Non‐carbohydrate oligosaccharides: cocoa‐derived flavanols.
Natural sources of prebiotics can be obtained in peas, beans, cow's milk, human breast milk, soybean, rye, tomato, barley, wheat, honey, banana, onion, chicory, garlic, sugar beet, asparagus, and artichoke.
Probiotics
The term probiotics is used to describe live micro‐organisms that are intended to confer health benefits on the host when administered in adequate quantities (FAO/WHO 2002). The living bacteria may modulate the existing composition of gut microbiota to improve the health of the GI tract, the immune system, the inflammatory state and the "bioavailability of micronutrients" (Cremon 2018).
The key microbial organisms often found in probiotic treatments are:
Lactobacillus
Bifidobacterium
Saccharomyces
Streptococcus
Enterococcus
Escherichia
Bacillus
Natural sources of probiotics can be obtained in fermented foods such as yoghurt, kimchi, kombucha, sauerkraut, miso, pickles, raw apple cider vinegar, kefir, tempeh, some cheeses, and some sourdough breads.
Synbiotics
Synbiotics are the combination of prebiotics and probiotics in one treatment with the intention of producing a superior effect compared to either agent alone (Pan 2018). The effect is currently unknown.
Synthetic versions of synbiotics, prebiotics, and probiotics are available as oral capsules, tablets, liquids, or powder forms over‐the‐counter in most developed countries (Cremon 2018).
How the intervention might work
Growing research suggests that high doses of synbiotics, prebiotics, and probiotics are able to modify and improve dysbiosis of gut micro‐organisms by altering the population of the micro‐organisms. With the right balance of gut flora, a primary benefit is (believed to be) the suppression of pathogens through immunostimulation and gut barrier enhancement (reduced permeability of the gut) (Cremon 2018).
Gut microbiota ferments prebiotics and produces short‐chain fatty acids (lactic acid, butyric acid, propionic acid), which have positive effects on the airways and dendritic cells in the bone marrow, and decrease the pH of the colon (Davani‐Davari 2019). Prebiotics also decrease the gut pH, resulting in the butyrogenic effect ‐ where a slight change in the unit of change in pH alters the entire composition or population of acid‐sensitive species (Bacterioides) and promotes butyrate formation of Firmicutes (Davani‐Davari 2019).
Probiotics alter the intestinal pH, inhibit pathogens (via the generation of antibacterial compounds, competitively eliminating pathogens in receptor binding sites and competing for available nutrients), inhibit the production of mutagenic and carcinogenic substances, and maintain the intestinal barrier (Kato 2008).
Why it is important to do this review
Prebiotics and probiotics are freely available as over‐the‐counter purchases in most high‐income countries and are being used as therapeutic supplements for improving the function and balance of gut microbiota in the general population. Whilst many positive effects have been identified, the exact mechanism of action by which these compounds exert their beneficial actions in humans is only partially understood (Cremon 2018). In the general population, there is no definitive data to support the use of synbiotics, prebiotics, or probiotics. In CKD, there are uncertain effects in people with reduced kidney function because of the risk of catastrophic infections from the live micro‐organisms in patients who are immunocompromised. The efficacy of these interventions and the certainty of the evidence in CKD patients remains unknown, and it is imperative to synthesise the benefits and harms associated with these treatments.
Objectives
This review aims to look at the benefits and harms of synbiotics, prebiotics, and probiotics for people with CKD.
Methods
Criteria for considering studies for this review
Types of studies
All randomised controlled trials (RCTs) and quasi‐RCTs (RCTs in which allocation to treatment was obtained by alternation, use of alternate medical records, date of birth or other predictable methods) and cluster RCTs were included. Unblinded, single and double‐blind studies were included.
Cross‐over studies were included, and only data from the first phase was used for analysis.
Full journal publication and peer review were required. Unpublished clinical studies with online results available were, however, included.
Studies in any healthcare setting were included.
Excluded study designs: abstracts, single‐arm studies, commentaries, editorials, and clinical observations.
Types of participants
Inclusion criteria
Adults and children with CKD (stages 1 to 5), receiving dialysis, and kidney transplant recipients.
Studies of populations with altered GI function and diabetic kidney disease were included and analysed as subgroups.
Exclusion criteria
Studies of populations receiving enteral nutrition.
Adults and children who have signs of systemic illness (such as fever, loin pain, toxicity).
Types of interventions
Any synbiotic, prebiotic, or probiotic treatment compared to another, other pharmacological, non‐pharmacological, placebo, or no treatment
Any route of administration, dose, duration, or frequency
Formulations such as oral tablets and capsules, liquids, and powders
Combination therapies of synbiotics, prebiotics, or probiotics with other pharmacological treatments or non‐pharmacological treatments were analysed as separate comparisons.
Participants receiving concurrent pharmacological medications for co‐morbidities, such as blood glucose medications, blood pressure medications, and immunosuppressants, were included, and we planned to analyse these as subgroups.
Studies of high‐dose prebiotics for the purpose of purgation and studies of dietary changes were excluded.
Comparison pairs for analysis
A synbiotic, prebiotic, or probiotic treatment versus another synbiotic, prebiotic, or probiotic
A synbiotic, prebiotic, or probiotic treatment versus any other pharmacological comparator (antibiotics, immunosuppressants, other medicines)
A synbiotic, prebiotic, or probiotic treatment versus another non‐pharmacological comparator (dietary, educational, behavioural, vitamin or herbal supplements, Traditional Chinese Medicine)
Any synbiotic, prebiotic, or probiotic treatment versus placebo
Any synbiotic, prebiotic, or probiotic treatment versus no treatment
Any synbiotic, prebiotic, or probiotic treatment versus a combination treatment (any of the above)
Any synbiotic, prebiotic, or probiotic treatment in combination with any of the above versus any of the above comparators.
For each of these comparisons, synbiotics, prebiotics, and probiotics were analysed as separate comparisons.
Types of outcome measures
This review did not exclude studies based on non‐reporting of outcomes of interest.
The outcomes selected include the relevant SONG core outcome sets as specified by the Standardised Outcomes in Nephrology initiative (SONG 2017).
Primary outcomes
Kidney function: eGFR; serum creatinine (SCr); albuminuria; proteinuria; infection (including pyelonephritis or urosepsis)
Uraemic toxins: urea; indoxyl sulfate; p‐cresyl sulfate; trimethylamine N‐oxide; phenylacetylglutamine; kynurenine
GI function: change in any GI upset or intolerance; microbiota composition; faecal characteristics (such as the Bristol Stool Chart) (Lewis 1997); colonic transit time.
Secondary outcomes
Dialysis outcomes: peritoneal dialysis (PD) or haemodialysis (HD) infection; vascular access; technique survival; dialysis failure
Transplant function: need for transplant; graft survival/health
Patient‐reported outcomes: pain rating using any validated pain scale; quality of life (QoL) (using any validated scale); fatigue; life participation
Adverse events: any adverse events (including infection); serious adverse events (including death); withdrawals due to adverse events. Potential (but not limited to) events include GI responses, nausea, vomiting, diarrhoea, and constipation
CVD
Cancer
Search methods for identification of studies
Electronic searches
We searched the Cochrane Kidney and Transplant Register of Studies up to 9 October 2023 through contact with the Information Specialist using search terms relevant to this review. The Register contains studies identified from the following sources.
Monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL)
Weekly searches of MEDLINE OVID SP
Searches of kidney and transplant journals and the proceedings and abstracts from major kidney and transplant conferences
Searching of the current year of EMBASE OVID SP
Weekly current awareness alerts for selected kidney and transplant journals
Searches of the International Clinical Trials Registry Platform (ICTRP) Search Portal and ClinicalTrials.gov.
Studies contained in the Register are identified through searches of CENTRAL, MEDLINE, and EMBASE based on the scope of Cochrane Kidney and Transplant. Details of search strategies, as well as a list of handsearched journals, conference proceedings and current awareness alerts, are available on the Cochrane Kidney and Transplant website.
See Appendix 2 for search terms used in strategies for this review.
Searching other resources
Reference lists of review articles, relevant studies, and clinical practice guidelines.
Contacting relevant individuals/organisations seeking information about unpublished or incomplete studies.
Grey literature sources (e.g. abstracts, dissertations, and theses), in addition to those already included in the Cochrane Kidney and Transplant Register of Studies, were not searched.
Data collection and analysis
Selection of studies
The search strategy described was used to obtain titles and abstracts of studies that may be relevant to the review. The titles and abstracts were screened independently by two authors, who discarded studies that were not applicable; however, studies and reviews that might include relevant data or information on studies were retained initially. Two authors independently assessed the retrieved abstracts and, where necessary, the full text of these studies to determine which studies satisfied the inclusion criteria. Disagreements were resolved in consultation with a third author.
Data extraction and management
Data extraction was carried out independently by two authors using standard data extraction forms. Disagreements were resolved in consultation with a third author. Studies reported in non‐English language journals were translated before assessment. Where more than one publication of one study existed, reports were grouped together, and the publication with the most complete data was used in the analyses. Where relevant outcomes were only published in earlier versions, these data were used. Any discrepancy between published versions was to be highlighted.
Assessment of risk of bias in included studies
The following items were independently assessed by two authors using the risk of bias assessment tool (Higgins 2022) (see Appendix 3).
Was there adequate sequence generation (selection bias)?
Was allocation adequately concealed (selection bias)?
-
Was knowledge of the allocated interventions adequately prevented during the study?
Participants and personnel (performance bias)
Outcome assessors (detection bias)
Were incomplete outcome data adequately addressed (attrition bias)?
Are reports of the study free of suggestion of selective outcome reporting (reporting bias)?
Was the study apparently free of other problems that could put it at risk of bias?
Measures of treatment effect
For dichotomous outcomes (e.g. progression to CKD stage), comparisons between groups were based on risk ratios (RR), the number needed to treat for an additional beneficial outcome (NNT) and pooled differences as absolute measures of effect with 95% confidence intervals (CI).
Where continuous scales of measurement were used to assess the effects of treatment (e.g. pain or decline in kidney function), the mean difference (MD) was used, or the standardised mean difference (SMD) if different scales had been used.
Where possible, we used the mean change score from baseline. We anticipated that some studies may only report the mean endpoint score of which we planned to use the final time point available.
Unit of analysis issues
We only accepted randomisation of the individual participants. For multiple‐dose studies, we used data for the first dose only. For cross‐over studies, we used data from the first phase only.
Dealing with missing data
Any further information required from the original author was requested by written correspondence (e.g. emailing the corresponding author), and any relevant information obtained in this manner was included in the review. Evaluation of important numerical data such as screened, randomised patients as well as intention‐to‐treat (ITT), as‐treated and per‐protocol population was carefully performed. Attrition rates, for example, drop‐outs, losses to follow‐up and withdrawals, were investigated. Issues of missing data and imputation methods (for example, last‐observation‐carried‐forward) were critically appraised (Higgins 2022).
Assessment of heterogeneity
We first assessed the heterogeneity by visual inspection of the forest plot. We quantified statistical heterogeneity using the I² statistic, which describes the percentage of total variation across studies that was due to heterogeneity rather than sampling error (Higgins 2003). A guide to the interpretation of I² values is as follows.
0% to 40%: might not be important
30% to 60%: may represent moderate heterogeneity
50% to 90%: may represent substantial heterogeneity
75% to 100%: considerable heterogeneity.
The importance of the observed value of I² depends on the magnitude and direction of treatment effects and the strength of evidence for heterogeneity (e.g. P‐value from the Chi² test, or a CI for I²) (Higgins 2022).
Assessment of reporting biases
Where possible, funnel plots were planned to be used to assess for the potential existence of small study bias (Higgins 2022).
Data synthesis
Data were pooled using random‐effects models. Fixed‐effect models were also fitted to investigate potential discrepancies with the random‐effects models (e.g., the influence of large studies on the pooled estimates).
Subgroup analysis and investigation of heterogeneity
Subgroup analysis and meta‐regression were planned to be used to explore possible sources of heterogeneity where there was sufficient data. Heterogeneity among participants could be related to the distribution of age, co‐morbidities, and cause of kidney disease. Heterogeneity in treatments could be related to prior agent(s) used and the agent, dose, and duration of therapy. Adverse effects were tabulated and assessed with descriptive techniques, as they were likely to be different for the various agents used (this was conducted as part of the meta‐analysis as adverse events were a secondary outcome). Where possible, the risk difference (RD) with 95% CI was calculated for each adverse event, either compared to no treatment or to another agent.
Planned subgroups where sufficient data were available.
CKD stage: 1 to 5 pre‐dialysis, dialysis, transplant, diabetes, hypertension
Dose (to be determined upon presentation of available data)
Timepoint: short‐term, long‐term (to be determined upon presentation of available data)
Level of GI function or GI issues (to be determined upon presentation of available data)
Age: children (< 18 years), adults (> 18 years).
Sensitivity analysis
We planned to undertake sensitivity analyses (however, this was not possible) to explore the influence of the following factors on effect size.
Repeating the analysis, excluding unpublished studies
Repeating the analysis, taking account of the risk of bias, as specified
Repeating the analysis, excluding any very long or large studies to establish how much they dominate the results
Repeating the analysis excluding studies using the following filters: diagnostic criteria, language of publication, source of funding (industry versus other), and country.
Summary of findings and assessment of the certainty of the evidence
We presented the main results of the review in 'Summary of findings' tables. These tables present key information concerning the certainty of the evidence, the magnitude of the effects of the interventions examined, and the sum of the available data for the main outcomes (Schünemann 2022a).
The 'Summary of findings' tables also include an overall grading of the evidence related to each of the main outcomes using the GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach (GRADE 2008; GRADE 2011). The GRADE approach defines the certainty of a body of evidence as the extent to which one can be confident that an estimate of effect or association is close to the true quantity of specific interest. This was assessed by two authors. A summary of the assessment process is in Appendix 4. The certainty of a body of evidence involves consideration of within‐trial risk of bias (methodological quality), directness of evidence, heterogeneity, precision of effect estimates and risk of publication bias (Schünemann 2022b). We planned to present the following outcomes in the 'Summary of findings' tables.
Changes in kidney function: eGFR
Changes in kidney function: kidney damage (albuminuria, proteinuria)
Uraemic toxins: free and protein‐bound concentrations of serum indoxyl sulfate
GI function: change in any GI upset or intolerance
GI function: microbiota composition
Transplant function: graft function
Transplant function: graft infection
Results
Description of studies
The following section contains broad descriptions of the studies considered in this review. For further details on each individual study, please see the characteristics of studies tables (Characteristics of included studies; Characteristics of excluded studies; Characteristics of studies awaiting classification; Characteristics of ongoing studies).
Results of the search
Our search of the Specialised Register up to 9 October 2023 identified a total of 161 records. After screening titles and abstracts and full‐text review, 45 studies (88 reports) were included, 21 studies (29 reports) were excluded, 12 studies were identified as ongoing, and 12 abstracts (17 reports) are awaiting classification. We will include ongoing and abstracts awaiting classification in a future update of this review (Figure 1).
1.
Study flow diagram.
Included studies
Forty‐five studies, randomising 2274 participants, met our inclusion criteria (Characteristics of included studies).
Thirty‐seven studies were single‐centre, and eight studies were multicentre. All studies took place in a research centre or hospital outpatient setting in Australia, Belgium, Brazil, Canada, China, France, Indonesia, Iran, Italy, Mexico, Saudi Arabia, South Africa, and the USA.
Sample sizes ranged from 13 (Biruete 2017) to 124 (Xie 2015a) participants.
Twenty‐five studies investigated participants with CKD stage 5D (dialysis), 18 studies investigated participants with stages 1 to 5 non‐dialysis, and two studies investigated kidney transplant or simultaneous pancreas‐kidney (SPK) transplant recipients (Guida 2017; PREBIOTIC 2022). Twenty‐nine studies included participants who had diabetes, and 24 studies included participants who had hypertension.
Forty‐three studies investigated adults 18 years and older, and two studies investigated adults and children of all ages (Mirzaeian 2020; Xie 2015a).
Thirty‐two studies compared two parallel arms, three studies compared three parallel arms (Elamin 2017; Haghighat 2019; Xie 2015a), 10 studies compared a cross‐over treatment with either a washout period (Biruete 2017; de Andrade 2021; Esgalhado 2018; He 2022; Li 2020; Natarajan 2014; Poesen 2016; SYNERGY 2014) or no washout period (Bliss 1992; Ranganathan 2009).
Comparisons
One study investigated a synbiotic to another synbiotic (Haghighat 2019)
Seven studies investigated a synbiotic to a prebiotic (Guida 2014; Guida 2017; Haghighat 2019; Lopes 2018; Mirzaeian 2020; SYNERGY 2014; SYNERGY II 2021)
Nine studies investigated a prebiotic to a prebiotic (Biruete 2017; Bliss 1992; Elamin 2017; He 2022; Li 2020; Poesen 2016; Ramos 2019; Sirich 2014; Xie 2015a)
Two studies investigated a prebiotic to a probiotic (Natarajan 2014; Wang 2015a)
One study investigated a probiotic to another probiotic (Miranda Alatriste 2014)
Six studies compared a synbiotic to placebo (Cosola 2021; Dehghani 2016; Kooshki 2019; Lydia 2022; Soleimani 2017; Viramontes‐Horner 2015)
Six studies investigated a prebiotic to placebo (de Andrade 2021; Esgalhado 2018; Khosroshahi 2018; Pan 2021; PREBIOTIC 2022; Xie 2015a)
Ten studies investigated a probiotic to placebo (Borges 2018; de Araujo 2022; Eidi 2018; Lim 2021; Liu 2020; Mafi 2018; Mazruei Arani 2019; Ranganathan 2009; Shariaty 2017; Soleimani 2017)
Two studies investigated a prebiotic to no treatment (Ebrahim 2022; Meng 2019)
Two studies investigated a probiotic to no treatment (Abbasi 2017; Miraghajani 2017)
Twenty‐eight studies contributed data to our meta‐analyses, 11 studies did not report data for our planned outcomes or data was not reported in a useable way to be meta‐analysed (de Araujo 2022; Ebrahim 2022; Elamin 2017; Kooshki 2019; Lydia 2022; Miraghajani 2017; Pan 2018; PREBIOTIC 2022; Shariaty 2017; Soleimani 2017; Xie 2015a), and six were cross‐over studies and did not report separate data for the first phase of the study (de Andrade 2021; He 2022; Natarajan 2014; Poesen 2016; Ranganathan 2009; SYNERGY 2014).
Excluded studies
Following full‐text review, we excluded 21 studies (Characteristics of excluded studies). Eleven studies were undertaken in the wrong population, nine studies investigated the wrong intervention, and one study was of ineligible study design.
Ongoing studies and studies awaiting classification
Twenty‐six ongoing studies were identified on trial registries or had published an a priori protocol (Characteristics of ongoing studies), and 12 abstracts were identified (Characteristics of studies awaiting classification). These studies will be assessed in a future update of this review.
Risk of bias in included studies
See Figure 2 for a graphical summary of the risk of bias assessment within each study.
2.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Most studies were characterised by an unclear risk of bias across most domains due to the lack of information and detail provided to permit judgement.
Using funnel plots to detect publication bias was not feasible due to the lack of available data to analyse quantitatively.
Allocation
Random sequence generation
Thirty‐six studies were judged to have a low risk of bias for providing an adequate description of how their randomisation methods were undertaken.
Nine studies were judged to have an unclear risk of bias due to a lack of information provided on their randomisation methods, although stated to be randomised.
Allocation concealment
Twenty‐four studies were judged to have a low risk of bias for providing an adequate description of how allocations were concealed.
Two studies were judged to be at high risk of bias due to being open‐label and appeared to have no approach to concealing allocation (Ebrahim 2022; Meng 2019).
Nineteen studies were judged to have an unclear risk of bias due to a lack of information provided on how allocations were concealed.
Blinding
Performance bias
Twenty‐six studies were judged to have a low risk of bias for clearly reporting how both the study participants were kept blind to treatments as well as the study personnel.
Ten studies were judged to be at high risk of bias due to being open‐label (Bliss 1992; Cosola 2021; Ebrahim 2022; Elamin 2017; Lopes 2018; Meng 2019; Miranda Alatriste 2014; Pan 2021; ProbiotiCKD 2019; Xie 2015a).
Nine studies were judged to have an unclear risk of bias due to a lack of information provided on blinding methods, although stated to be double‐blind.
Detection bias
Fifteen studies were judged to have a low risk of bias for clearly reporting how the outcomes were kept blind to treatments.
Nine studies were judged to be at high risk of bias due to being open‐label (Bliss 1992; Cosola 2021; Elamin 2017; Lopes 2018; Meng 2019; Miranda Alatriste 2014; Pan 2021; ProbiotiCKD 2019; Xie 2015a). Ebrahim 2022 was blinded to investigators and therefore judged unclear rather than high risk.
Twenty‐one studies were judged to have an unclear risk of bias due to a lack of information provided on blinding methods for outcome assessors, although stated to be double‐blind.
Incomplete outcome data
Eleven studies were judged to be at low risk of bias for adequately accounting for all participants throughout the study, providing reasons for withdrawals, having low attrition rates, and undertaking an ITT analysis.
Thirty‐one studies were judged to be at high risk of bias due to either not accounting for all participants throughout the study and providing reasons for withdrawals, high attrition rates (ranging from 40% to 50% and higher), or for not undertaking an ITT analysis.
Three studies were judged to have unclear risk of bias as no information about withdrawals, attrition, or ITT analysis could be identified in the available text (Elamin 2017; Esgalhado 2018; Kooshki 2019).
Selective reporting
Twenty‐six studies were judged to be at low risk of bias for providing a trial registration number or had an a priori published protocol.
Five studies were judged to be at high risk of bias due to serious changes to study outcomes and analyses that were not explained (Abbasi 2017; Cosola 2021; Dehghani 2016; Miranda Alatriste 2014; Viramontes‐Horner 2015).
Fourteen studies were judged to have an unclear risk of bias as no information was available about trial registration or an a priori published protocol.
Other potential sources of bias
Control for confounding factors
Seventeen studies were judged to be at low risk of bias for adequately describing control for standardising dietary intake and/or ingesting synbiotics, prebiotics, or probiotics where possible for the pre‐study run‐in and during study periods.
Twenty‐eight studies were judged to have an unclear risk of bias for not reporting any information about whether diet or medications were controlled for pre‐ or during study periods.
Other biases
Seventeen studies were judged to be at low risk of bias due to providing information on funding (non‐conflicting) and reporting disclosures (non‐conflicting).
Twenty‐two studies were judged to be at high risk of bias due to conflicting funding (industry or otherwise).
Six studies were judged to have unclear risk of bias as no information was available about funding or disclosures, or only information about one of these was provided.
Effects of interventions
See: Table 1; Table 2; Table 3; Table 4; Table 5; Table 6; Table 7; Table 8
Adverse events are reported in Appendix 5.
1: Synbiotic versus synbiotic
Haghighat 2019 compared the same probiotics (Lactobacillusacidophilus T16, Bifidobacteriumbifidum BIA‐6, Bifidobacteriumlactis BIA‐6, and Bifidobacteriumlongum LAF‐5) with two different prebiotics (fructo‐oligosaccharides plus galacto‐oligosaccharides plus inulin compared to maltodextrin).
Patient‐reported outcomes
Health‐related quality of life
Haghighat 2019 reported no difference in health‐related QoL (HRQoL‐14) at 12 weeks in patients receiving synbiotics compared to another synbiotic of a different dose (Analysis 1.1 (1 study, 46 participants): MD 1.98, 95% CI ‐11.2 to 15.08; very low certainty evidence).
1.1. Analysis.
Comparison 1: Synbiotic versus synbiotic, Outcome 1: Patient‐reported outcomes: HRQoL at 12 weeks
Adverse events
Adverse events were minimal and non‐serious, and withdrawals were not related to the study interventions (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
There were no subgroups to analyse for this comparison.
2: Synbiotic versus prebiotic
Six studies contributed to this comparison.
-
Synbiotic: Lactobacillusplantarum, Lactobacilluscasei subsp. rhamnosus, Lactobacillus gasseri, Bifidobacteriuminfantis,Bifidobactetriumlongum, Lactobacillusacidophilus, Lactobacillussalivarius,Lactobacillussporogenes and Streptococcusthermophilus plus prebiotics inulin and tapioca‐resistant starch
Prebiotic: tapioca‐resistant starch
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Synbiotic: Lactobacillusplantarum,Lactobacilluscasei subsp. rhamnosus,Lactobacillusgasseri, Bifidobacteriuminfantis,Bifidobacteriumlongum, Lactobacillusacidophilus, Lactobacillussalivarius, Lactobacillussporogenes, Streptococcusthermophilus plus inulin and tapioca‐resistant starch
Prebiotic: cellulose
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Synbiotic 1: Lactobacillusacidophilus T16, Bifidobacteriumbifidum BIA‐6, Bifidobacteriumlactis BIA‐6, and Bifidobacteriumlongum LAF‐5 plus fructo‐oligosaccharides, galacto‐oligosaccharides and inulin
Synbiotic 2: Lactobacillusacidophilus T16, Bifidobacteriumbifidum BIA‐6, Bifidobacteriumlactis BIA‐6, and Bifidobacteriumlongum LAF‐5 plus maltodextrin
Prebiotic: maltodextrin
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Synbiotic: Bifidobacterium longum BL‐G301 plus extruded sorghum flakes
Prebiotic: extruded corn flakes
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Synbiotic: Lactobacillus casei, Lactobacillus acidophilus, Lactobacillus rhamnosus, Lactobacillus bulgaricus, Bifidobacterium breve, Bifidobacterium longum, and Streptococcus thermophiles plus fructo‐oligosaccharide lactose
Prebiotic: maltodextrin
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Synbiotic: Lactobacillus, Bifidobacteria, and Streptococcus plus high‐resistant starch fibre supplement
Prebiotic: maltodextrin.
Kidney function
Estimated glomerular filtration rate
Guida 2017 reported no difference in eGFR at four weeks in patients receiving synbiotics compared to prebiotics (Analysis 2.1(1 study, 34 participants): MD ‐3.80 mL/min/1.73 m², 95% CI ‐17.98 to 10.38; very low certainty evidence).
2.1. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 1: Kidney function: eGFR at 4 weeks
SYNERGY II 2021 reported that patients receiving synbiotic supplementation resulted in a mean reduction in eGFR of ‐3.14 mL/min/1.73 m2 (95% CI ‐6.23 to ‐0.06) at 12 months from baseline (prebiotics had a mean increase of 2.61 mL/min/1.73 m2; 95% CI ‐0.41 to 5.63) (n = 56; P < 0.01).
Serum creatinine
Mirzaeian 2020 reported no difference in SCr at eight weeks in patients receiving synbiotics compared to prebiotics (Analysis 2.2 (1 study, 42 participants): MD ‐0.20 mg/dL, 95% CI ‐1.50 to 1.10; very low certainty evidence).
2.2. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 2: Kidney function: serum creatinine at 8 weeks
SYNERGY II 2021 reported synbiotic supplementation resulted in a mean increase in SCr concentration of 20.8 μmol (95% CI 2.97 to 38.5) at 12 months from baseline (prebiotics had a mean decrease of ‐9.79 μmol; 95% CI 21.7 to 2.09) (n = 56; P < 0.01).
Uraemic toxins
Urea
Mirzaeian 2020 reported no difference in urea at four weeks in patients receiving synbiotics compared to prebiotics (Analysis 2.3 (1 study, 42 participants): MD ‐2.10 mg/dL, 95% CI ‐13.93 to 9.73; very low certainty evidence).
2.3. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 3: Uraemic toxins: urea at 4 weeks
Indoxyl sulfate
Mirzaeian 2020 reported no difference in indoxyl sulfate at four weeks in patients receiving synbiotics compared to prebiotics (Analysis 2.4 (1 study, 42 participants): MD 128.30 ng/mL, 95% CI ‐242.77 to 499.37; very low certainty evidence).
2.4. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 4: Uraemic toxins: indoxyl sulfate at 4 weeks
SYNERGY II 2021 reported no difference in total indoxyl sulfate at 12 months in patients receiving synbiotic supplementation (mean change 1.5 μmol/L; 95% CI ‐3.25 to 6.26) compared to prebiotics (mean change ‐3.07 μmol/L; 95% CI ‐9.14 to 2.99) mean change from baseline (n = 56; P = 0.96).
SYNERGY II 2021 reported no difference in free indoxyl sulfate at 12 months in patients receiving synbiotic supplementation (mean change 0.1 μmol/L; 95% CI ‐0.14 to 0.34) compared to prebiotics (mean change ‐0.09 μmol/L; 95% CI ‐0.34 to 0.17) mean change from baseline (n = 56; p = 0.25).
P‐cresyl sulfate
Guida 2014 reported p‐cresyl sulfate was lower at four weeks in patients receiving synbiotics compared to prebiotics (Analysis 2.5 (1 study, 34 participants): MD ‐2.10 μg/mL, 95% CI ‐3.92 to ‐0.28; very low certainty evidence).
2.5. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 5: Uraemic toxins: p‐cresol sulfate at 4 weeks
SYNERGY II 2021 reported no difference in total p‐cresyl sulfate at 12 months in patients receiving synbiotic supplementation (mean change 28.8 μmol/L; 95% CI ‐6.32 to 64.0) compared to prebiotics (mean change ‐17.2 μmol/L; 95% CI ‐49.8 to 15.3) mean change from baseline (n = 56; P = 0.15).
SYNERGY II 2021 reported no difference in free p‐cresyl sulfate at 12 months in patients receiving synbiotic supplementation (mean change 0.98 μmol/L; 95% CI 0.17 to 1.79) compared to prebiotics (mean change ‐0.17 μmol/L; 95% CI ‐1.18 to 0.84) mean change from baseline (n = 56; P = 0.08).
Gastrointestinal function
Change in any gastrointestinal upset or intolerance
Guida 2017 reported prebiotics decreased borborygmi at four weeks compared to synbiotics (Analysis 2.6 (1 study, 34 participants): RR 15.26, 95% CI 0.99 to 236.23; very low certainty evidence).
2.6. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 6: GI function: change in any GI upset or intolerance (prevalence of borborygmi) at 4 weeks
SYNERGY II 2021 reported no difference in change in GI symptoms according to the Gastrointestinal Symptom Rating Scale (GSRS) Total Index (scale of 1 to 7, a higher score indicates worse discomfort) at 12 months in patients receiving synbiotics compared to prebiotics (Analysis 2.7 (1 study, 56 participants): MD 0.00, 95% CI ‐0.27 to 0.27; very low certainty evidence). SYNERGY II 2021 also reported no difference in the subdomains of the GSRS in patients receiving synbiotics compared to prebiotics, respectively (mean score ± SD): reflux (1.4 ± 0.8, 1.3 ± 0.4); abdominal pain (1.2 ± 0.4, 1.3 ± 0.4); indigestion (1.7 ± 0.9, 1.6 ± 0.5); constipation (1.4 ± 1.0, 1.5 ± 0.8); diarrhoea (1.3 ± 0.5, 1.2 ± 0.4).
2.7. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 7: GI function: change in any GI upset or intolerance (GSRS Total Index at 12 months)
Microbiota composition
SYNERGY II 2021 reported no difference in change in microbiota composition (Richness and Shannon's index) at 12 months in patients receiving synbiotics compared to prebiotics (n = 56). SYNERGY II 2021 reported, "The coverage of the microbiota diversity for all samples was high with a rarefied sequencing depth of 4 million reads with 298 species identified".
Faecal characteristics
Lopes 2018 reported faecal pH at seven weeks was lower in patients receiving synbiotics compared to prebiotics (Analysis 2.8 (1 study, 58 participants): MD ‐0.63, 95% CI ‐1.13 to ‐0.13; very low certainty evidence).
2.8. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 8: GI function: faecal pH at 7 weeks
Guida 2017 reported no difference in stool shape and characteristics on the Bristol Stool Chart (scale of 1 to 7) at four weeks in patients receiving synbiotics compared to prebiotics (Analysis 2.9 (1 study, 34 participants): MD ‐0.50, 95% CI ‐1.15 to 0.15; very low certainty evidence).
2.9. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 9: GI function: faecal characteristics (Bristol Stool Chart) at 4 weeks
SYNERGY II 2021 reported no difference in stool consistency on the Bristol Stool Chart at 12 months in patients receiving synbiotics compared to prebiotics (Analysis 2.10 (1 study, 56 participants): MD 0.50, 95% CI ‐0.18 to 1.18; very low certainty evidence).
2.10. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 10: GI function: faecal characteristics (Bristol Stool Chart) at 12 months
SYNERGY II 2021 reported no difference in stool frequency (patient‐reported number of times their bowels opened in the previous 24‐hour period) at 12 months in patients receiving synbiotics compared to prebiotics, respectively (1.8 ± 1.0, 1.6 ± 0.9; n = 56).
Patient‐reported outcomes
Health‐related quality of life
Haghighat 2019 reported no difference in HRQoL (HRQoL‐14) scores at 12 weeks in patients receiving synbiotics compared to prebiotics (Analysis 2.11 (2 studies, 65 participants): MD 6.38, 95% CI ‐4.88 to 17.64; very low certainty evidence).
2.11. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 11: Patient‐reported outcomes: HRQoL at 24 weeks
SYNERGY II 2021 reported no difference in HRQoL (Assessment of Quality of Life‐4 Dimension, 5‐point scale (AQoL‐4D)) at 12 months in patients receiving synbiotics compared to prebiotics, respectively (median (IQR): 16.0 (13.0 to 18.0), 15.0 (13.0 to 17.0); n = 56).
Adverse events
It is uncertain whether synbiotics decreased adverse events compared to prebiotics (Analysis 2.12 (5 studies, 279 participants): very low certainty evidence). It is uncertain whether synbiotics decreased withdrawals due to adverse events compared to prebiotics (Analysis 2.13 (4 studies, 211 participants): very low certainty evidence).
2.12. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 12: Adverse events: any adverse event
2.13. Analysis.
Comparison 2: Synbiotic versus prebiotic, Outcome 13: Withdrawals due to adverse events
Mirzaeian 2020 reported one death in each arm; however, they were not related to the study interventions.
The remaining adverse events were minimal and non‐serious, and withdrawals were not related to study treatment (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
Subgroups were not estimable for the remaining analyses in this comparison. In Analysis 2.12 and Analysis 2.13, totals were turned off due to zero event rate data and are also not estimable.
3: Prebiotic versus prebiotic
Five studies contributed to this comparison.
Biruete 2017 compared inulin to maltodextrin
Bliss 1992 compared gum Arabic to pectin
Li 2020 compared 50:50 inulin plus oligofructose to maltodextrin
Ramos 2019 compared fructo‐oligosaccharide to maltodextrin
Sirich 2014 compared high‐amylose corn starch to high‐amylopectin starch.
Kidney function
Estimated glomerular filtration rate
Ramos 2019 reported no difference in eGFR at 12 weeks in patients receiving fructo‐oligosaccharide compared to maltodextrin of a different dose (Analysis 3.1 (1 study, 50 participants): MD 0.00 mL/min, 95% CI ‐1.73 to 1.73; very low certainty evidence).
3.1. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 1: Kidney function: eGFR at 12 weeks
Uraemic toxins
Indoxyl sulfate
It is uncertain whether prebiotic 1 (inulin or high‐amylose corn starch) improves indoxyl sulfate at six weeks compared to prebiotic 2 (maltodextrin or high‐amylopectin starch) (Analysis 3.2 (2 studies, 64 participants): MD ‐0.20 μg/mL, 95% CI ‐1.01 to 0.61; I² = 0%; very low certainty evidence).
3.2. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 2: Uraemic toxins: indoxyl sulfate at 6 weeks
Uraemic toxins
P‐cresyl sulfate
It is uncertain whether prebiotic 1 (inulin or high‐amylose corn starch) improves indoxyl sulfate at six weeks compared to prebiotic 2 (maltodextrin or high‐amylopectin starch) (Analysis 3.3 (2 studies, 64 participants): SMD ‐0.04 μg/mL, 95% CI ‐0.53 to 0.45; I² = 0%; very low certainty evidence).
3.3. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 3: Uraemic toxins: p‐cresol sulfate at 6 weeks
Gastrointestinal function
Change in any gastrointestinal upset or intolerance
In very low certainty evidence, Biruete 2017 reported no difference in patients receiving inulin compared to maltodextrin at four weeks for burping (Analysis 3.4 (1 study, 24 participants): MD 0.17, 95% CI ‐0.50 to 0.84), cramping (Analysis 3.5 (1 study, 24 participants): MD ‐0.17, 95% CI ‐0.50 to 0.16), distension (Analysis 3.6 (1 study, 24 participants): MD 0.33, 95% CI ‐0.04 to 0.70), flatulence (Analysis 3.7 (1 study, 24 participants): MD 1.00, 95% CI 0.25 to 1.75), nausea (Analysis 3.8 (1 study, 24 participants): MD 0.00, 95% CI ‐0.00 to 0.00), reflux (Analysis 3.9 (1 study, 24 participants): MD 0.00, 95% CI ‐0.50 to 0.50), and rumbling (Analysis 3.10 (1 study, 24 participants): MD 0.50, 95% CI ‐0.14 to 1.14).
3.4. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 4: GI function: change in any GI upset or intolerance (burping) at 4 weeks
3.5. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 5: GI function: change in any GI upset or intolerance (cramping) at 4 weeks
3.6. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 6: GI function: change in any GI upset or intolerance (distension) at 4 weeks
3.7. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 7: GI function: change in any GI upset or intolerance (flatulence) at 4 weeks
3.8. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 8: GI function: change in any GI upset or intolerance (nausea) at 4 weeks
3.9. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 9: GI function: change in any GI upset or intolerance (reflux) at 4 weeks
3.10. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 10: GI function: change in any GI upset or intolerance (rumblings) at 4 weeks
Microbiota composition
In very low certainty evidence, Biruete 2017 reported no difference in patients receiving inulin compared to maltodextrin at four weeks for actinobacteria Analysis 3.11 (1 study, 24 participants): MD ‐1.26, 95% CI ‐4.46 to 1.94), bacteriodetes (Analysis 3.12 (1 study, 24 participants): MD 3.23, 95% CI ‐8.24 to 14.70), proteobacteria (Analysis 3.13 (1 study, 24 participants): MD 0.11, 95% CI ‐1.61 to 1.83), firmicutes (Analysis 3.14 (1 study, 24 participants): MD ‐2.44, 95% CI ‐14.19 to 9.31), synergistetes (Analysis 3.15 (1 study, 24 participants): MD ‐0.25, 95% CI ‐0.89 to 0.39), verrucomicrobia (Analysis 3.16 (1 study, 24 participants): MD 0.96, 95% CI ‐1.36 to 3.28), faceal acetate (Analysis 3.17 (1 study, 24 participants): MD ‐69.91, 95% CI ‐203.95 to 64.13), faecal propionate (Analysis 3.18 (1 study, 24 participants): MD ‐19.35, 95% CI ‐63.87 to 25.17), faecal butyrate (Analysis 3.19 (1 study, 24 participants): MD ‐11.04, 95% CI ‐39.57 to 17.49), faecal total short‐chain fatty acids (Analysis 3.20 (1 study, 24 participants): MD ‐104.71, 95% CI ‐293.34 to 83.92), faecal indoles (Analysis 3.21 (1 study, 24 participants): MD 2.71, 95% CI ‐69.78 to 75.20), and faecal p‐cresol (Analysis 3.22 (1 study, 24 participants): MD 28.84, 95% CI ‐105.07 to 162.75).
3.11. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 11: GI function: microbiota composition (Actinobacteria) at 4 weeks
3.12. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 12: GI function: microbiota composition (Bacteriodetes) at 4 weeks
3.13. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 13: GI function: microbiota composition (Proteobacteria) at 4 weeks
3.14. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 14: GI function: microbiota composition (Firmicutes) at 4 weeks
3.15. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 15: GI function: microbiota composition (Synergistetes) at 4 weeks
3.16. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 16: GI function: microbiota composition (Verrucomicrobia) at 4 weeks
3.17. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 17: GI function: microbiota composition (faecal acetate) at 4 weeks
3.18. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 18: GI function: microbiota composition (faecal propionate) at 4 weeks
3.19. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 19: GI function: microbiota composition (faecal butyrate) at 4 weeks
3.20. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 20: GI function: microbiota composition (faecal total short‐chain fatty acids) at 4 weeks
3.21. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 21: GI function: microbiota composition (faecal indoles) at 4 weeks
3.22. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 22: GI function: microbiota composition (faecal p‐cresol) at 4 weeks
Faecal characteristics
In very low certainty evidence, Biruete 2017 reported no difference in patients receiving inulin compared to maltodextrin at four weeks for bowel movements (Analysis 3.23 (1 study, 24 participants): MD ‐0.27, 95% CI ‐1.23 to 0.69), ease of passage (Analysis 3.24 (1 study, 24 participants): MD 0.00, 95% CI ‐0.90 to 0.90; very low certainty evidence), and consistency (Analysis 3.25 (1 study, 24 participants): MD ‐0.19, 95% CI‐1.34 to 0.96).
3.23. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 23: GI function: faecal characteristics (bowel movements) at 4 weeks
3.24. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 24: GI function: faecal characteristics (ease of passage) at 4 weeks
3.25. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 25: GI function: faecal characteristics (consistency) at 4 weeks
Adverse events and withdrawals
It is uncertain whether prebiotic 1 (gum Arabic or inulin plus oligofructose) decreased adverse events compared to prebiotic 2 (pectin or maltodextrin) (Analysis 3.26 (2 studies, 79 participants): RR 2.92, 95% CI 0.10 to 88.03; I² = 77%; very low certainty evidence).
3.26. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 26: Adverse events: number participants reporting an event
It is uncertain whether inulin plus oligofructose decreased withdrawals due to adverse events compared to maltodextrin (Analysis 3.27 (1 study, 39 participants): RR 0.70, 95% CI 0.13 to 3.75; very low certainty evidence).
3.27. Analysis.
Comparison 3: Prebiotic versus prebiotic, Outcome 27: Withdrawals due to adverse events
Adverse events were minimal and non‐serious, and withdrawals were not related to the study interventions (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
There were no subgroups to analyse for this comparison.
4: Prebiotic versus probiotic
Two studies contributed to this comparison.
Natarajan 2014 compared a 1:1 blend of cream of wheat and psyllium husk to Streptococcus thermophilus KB19, Lactobacillus acidophilus KB 27, and Bifidobacteriumlongum KB 31.
Wang 2015a compared maltodextrin to Bifidobacteriumbifidum A218, Bifidobacteriumcatenulatum A302, Bifidobacteriumlongum A101, Lactobacillusplantarum A87.
Dialysis outcomes
Peritonitis
Wang 2015a reported no difference in the occurrence of peritonitis at eight weeks in patients receiving prebiotics compared to probiotics (Analysis 4.1 (1 study, 47 participants): very low certainty evidence).
4.1. Analysis.
Comparison 4: Prebiotic versus probiotic, Outcome 1: Dialysis outcomes: peritonitis at 24 weeks
Adverse events
Natarajan 2014 reported one death not related to the study intervention: myocardial infarction at home from underlying cardiovascular conditions. Cross‐over numbers and denominators are unclear. Wang 2015a reported one patient in the placebo group died due to a head injury.
The remaining adverse events were minimal and non‐serious, and withdrawals were not related to the study interventions (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
There were no subgroups to analyse for this comparison.
5: Low versus high dose probiotic
Miranda Alatriste 2014 compared a low dose of Lactobacillus casei Shirota (8 x 109 CFU) to a higher dose of Lactobacillus casei Shirota (16 x 109 CFU).
Kidney function
Estimated glomerular filtration rate
Miranda Alatriste 2014 reported no difference in eGFR at eight weeks in patients receiving a low dose of Lactobacillus casei Shirota compared to a higher dose (Analysis 5.1 (1 study, 30 participants): MD ‐0.64 mL/min, 95% CI ‐9.51 to 8.23; very low certainty evidence).
5.1. Analysis.
Comparison 5: Low versus high dose probiotic, Outcome 1: Kidney function: GFR at 8 weeks
Serum creatinine
Miranda Alatriste 2014 reported no difference in SCr at eight weeks in patients receiving a low dose of Lactobacillus casei Shirota compared to a higher dose (Analysis 5.2 (1 study, 30 participants): MD ‐0.13 mg/dL, 95% CI ‐0.89 to 0.63; very low certainty evidence).
5.2. Analysis.
Comparison 5: Low versus high dose probiotic, Outcome 2: Kidney function: serum creatinine at 8 weeks
Urea
Miranda Alatriste 2014 reported no difference in urea rate at eight weeks in patients receiving a low dose of Lactobacillus casei Shirota compared to a higher dose (Analysis 5.3 (1 study, 30 participants): MD 4.57 mg/dL, 95% CI ‐9.52 to 18.66; very low certainty evidence).
5.3. Analysis.
Comparison 5: Low versus high dose probiotic, Outcome 3: Uraemic toxins: urea at 8 weeks
Adverse events
Adverse events were minimal and non‐serious, and withdrawals were not related to the study treatment (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
There were no subgroups to analyse for this comparison.
6: Synbiotic versus placebo or no treatment
Three studies contributed to this comparison.
Cosola 2021 compared a synbiotic (Lactobacillus casei LC4P1, Bifidobacteriumanimalis BLC1 plus fructo‐oligosaccharides, inulin and natural antioxidants) to a placebo.
Dehghani 2016 compared a synbiotic (Lactobacilluscasei, Lactobacillusacidophilus, Lactobacillusbulgaricus, Lactobacillusrhamnosus, Bifidobacteriumbreve, Bifidobacterium longum, Streptococcusthermophilus plus fructo‐oligosaccharides) to a placebo.
Viramontes‐Horner 2015 compared a synbiotic (Lactobacillus acidophilus, Bifidobacteriumlactis Bi‐07 plus inulin, omega‐3 fatty acids and vitamins) to a placebo.
Kidney function
Estimated glomerular filtration rate
It is uncertain whether synbiotics improve eGFR at six or 12 weeks compared to placebo (Analysis 6.1 (2 studies, 98 participants): MD 1.42 mL/min, 95% CI 0.65 to 2.2; very low certainty evidence).
6.1. Analysis.
Comparison 6: Synbiotic versus placebo, Outcome 1: Kidney function: eGFR at 6 or 12 weeks
Serum creatinine
It is uncertain whether synbiotics improve SCr at six or 12 weeks compared to placebo (Analysis 6.2 (2 studies, 98 participants): MD ‐0.57 mg/dL, 95% CI ‐1.08 to 0.07; very low certainty evidence).
6.2. Analysis.
Comparison 6: Synbiotic versus placebo, Outcome 2: Kidney function: SrCr at 6 or 12 weeks
Uraemic toxins
Urea
It is uncertain whether synbiotics improve urea at six or 12 weeks compared to placebo, with no differences found between subgroups (Analysis 6.3 (2 studies, 117 participants): MD 3.34 mg/dL, 95% CI ‐15.65 to 22.32; very low certainty evidence; test for subgroup differences P = 0.15).
6.3. Analysis.
Comparison 6: Synbiotic versus placebo, Outcome 3: Uraemic toxins: urea at 6 or 12 weeks
Gastrointestinal function
Change in any gastrointestinal upset or intolerance
In very low certainty evidence, Cosola 2021 reported no difference at 12 weeks in patients receiving synbiotics compared to placebo on the GSRS scale for rumbling (Analysis 6.4 (1 study, 23 participants): MD ‐0.54, 95% CI ‐0.77 to ‐0.31), hard stools (Analysis 6.5 (1 study, 23 participants): MD ‐0.09, 95% CI ‐0.35 to 0.17), abdominal pain (Analysis 6.6 (1 study, 23 participants): MD 0.22, 95% CI ‐0.02 to 0.46) or constipation syndrome (Analysis 6.7 (1 study, 23 participants): MD ‐0.17, 95% CI ‐0.72 to 0.38).
6.4. Analysis.
Comparison 6: Synbiotic versus placebo, Outcome 4: GI function: GSRS Item 6 (rumbling) at 12 weeks
6.5. Analysis.
Comparison 6: Synbiotic versus placebo, Outcome 5: GI function: GSRS Item 13 (hard stools) at 12 weeks
6.6. Analysis.
Comparison 6: Synbiotic versus placebo, Outcome 6: GI function: abdominal pain at 12 weeks
6.7. Analysis.
Comparison 6: Synbiotic versus placebo, Outcome 7: GI function: constipation syndrome at 12 weeks
Adverse events
Adverse events were minimal and non‐serious, and withdrawals were not related to the study interventions (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
There were no subgroups to analyse for the remaining analyses other than Analysis 6.3.
7: Prebiotic versus placebo or no treatment
Three studies contributed to this comparison.
Meng 2019 compared a high‐resistant starch, low‐protein flour to no treatment.
Esgalhado 2018 compared a resistant starch to a placebo.
Khosroshahi 2018 compared high‐amylose maize‐resistant starch to a placebo.
Kidney function
Serum creatinine
It is uncertain whether prebiotics improves SCr at eight or 12 weeks compared to placebo or no treatment (Analysis 7.1 (3 studies, 145 participants): MD 0.52 mg/dL, 95% CI ‐2.39 to 3.44; very low certainty evidence).
7.1. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 1: Kidney function: serum creatinine at 8 or 12 weeks
A difference was identified across subgroups by CKD stage. Participants receiving placebo or no treatment showed increased SCr in patients with CKD stage A2 with diabetic nephropathy (70 participants) compared to CKD stage G5D (75 participants); however, heterogeneity was very high I² = 79% (P = 0.03).
Uraemic toxins
Urea
Meng 2019 reported no difference no difference to urea at 12 weeks in patients receiving prebiotics compared to no treatment (Analysis 7.2 (1 study, 70 participants): MD ‐0.40 mmol/L, 95% CI ‐0.86 to 0.06; very low certainty evidence).
7.2. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 2: Uraemic toxins: urea at 12 weeks
Indoxyl sulfate
It is uncertain whether prebiotics improve indoxyl sulfate at eight weeks compared to placebo or no treatment (Analysis 7.3 (2 studies, 75 participants): SMD ‐0.14 mg/L, 95% CI ‐0.60 to 0.31; very low certainty evidence).
7.3. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 3: Uraemic toxins: indoxyl sulfate at 8 weeks
P‐cresyl sulfate
Khosroshahi 2018 reported no difference in p‐cresyl sulfate at eight weeks in patients receiving prebiotics compared to placebo (Analysis 7.4 (1 study, 44 participants): MD ‐1.68 mg/L, 95% CI ‐14.30 to 10.94; very low certainty evidence).
7.4. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 4: Uraemic toxins: p‐cresyl sulfate at 8 weeks
Gastrointestinal function
Microbiota composition
In very low certainty evidence, Khosroshahi 2018 reported no difference at eight weeks in prebiotics compared to placebo to the microbiota compositions of Facealibacterium (Analysis 7.5 (1 study, 44 participants): MD 2.37, 95% CI 0.23 to 4.51), Parabacteroides (Analysis 7.6 (1 study 44 participants): MD 0.22, 95% CI 0.06 to 0.38), Bifidobacteria (Analysis 7.7 (1 study 44 participants): MD ‐3.92, 95% CI ‐9.83 to 1.99), Ruminococcus (Analysis 7.8 (1 study 44 participants): MD 3.86, 95% CI ‐0.32 to 8.04), and Prevotella (Analysis 7.9 (1 study 44 participants): MD ‐0.43, 95% CI ‐1.45 to 0.59).
7.5. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 5: GI function: microbiota composition (Facealibacterium) at 8 weeks
7.6. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 6: GI function: microbiota composition (Parabacteroides) at 8 weeks
7.7. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 7: GI function: microbiota composition (Bifidobacteria) at 8 weeks
7.8. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 8: GI function: microbiota composition (Ruminococcus) at 8 weeks
7.9. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 9: GI function: microbiota composition (Prevotella) at 8 weeks
Adverse events
Khosroshahi 2018 reported no difference in any adverse events (number of participants reporting an event) in patients receiving prebiotics compared to placebo (Analysis 7.10 (1 study, 50 participants): RR 2.50, 95% CI 0.53 to 11.70; very low certainty evidence).
7.10. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 10: Adverse events: any adverse event (number of participants)
Khosroshahi 2018 reported no difference in withdrawals due to adverse events in patients receiving prebiotics compared to placebo (Analysis 7.11 (1 study, 50 participants): RR 3.0, 95% CI 0.13 to 70.30; very low certainty evidence).
7.11. Analysis.
Comparison 7: Prebiotic versus placebo or no treatment, Outcome 11: Withdrawals due to adverse events
Adverse events were minimal and non‐serious, and withdrawals were not related to the study interventions (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
There were no subgroups to analyse for the remaining analyses.
8: Probiotic versus placebo or no treatment
Nine studies contributed to this comparison.
Abbasi 2017 compared soy milk plus Lactobacillusplantarum A7 to soy milk.
Borges 2018 compared Streptococcusthermophilus, Lactobacillusacidophilus, and Bifidobacterialongum strains to a placebo.
Eidi 2018 compared LactobacillusRhamnosus to infant formula.
Lim 2021 compared Lactococcuslactis subspecies (Lactis LL358, Lactobacillussalivarius LS159, and Lactobaccilluspentosus LPE588) to a placebo.
Liu 2020 compared Bifidobacteriumlongum NQ1501, Lactobacillusacidophilus YIT2004 and Enterococcifaecalis YIT0072 to a placebo.
Mafi 2018 compared Lactobacillusacidophilus, Bifidobacteriumbifidum ZT‐B1, Lactobacillusreuteri ZT‐Lre and Lactobacillusfermentum ZT‐L3 to a placebo
Mazruei Arani 2019 compared honey containing a viable and heat‐resistant probiotic Bacillus coagulans T4 (IBRC‐N10791) to control honey.
ProbiotiCKD 2019 compared different probiotics over different weeks (week 1, weeks 2 to 3, weeks 4 to 15) to placebo.
Soleimani 2017 compared Lactobacillus acidophilus, Lactobacillus casei, and Bifidobacteria bifidum to a placebo.
Kidney function
Estimated glomerular filtration rate
It is uncertain whether probiotics improve eGFR at eight, 12, or 15 weeks compared to placebo or no treatment (Analysis 8.1 (3 studies, 128 participants): MD 2.73 mL/min, 95% CI ‐2.28 to 7.75; I² = 78%; very low certainty evidence). A difference was identified across subgroups by CKD stage. Participants receiving placebo or no treatment showed decreased eGFR in patients with CKD stage 1 with type 2 diabetes mellitus (40 participants) compared to CKD stage 3A with diabetes and hypertension (28 participants) and CKD stage G5D with diabetes and hypertension (60 participants); however, heterogeneity was very high I² = 77.6% (P = 0.01).
8.1. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 1: Kidney function: GFR at 8, 12 or 15 weeks
Serum creatinine
Probiotics may have little or no effect on SCr at eight, 12, or 24 weeks compared to placebo or no treatment, with no difference found between subgroups (Analysis 8.2 (6 studies, 303 participants): MD ‐0.51 mg/dL, 95% CI ‐1.06 to 0.04; I² = 96%; low certainty evidence; test for subgroup differences P = 0.55).
8.2. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 2: Kidney function: serum creatinine at 8, 12 or 24 weeks
Albuminuria
Probiotics may have little or no effect on albuminuria at eight, 12, or 24 weeks compared to placebo or no treatment, with no difference found between subgroups (Analysis 8.3 (4 studies, 193 participants): MD 0.02 g/dL, 95% CI ‐0.08 to 0.13; I² = 0%; low certainty evidence; test for subgroup differences P = 0.80).
8.3. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 3: Kidney function: albuminuria at 12 or 24 weeks
Proteinuria
Mafi 2018 reported no difference in proteinuria at 12 weeks in patients receiving probiotics compared to placebo or no treatment (Analysis 8.4 (1 study, 60 participants): MD ‐15.60 mg/dL, 95% CI ‐34.30 to 3.10; very low certainty evidence).
8.4. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 4: Kidney function: proteinuria at 12 weeks
Uraemic toxins
Urea
Probiotics may have little or no effect on urea at 12 or 24 weeks compared to placebo or no treatment, with no difference found between subgroups (Analysis 8.5 (5 studies, 263 participants): MD ‐1.11 mg/dL, 95% CI ‐2.58 to 0.35; I² = 0%; low certainty evidence; test for subgroup differences P = 0.73).
8.5. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 5: Uraemic toxins: urea at 12 or 24 weeks
Indoxyl sulfate
It is uncertain whether probiotics improved indoxyl sulfate at 12 or 24 weeks compared to placebo or no treatment, with no difference found between subgroups (Analysis 8.6 (2 studies, 83 participants): MD ‐4.42 mg/dL, 95% CI ‐9.83 to 1.35; I² = 0%; very low certainty evidence; test for subgroup differences P = 0.63).
8.6. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 6: Uraemic toxins: indoxyl sulfate at 12 or 24 weeks
P‐cresyl sulfate
It is uncertain whether probiotics improved p‐cresyl sulfate at four, 12 or 24 weeks compared to placebo or no treatment, with no difference found between subgroups (Analysis 8.7 (3 studies, 125 participants): MD ‐2.12 mg/dL, 95% CI ‐5.19 to 0.95; I² = 16%; very low certainty evidence; test for subgroup differences P = 0.21).
8.7. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 7: Uraemic toxins: p‐cresyl sulfate at 4, 12 or 24 weeks
Indole‐3‐acetic acid
Borges 2018 reported no difference in indole‐3‐acetic acid at 12 weeks in patients receiving probiotics compared to placebo or no treatment (Analysis 8.8 (1 study, 33 participants): MD ‐288.10 μg/L, 95% CI ‐464.41 to ‐111.79; very low certainty evidence).
8.8. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 8: Uraemic toxins: indole‐3‐acetic acid acid at 12 weeks
Gastrointestinal function
Change in any gastrointestinal upset or intolerance
Borges 2018 reported no difference at 12 weeks in patients receiving probiotics compared to placebo or no treatment for abdominal pain or diarrhoea (Analysis 8.9 (1 study, 33 participants): RR 2.13, 95% CI 0.21 to 21.22; very low certainty evidence), or constipation (Analysis 8.10 (1 study, 33 participants): RR 3.18, 95% CI 0.14 to 72.75; very low certainty evidence).
8.9. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 9: GI function: any GI upset or intolerance (abdominal pain/diarrhoea) at 12 weeks
8.10. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 10: GI function: any GI upset or intolerance (constipation) at 12 weeks
Faecal characteristics
Borges 2018 reported no difference in faecal pH at 12 weeks in patients receiving probiotics compared to placebo or no treatment (Analysis 8.11 (1 study, 20 participants): MD ‐2.10, 95% CI ‐7.28 to 3.08; very low certainty evidence).
8.11. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 11: GI function: faecal pH at 12 weeks
Adverse events
It is uncertain whether probiotics decrease adverse events compared to placebo or no treatment, with no difference found between subgroups (Analysis 8.12 (4 studies, 205 participants): RR 1.96, 95% CI 0.63 to 6.12; I² = 13%; very low certainty evidence; test for subgroup differences P = 0.17), and withdrawals due to adverse events, with no difference found between subgroups (Analysis 8.13 (4 studies, 205 participants): RR 4.96, 95% CI 1.13 to 21.77; I² = 0%; very low certainty evidence; test for subgroup differences P = 1.00).
8.12. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 12: Adverse events: any adverse event (number of participants)
8.13. Analysis.
Comparison 8: Probiotic versus placebo or no treatment, Outcome 13: Withdrawals due to adverse events
Lim 2021 reported one death in each arm but not related to the study treatment, "No significant gastrointestinal side effects were reported or recorded throughout the study in either group."
The remaining adverse events were minimal and non‐serious, and withdrawals were not related to study treatment (see Appendix 5).
The studies in this comparison did not report data on our remaining primary and secondary outcomes.
Discussion
Summary of main results
Forty‐five studies (2266 randomised participants) were included in this review. Study participants were predominantly adults (two studies included children) with CKD ranging from stages 1 to 5, with patients receiving and not receiving dialysis, of whom half also had diabetes and hypertension.
No studies investigated the same synbiotic, prebiotic or probiotic of similar strains, doses, or frequencies. The risk of bias in the included studies varied between low, unclear or high risk across each of the domains.
Synbiotics versus synbiotics: compared to synbiotics of a different dose, it is uncertain whether synbiotics improve HRQoL because the certainty of the evidence was very low.
Synbiotics versus prebiotics: compared to prebiotics, it is uncertain whether synbiotics improve eGFR, SCr, urea, indoxyl sulfate, p‐cresyl sulfate, change in any GI upset or intolerance, microbiota composition, faecal characteristics, or HRQoL because the certainty of the evidence was very low.
Prebiotics versus prebiotics: compared to prebiotics of a different dose, it is uncertain whether prebiotics improves eGFR, indoxyl sulfate, p‐cresyl sulfate, change in any GI upset or intolerance, microbiota composition, or faecal characteristics because the certainty of the evidence was very low.
Prebiotics versus probiotics: compared to probiotics, it is uncertain whether prebiotics prevent peritonitis because the certainty of the evidence was very low.
Probiotics versus probiotics: compared to probiotics of a different dose, it is uncertain whether probiotics improve eGFR, SCr, or urea because the certainty of the evidence was very low.
Synbiotics versus placebo or no treatment: compared to placebo or no treatment, it is uncertain whether synbiotics improve eGFR, SCr, urea, or change in any GI upset or intolerance because the certainty of the evidence was very low.
Prebiotics versus placebo or no treatment: compared to placebo or no treatment, it is uncertain whether prebiotics improve SCr, urea, indoxyl sulfate, p‐cresyl sulfate, or microbiota composition because the certainty of the evidence is very low. For SCr, a difference was identified across subgroups by CKD stage. Participants receiving placebo or no treatment showed an increase in SCr in patients with CKD stage A2 with diabetic nephropathy (70 participants) compared to CKD stage G5D (75 participants); however, heterogeneity was very high I² = 79% (P = 0.03).
Probiotics versus placebo or no treatment: compared to placebo or no treatment, it is uncertain whether probiotics improve eGFR, proteinuria, indoxyl sulfate, p‐cresyl sulfate, indole‐3‐acetic acid, change in any GI upset or intolerance, or faecal characteristics because the certainty of the evidence is very low. For eGFR, a difference was identified across subgroups by CKD stage. Participants receiving placebo or no treatment showed decreased eGFR in patients with CKD stage 1 with type 2 diabetes mellitus (40 participants) compared to CKD stage 3A with diabetes and hypertension (28 participants) and CKD stage G5D with diabetes and hypertension (60 participants); however, heterogeneity was very high I² = 77.6% (P = 0.01). Probiotics may have little or no effect on SCr, albuminuria, or urea compared to placebo or no treatment, as the certainty of the evidence is low.
For all comparisons, adverse events were poorly reported and were minimal (flatulence, nausea, diarrhoea, abdominal pain) and non‐serious, and withdrawals were not related to the study treatment.
Overall completeness and applicability of evidence
This review identified a substantial number of RCTs testing the efficacy of synbiotics, prebiotics or probiotics in people with CKD. However, the severe lack of congruence across the studies highlights the lack of high‐quality RCTs testing similar biotics, doses, strains, frequencies, and standardised outcomes.
This field contains emerging trials of diverse and assorted interventions. No studies investigated the same synbiotic, prebiotic or probiotic of similar strains or doses.
We have identified significant gaps in the evidence with the meta‐analyses undertaken containing limited data from small studies. It is critically important for this emerging field to conduct trials of alternative interventions in a standardised way to help better inform whether these agents favourably modify gut dysbiosis and its associated morbidity and QoL in people with CKD.
The four major issues around the completeness of the evidence were:
Limited sample size and insufficient power
Standardised dosing of synbiotics, prebiotics or probiotics
Standardised measuring
Reporting of outcomes.
The three major issues around the applicability of the evidence were:
Participant criteria: the spread of patients across CKD stages 1 to 5, dialysis and non‐dialysis, diabetes, and hypertension
Outcome measures varied greatly by definition of units, scale, and time points.
Lack of patient‐important and patient‐centred outcomes.
Quality of the evidence
Overall, the quality of the evidence was low to very low. Studies were judged to have a spread of low to unclear to high risks of bias across most domains (Figure 2). Of the available evidence, meta‐analyses undertaken were of limited data from small studies. Data were sparse and addressed few primary and secondary outcomes.
Across all comparisons, GRADE evaluations were judged to be low or very low certainty evidence. This evidence was downgraded primarily due to the risk of bias and sparse data from small study sizes. The evidence was also downgraded to very low for single‐study data or incomplete or no data reported for an outcome.
Very low certainty evidence implies that we are very uncertain about results (not estimable due to lack of data or poor quality). We have no evidence to support or refute the use of synbiotics, prebiotics, or probiotics in people with CKD, and findings should be viewed with caution.
Potential biases in the review process
This review was conducted as per the protocol following prespecified inclusion criteria and used comprehensive literature searches to find all relevant studies. We do not believe there are any other potential biases in this review process.
Agreements and disagreements with other studies or reviews
This review is the most up‐to‐date synthesis of the evidence that examines synbiotics, prebiotics, and probiotics in people with CKD.
A recent systematic review has identified similar RCTs to those of an earlier search date (McFarlane 2019). The included studies are similar, and the results of the meta‐analyses also found, from very low certainty evidence, that synbiotic, prebiotic or probiotic interventions made little or no difference to some uraemic toxins (urea, indoxyl sulfate, p‐cresyl sulfate). Similarly, the review concludes that further high‐quality, standardised trials are needed to develop answers within this emerging field.
In contrast, Zheng 2020 and colleagues identified improvement in lipids, oxidative stress and inflammatory biomarkers from treatment with biotic supplementation. The meta‐analysis appears to have combined synbiotics, prebiotics and probiotics involving entirely different treatment options, doses and strains. Further to this, the included studies have been rated as mostly low risk of bias across the domains. Our review disagrees with this quality assessment. GRADE rating was also not used for assessing the certainty of the evidence. Zheng 2020 and colleagues may prematurely promote the use of biotic interventions in this population.
A further two systematic reviews focus on patients receiving dialysis and conclude similar results. Chen 2022 and colleagues found from low‐quality evidence that supplementation with biotics may reduce some inflammatory biomarkers (C‐reactive protein, interleukin‐6), and uraemic toxins (indoxyl sulfate) and increase HDL in dialysis patients. March 2020 and colleagues have similarly reported that supplementation with biotics may reduce endotoxins, uraemic toxins (indoxyl‐sulphate, p‐cresyl sulfate), and reduced GI symptoms. However, the review correctly identifies that these were low‐quality, high‐risk of bias studies.
Authors' conclusions
Implications for practice.
We found very few studies that adequately test biotic supplementation as an alternative treatment to improve GI symptoms, kidney function, uraemic toxins, allograft function, dialysis outcomes, QoL, CVD, cancer, and adverse events for people with CKD.
There is currently no evidence to support or refute the use of synbiotics, prebiotics, or probiotics in people with CKD, and findings should be viewed with caution.
We are not certain whether synbiotics, prebiotics, or probiotics are more or less effective compared to one another, antibiotics, or standard care for improving patient outcomes in people with CKD. Adverse events were uncommon and mild. Twenty‐six studies are currently ongoing; therefore, it is possible findings may change with the inclusion of these studies in future updates.
Implications for research.
To effectively examine the efficacy of synbiotics, prebiotics, or probiotics in people with CKD, future research in this field requires adequately powered, longer‐term RCTs comparing synbiotics, prebiotics, and probiotics separately (and with a placebo) measuring standardised strains, dosing and frequency as well as a standard set of core kidney transplant and core CKD outcomes (SONG 2017).
History
Protocol first published: Issue 5, 2020
Acknowledgements
We wish to acknowledge the assistance of the Cochrane Kidney and Transplant Information Specialists, Gail Higgins, Ruth Mitchell and Anh Kieu. The authors are grateful to the following peer reviewers for their time and comments: Gabrielle Williams (Melanoma Institute Australia), Deirdre Hahn (Department of Nephrology, The Children’s Hospital Westmead, Australia).
The Methods section of this review is based on a standard template used by Cochrane Kidney and Transplant.
Appendices
Appendix 1. Chronic kidney disease (CKD) definitions
The US Kidney Disease: Improving Global Outcomes (KDIGO) organization developed clinical practice guidelines and classifications for CKD in 2002. In 2012, these guidelines and classifications were updated and adopted by the international Kidney Disease Improving Global Outcomes (KDIGO) CKD guideline development work group (KDIGO 2013).
Persistent albuminuria categories Description and range |
||||||
A1 | A2 | A3 | ||||
Normal to mildly increased | Moderately increased | Severely increased | ||||
ACRa < 30 mg/g | ACR 30 to 300 mg/g | ACR > 300 mg/g | ||||
eGFRb categories (mL/min/1.73 m2) Description and range |
G1 | Normal or highc | ≥ 90 | 1 if CKD | 1 | 2 |
G2 | Mildly decreasedc | 60 to 89 | 1 if CKD | 1 | 2 | |
G3a | Mildly to moderately decreased | 45 to 59 | 1 | 2 | 3 | |
G3b | Moderately to severely decreased | 30 to 44 | 2 | 3 | 3 | |
G4 | Severely decreased | 15 to 29 | 3 | 3 | 4+ | |
G5 | Kidney failure | < 15 | 4+ | 4+ | 4+ |
aACR ‐ albumin‐creatinine ratio
beGFR ‐ estimated glomerular filtration rate
cIn the absence of evidence of kidney damage, neither eGFR category G1 nor G2 fulfil the criteria for CKD (KDIGO 2013).
Classification is based on two markers: evidence of kidney damage (such as the presence of microalbuminuria, proteinuria or structural abnormality); and the sustained impairment of eGFR for at least 3 months. Normal eGFR in young adults is around 100 to 120 mL/min/1.73 m2.
Early CKD is described as stages 1 to 3 of the KDIGO 2012 classification. At these stages, a patient may have no outward symptoms or signs of illness and only testing such as dipstick urine measurement for proteinuria/haematuria, or blood test may detect the presence of a kidney abnormality.
Appendix 2. Electronic search strategies
Database | Search terms |
CENTRAL |
|
MEDLINE |
|
EMBASE |
|
Appendix 3. Risk of bias assessment tool
Potential source of bias | Assessment criteria |
Random sequence generation Selection bias (biased allocation to interventions) due to inadequate generation of a randomised sequence |
Low risk of bias: Random number table; computer random number generator; coin tossing; shuffling cards or envelopes; throwing dice; drawing of lots; minimisation (minimisation may be implemented without a random element, and this is considered to be equivalent to being random). |
High risk of bias: Sequence generated by odd or even date of birth; date (or day) of admission; sequence generated by hospital or clinic record number; allocation by judgement of the clinician; by preference of the participant; based on the results of a laboratory test or a series of tests; by availability of the intervention. | |
Unclear: Insufficient information about the sequence generation process to permit judgement. | |
Allocation concealment Selection bias (biased allocation to interventions) due to inadequate concealment of allocations prior to assignment |
Low risk of bias: Randomisation method described that would not allow investigator/participant to know or influence intervention group before eligible participant entered in the study (e.g. central allocation, including telephone, web‐based, and pharmacy‐controlled, randomisation; sequentially numbered drug containers of identical appearance; sequentially numbered, opaque, sealed envelopes). |
High risk of bias: Using an open random allocation schedule (e.g. a list of random numbers); assignment envelopes were used without appropriate safeguards (e.g. if envelopes were unsealed or non‐opaque or not sequentially numbered); alternation or rotation; date of birth; case record number; any other explicitly unconcealed procedure. | |
Unclear: Randomisation stated but no information on method used is available. | |
Blinding of participants and personnel Performance bias due to knowledge of the allocated interventions by participants and personnel during the study |
Low risk of bias: No blinding or incomplete blinding, but the review authors judge that the outcome is not likely to be influenced by lack of blinding; blinding of participants and key study personnel ensured, and unlikely that the blinding could have been broken. |
High risk of bias: No blinding or incomplete blinding, and the outcome is likely to be influenced by lack of blinding; blinding of key study participants and personnel attempted, but likely that the blinding could have been broken, and the outcome is likely to be influenced by lack of blinding. | |
Unclear: Insufficient information to permit judgement | |
Blinding of outcome assessment Detection bias due to knowledge of the allocated interventions by outcome assessors. |
Low risk of bias: No blinding of outcome assessment, but the review authors judge that the outcome measurement is not likely to be influenced by lack of blinding; blinding of outcome assessment ensured, and unlikely that the blinding could have been broken. |
High risk of bias: No blinding of outcome assessment, and the outcome measurement is likely to be influenced by lack of blinding; blinding of outcome assessment, but likely that the blinding could have been broken, and the outcome measurement is likely to be influenced by lack of blinding. | |
Unclear: Insufficient information to permit judgement | |
Incomplete outcome data Attrition bias due to amount, nature or handling of incomplete outcome data. |
Low risk of bias: No missing outcome data; reasons for missing outcome data unlikely to be related to true outcome (for survival data, censoring unlikely to be introducing bias); missing outcome data balanced in numbers across intervention groups, with similar reasons for missing data across groups; for dichotomous outcome data, the proportion of missing outcomes compared with observed event risk not enough to have a clinically relevant impact on the intervention effect estimate; for continuous outcome data, plausible effect size (difference in means or standardised difference in means) among missing outcomes not enough to have a clinically relevant impact on observed effect size; missing data have been imputed using appropriate methods. |
High risk of bias: Reason for missing outcome data likely to be related to true outcome, with either imbalance in numbers or reasons for missing data across intervention groups; for dichotomous outcome data, the proportion of missing outcomes compared with observed event risk enough to induce clinically relevant bias in intervention effect estimate; for continuous outcome data, plausible effect size (difference in means or standardized difference in means) among missing outcomes enough to induce clinically relevant bias in observed effect size; ‘as‐treated’ analysis done with substantial departure of the intervention received from that assigned at randomisation; potentially inappropriate application of simple imputation. | |
Unclear: Insufficient information to permit judgement | |
Selective reporting Reporting bias due to selective outcome reporting |
Low risk of bias: The study protocol is available and all of the study’s pre‐specified (primary and secondary) outcomes that are of interest in the review have been reported in the pre‐specified way; the study protocol is not available but it is clear that the published reports include all expected outcomes, including those that were pre‐specified (convincing text of this nature may be uncommon). |
High risk of bias: Not all of the study’s pre‐specified primary outcomes have been reported; one or more primary outcomes is reported using measurements, analysis methods or subsets of the data (e.g. sub‐scales) that were not pre‐specified; one or more reported primary outcomes were not pre‐specified (unless clear justification for their reporting is provided, such as an unexpected adverse effect); one or more outcomes of interest in the review are reported incompletely so that they cannot be entered in a meta‐analysis; the study report fails to include results for a key outcome that would be expected to have been reported for such a study. | |
Unclear: Insufficient information to permit judgement | |
Other bias Bias due to problems not covered elsewhere in the table |
Low risk of bias: The study appears to be free of other sources of bias. |
High risk of bias: Had a potential source of bias related to the specific study design used; stopped early due to some data‐dependent process (including a formal‐stopping rule); had extreme baseline imbalance; has been claimed to have been fraudulent; had some other problem. | |
Unclear: Insufficient information to assess whether an important risk of bias exists; insufficient rationale or evidence that an identified problem will introduce bias. |
Appendix 4. The GRADE approach (Grades of Recommendation, Assessment, Development, and Evaluation)
The GRADE approach assesses the certainty of a body of evidence, rating it in one of four grades (GRADE 2008).
High: we are very confident that the true effect lies close to that of the estimate of the effect
Moderate: we are moderately confident in the effect estimate; the true effect is likely to be close the estimate of effect, but there is a possibility that it is substantially different
Low: our confidence in the effect estimate is limited; the true effect may be substantially different from the estimate of the effect
Very low: we have very little confidence in the effect estimate; the true effect is likely to be substantially different from the estimate of effect.
We decreased the certainty of evidence if there was (Balshem 2011):
serious (‐1) or very serious (‐2) limitation in the study design or execution (risk of bias);
important inconsistency of results (‐1);
some (‐1) or major (‐2) uncertainty about the directness of evidence;
imprecise or sparse data (‐1) or serious imprecision (‐2); or
high probability of publication bias (‐1).
We increased the certainty of evidence if there was (GRADE 2011):
a large magnitude of effect (direct evidence, relative risk (RR) = 2 to 5 or RR = 0.5 to 0.2 with no plausible confounders) (+1); very large with RR > 5 or RR < 0.2 and no serious problems with risk of bias or precision; more likely to rate up if effect is rapid and out of keeping with prior trajectory; usually supported by indirect evidence (+2);
evidence of a dose response gradient (+1); or
all plausible residual confounders or biases would reduce a demonstrated effect, or suggest a spurious effect when results show no effect (+1).
Appendix 5. Adverse events
Adverse events
Note: all numerals are 'number of participants reporting an event' (not number of events reported) unless stated otherwise.
Study ID | Synbiotic | Prebiotic | Probiotic | Placebo | No treatment/the control starch etc. | Notes from study |
Abbasi 2017 | ‐ | ‐ | Any AE: 4/22 (flatulence: 4) Withdrawal due to AE: 0 |
‐ | Any AE: 5/22 (flatulence: 5) Withdrawal due to AE: 0 |
Also some minor complaints about the specific taste of soy milk at start. The numbers are not clear |
Biruete 2017 | ‐ | Any AE: not reported Withdrawal due to AE: not reported |
‐ | ‐ | ‐ | None reported |
Bliss 1992 | ‐ |
Gum Arabic Any AE: 8/20 (flatulence: 8) Withdrawal due to AE: unclear Pectin Any AE: 0/20 Withdrawal due to AE: unclear |
‐ | ‐ | ‐ | ‐ |
Borges 2018 | ‐ | ‐ | Any AE: 5/23 (abdominal pain/diarrhoea: 2; constipation: 1; precordial pain: 2) Withdrawal due to AE: 5 |
Any AE: 1/23 (abdominal pain: 1; death: 2 (not related to study)) Withdrawal due to AE: 1 |
‐ | ‐ |
Cosola 2021 | Any AE: 0/13 Withdrawal due to AE: 0/13 |
‐ | ‐ | Any AE: 0/13 Withdrawal due to AE: 0/13 |
‐ | ‐ |
de Andrade 2021 | ‐ | Any AE: 0/43 Withdrawal due to AE: 0/43 |
‐ | Any AE: 0/43 Withdrawal due to AE: 0/43 |
‐ | ‐ |
de Araujo 2022 | ‐ | ‐ | Any AE: 2/40 (abdominal pain/diarrhoea: 2) Withdrawal due to AE: 2 |
Any AE: 0/40 Withdrawal due to AE: 0/40 |
‐ | ‐ |
Dehghani 2016 | Any AE: 4/denominator not clear Withdrawal due to AE: 4 |
‐ | ‐ | Any AE: 3/denominator not clear Withdrawal due to AE: 3 |
‐ | ‐ |
Ebrahim 2022 | ‐ | Any AE: 0/30 Withdrawals due to AE: 0 |
‐ | ‐ | Any AE: 0/30 Withdrawals due to AE: 0 |
‐ |
Eidi 2018 | ‐ | ‐ | Any AE: 2/30 (abdominal ascites (acute): 1; vertigo: 1) Withdrawal due to AE: 2/30 |
Any AE: 0/29 Withdrawal due to AE: 0/29 |
‐ | ‐ |
Elamin 2017 | ‐ | Any AE: unclear/36 Withdrawal due to AE: unclear/36 |
‐ | ‐ | ‐ | Quote: "GA supplements were well tolerated with no significant gastrointestinal side effects (Table 4). One patient discontinued the supplements after one dose because she did not like the texture of the solution." Comment: these were reported as a mean across the entire 3 prebiotic groups |
Esgalhado 2018 | ‐ | Any AE: unclear/19 (unclear deaths but not related to study drugs) Withdrawal due to AE: unclear |
‐ | Any AE: unclear/19 (unclear deaths but not related to study drugs) Withdrawal due to AE: unclear |
‐ | Withdrawals and dropout reasons are unclear whether attributed to study drug or other reasons |
Guida 2014 | Any AE: 0/18 Withdrawal due to AE: 0/18 |
Any AE: 0/12 Withdrawal due to AE: 0/12 |
‐ | ‐ | ‐ | ‐ |
Guida 2017 | Any AE: 13/22 Withdrawal due to AE: 0/22 |
Any AE: 0/12 Withdrawal due to AE: 0/12 |
‐ | ‐ | ‐ | Quote: "Treatment with synbiotics was well tolerated with no relevant gastrointestinal adverse effect; borborygmi were reported as occasional by most patients (60%), whereas abdominal pain was virtually absent in both groups." |
He 2022 | ‐ |
Oligosaccharide Any AE: 0/33 Withdrawal due to AE: 0/33 Maltodextrin Any AE: 1/33 (peritonitis: 1) Withdrawal due to AE: 1/33 (peritonitis: 1) |
‐ | ‐ | ‐ | ‐ |
Haghighat 2019 | Any AE: 1/50 (headache: 1) Withdrawal due to AE: 0 |
Any AE: 3/25 (headache: 1; fatigue: 1; breathing problems: 1) Withdrawal due to AE: 0 |
‐ | ‐ | ‐ | These adverse events in this study were judged by the authors to be unrelated to study interventions |
Khosroshahi 2018 | ‐ | Any AE: 5/25 (epigastric pain and vomiting: 1; distention: 2; nausea: 2) Withdrawal due to AE: 1 (epigastric pain and vomiting: 1) |
‐ | Any AE: 2/25 (dyspepsia: 1; nausea: 1) Withdrawal due to AE: 0 |
‐ | |
Kooshki 2019 | Any AE: not reported/25 Withdrawal due to AE: not reported |
‐ | ‐ | Any AE: not reported/25 Withdrawal due to AE: not reported |
‐ | ‐ |
Li 2020 | ‐ |
Inulin Any AE: 2/19 (peritonitis: 2) Withdrawals due to AE: 2 Maltodextrin Any AE: 3/20 (peritonitis: 2; death: 1 (not related to study drug)) Withdrawal due to AE: 3 |
‐ | ‐ | ‐ | Data are not entered into meta‐analysis as these are from both phases of cross‐over |
Lim 2021 | ‐ | ‐ | Any AE: 2/28 (infection: 2) Withdrawal due to AE: 2/28 (hospitalisation due to infection: 2) |
Any AE: 0/28 Withdrawal due to AE: 0/28 |
‐ | One death in each arm but not related to study treatment Quote: "No significant gastrointestinal side effects were reported or recorded throughout the study in either group." |
Liu 2020 | ‐ | ‐ | Any AE: unclear/25 Withdrawal due to AE: unclear/25 |
Any AE: unclear/25 Withdrawal due to AE: unclear/25 |
Three from probiotics and 2 from placebo discontinued but reasons not provided and unclear whether related to adverse effects from study intervention or simply lost. | |
Lopes 2018 | Any AE: 14/49 (abdominal discomfort: 3; did not fit the food: 5; difficulty consuming product at home: 2; hospitalisation and death (unclear whether related to study): 4) Withdrawal due to AE: 10 (abdominal discomfort: 3; did not fit the food: 5; difficulty consuming product at home: 2) |
Any AE: 13/50 (abdominal discomfort: 4; did not fit the food: 5; difficulty consuming product at home: 4) Withdrawal due to AE: 13 (abdominal discomfort: 4; did not fit the food: 5; difficulty consuming product at home: 4) |
‐ | ‐ | ‐ | ‐ |
Lydia 2022 | Any AE: 9/30 (diarrhoea: 6; nausea: 2; bloating: 1) Withdrawal due to AE: 2/30 (diarrhoea: 2) |
‐ | ‐ | Any AE: 7/30 (diarrhoea: 2; nausea: 3; stomach ache/heartburn: 2) Withdrawal due to AE: 0/30 |
‐ | ‐ |
Mafi 2018 | ‐ | ‐ | Any AE: not reported/30 Withdrawal due to AE: 0/30 |
Any AE: not reported/30 ThreeWithdrawal due to AE: 0/30 |
‐ | Three withdrawals from each group due to personal reasons and not related to the study drug |
Mazruei Arani 2019 | ‐ | ‐ | Any AE: not reported/30 Withdrawals due to AE: not reported/30 |
Any AE: not reported/30 Withdrawals due to AE: not reported/30 |
‐ | Two withdrawals from probiotic group, 1 withdrawal from placebo group. Reasons not provided and unclear whether related to study or not |
Meng 2019 | ‐ | Any AE: 1/37: AE not specified Withdrawal due to AE: 1/37 |
‐ | ‐ | Any AE: 0/38 Withdrawal due to AE: 0/38 |
‐ |
Miraghajani 2017 | ‐ | ‐ | Any AE: not reported/24 Withdrawals due to AE: 0/24 |
‐ | Any AE: not reported/24 Withdrawals due to AE: 0/24 |
|
Miranda Alatriste 2014 | ‐ | ‐ |
Lower dose Any AE: 0/15 Withdrawal due to AE: 0/16 Higher dose Any AE: 0/15 Withdrawal due to AE: 0/16 |
‐ | ‐ | One hospitalised with urinary tract infection in low dose probiotic group, but not specified whether this was related to study drug One participant did not tolerate the drink, but this was during inclusion criteria and pre‐randomisation |
Mirzaeian 2020 | Any AE: 0/24 Withdrawal due to AE: 0/24 |
Any AE: 0/24 Withdrawal due to AE: 0/24 |
‐ | ‐ | ‐ | One death in each arm; however, not related to the study intervention |
Natarajan 2014 | ‐ | Any AE: unclear/28 Withdrawal due to AE: unclear/28 |
Any AE: 2/28 Withdrawal due to AE: 2/28 (nausea and vomiting: 2) |
‐ | ‐ | Cross‐over numbers and denominators are unclear One death not related to study intervention: myocardial infarction at home from underlying cardiovascular conditions |
Pan 2021 | ‐ | Any AE: 0/58 Withdrawals due to AE: 0/58 |
Any AE: 0/58 Withdrawals due to AE: 0/58 |
‐ | ‐ | Other lost to follow‐up not related to study treatment |
PREBIOTIC 2022 | ‐ | Any AE: 15/27 (UTI: 9; skin: 2; GI: 1; other: 3) Serious AE: 9/27 (hospitalised due to GI issue: 4; hospitalised due to skin issue: 2; hospitalised due to other: 3) Withdrawals due to AE: unclear/27 |
‐ | Any AE: 14/27 (bloodstream infection: 1; respiratory infection: 1; UTI: 6; skin issue: 3; cardiovascular: 1; GI: 2) Serious AE: 1/27 (hospitalised due to UTI: 1) Withdrawals due to AE: unclear/27 |
‐ | Withdrawals due to adverse events are unclear. There appear to be several discontinued participants in both arms. Reasons not linked to whether these are due to adverse events or practicalities of the feasibility trial. ITT analysis was undertaken |
ProbiotiCKD 2019 | ‐ | ‐ | Any AE: 0/14 Withdrawal due to AE: 0/14 |
Any AE: 0/14 Withdrawal due to AE: 0/14 |
‐ | ‐ |
Poesen 2016 | ‐ |
Rabinoxylan Any AE: 1/40 (nausea) Withdrawal due to AE: 1/40 Maltodextrin Any AE: 0/40 Withdrawal due to AE: 0/40 |
‐ | ‐ | ‐ | ‐ |
Ranganathan 2009 | ‐ | ‐ | Any AE: 0/16 Withdrawal due to AE: 0/16 |
Any AE: 0/16 Withdrawal due to AE: 0/16 |
‐ | Three were withdrawn not due to adverse effects from study treatment The serious AE,MI, was not clear which group |
Ramos 2019 | ‐ |
Fructo‐oligosaccharide Any AE: 0/24 Withdrawal due to AE: 0 Maltodextrin Any AE: 0/26 Withdrawal due to AE: 0 |
‐ | ‐ | ‐ | The discontinued patients were not due to GI symptoms or due to the need of antibiotics |
Shariaty 2017 | ‐ | ‐ | Any AE: not reported/18 Withdrawals due to AE: not reported |
Any AE: not reported/18 Withdrawals due to AE: not reported |
‐ | No adverse events reported, possible none |
Sirich 2014 | ‐ | Any AE: 0/28 Withdrawal due to AE: 2/28 |
‐ | ‐ | Any AE: 2/28 (bloating: 1; loose stools: 1) Withdrawal due to AE: 2/28 (bloating: 1; loose stools: 1) |
‐ |
Soleimani 2017 | ‐ | ‐ | Any AE: 0/30 Withdrawals due to AE: 0 |
Any AE: 0/30 Withdrawals due to AE: 0 |
‐ | ‐ |
Soleimani 2019 | Any AE: 0/30 Withdrawals due to AE: 0 |
‐ | ‐ | Any AE: not reported/30 Withdrawals due to AE: 0 |
‐ | Side effects only reported for synbiotic group Quote: "No side effects were reported following the consumption of synbiotic in diabetic patients undergoing HD throughout the study." |
SYNERGY 2014 | Any AE: 1/unclear Withdrawals due to AE: unclear |
Any AE: 2/unclear Withdrawals due to AE: unclear |
‐ | ‐ | ‐ | Cross‐over denominators not reported Three AE occurred during washout period |
SYNERGY II 2021 | Any AE: 11/35 Withdrawals due to AE: 0/35 One participant died during the study period for reasons unrelated to the study |
Any AE: 7/33 Withdrawals due to AE: 0/33 |
‐ | ‐ | Eighteen serious AE in total: 7 in prebiotic (placebo) group, and 11 in synbiotic group. Initial hospitalisation accounted for 17 serious AEs Synbiotic group: 1 participant died during the study period for reasons unrelated to the study |
|
Viramontes‐Horner 2015 | Any AE: 1/22 (diarrhoea: 1) Withdrawals due to AE: 1 |
‐ | ‐ | Any AE: 1/20 (diarrhoea: 2) Withdrawals due to AE: 2 |
‐ | ‐ |
Wang 2015a | ‐ | Any AE: 0/23 Withdrawals due to AE: 0 |
Any AE: 0/18 Withdrawals due to AE: 0 |
‐ | ‐ | Two patients in the probiotics group and five patients in the placebo group dropped out of the study because of noncompliance One patient in the placebo group died due to head injury |
AE: adverse event; GI: gastrointestinal; ITT: intention‐to‐treat; MI: myocardial infarction; UTI: urinary tract infection
Data and analyses
Comparison 1. Synbiotic versus synbiotic.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
1.1 Patient‐reported outcomes: HRQoL at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
1.1.1 CKD stage G5D with diabetes and hypertension | 1 | 46 | Mean Difference (IV, Random, 95% CI) | 1.98 [‐11.12, 15.08] |
Comparison 2. Synbiotic versus prebiotic.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
2.1 Kidney function: eGFR at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.1.1 CKD stage 3Ga (transplant) | 1 | 34 | Mean Difference (IV, Random, 95% CI) | ‐3.80 [‐17.98, 10.38] |
2.2 Kidney function: serum creatinine at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.2.1 CKD stage G5D | 1 | 42 | Mean Difference (IV, Random, 95% CI) | ‐0.20 [‐1.50, 1.10] |
2.3 Uraemic toxins: urea at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.3.1 CKD stage G5D | 1 | 42 | Mean Difference (IV, Random, 95% CI) | ‐2.10 [‐13.93, 9.73] |
2.4 Uraemic toxins: indoxyl sulfate at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.4.1 CKD stage G5D | 1 | 42 | Mean Difference (IV, Random, 95% CI) | 128.30 [‐242.77, 499.37] |
2.5 Uraemic toxins: p‐cresol sulfate at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.5.1 CKD stage 3Ga (transplant) | 1 | 34 | Mean Difference (IV, Random, 95% CI) | ‐2.10 [‐3.92, ‐0.28] |
2.6 GI function: change in any GI upset or intolerance (prevalence of borborygmi) at 4 weeks | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
2.6.1 CKD stage 3Ga (transplant) | 1 | 34 | Risk Ratio (M‐H, Random, 95% CI) | 15.26 [0.99, 236.23] |
2.7 GI function: change in any GI upset or intolerance (GSRS Total Index at 12 months) | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.7.1 CKD Stage 3 to 4 | 1 | 56 | Mean Difference (IV, Random, 95% CI) | 0.00 [‐0.27, 0.27] |
2.8 GI function: faecal pH at 7 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.8.1 CKD stage G5D | 1 | 58 | Mean Difference (IV, Random, 95% CI) | ‐0.63 [‐1.13, ‐0.13] |
2.9 GI function: faecal characteristics (Bristol Stool Chart) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.9.1 CKD stage 3Ga (transplant) | 1 | 34 | Mean Difference (IV, Random, 95% CI) | ‐0.50 [‐1.15, 0.15] |
2.10 GI function: faecal characteristics (Bristol Stool Chart) at 12 months | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.10.1 CKD stage 3 to 4 | 1 | 56 | Mean Difference (IV, Random, 95% CI) | 0.50 [‐0.18, 1.18] |
2.11 Patient‐reported outcomes: HRQoL at 24 weeks | 2 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
2.11.1 CKD stage G5D with diabetes and hypertension | 2 | 65 | Mean Difference (IV, Random, 95% CI) | 6.38 [‐4.88, 17.64] |
2.12 Adverse events: any adverse event | 5 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
2.12.1 CKD stage G3a (transplant) | 2 | 64 | Risk Ratio (M‐H, Random, 95% CI) | 15.26 [0.99, 236.23] |
2.12.2 CKD stage 3 to 4 | 1 | 68 | Risk Ratio (M‐H, Random, 95% CI) | 1.48 [0.65, 3.36] |
2.12.3 CKD stage 5GD | 2 | 147 | Risk Ratio (M‐H, Random, 95% CI) | 1.10 [0.58, 2.09] |
2.13 Withdrawals due to adverse events | 4 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
2.13.1 CKD stage 3Ga (transplant) | 2 | 64 | Risk Ratio (M‐H, Random, 95% CI) | Not estimable |
2.13.2 CKD stage G5D | 2 | 147 | Risk Ratio (M‐H, Random, 95% CI) | 0.78 [0.38, 1.62] |
Comparison 3. Prebiotic versus prebiotic.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
3.1 Kidney function: eGFR at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.1.1 CKD stage 3 to 5 (non‐dialysis) | 1 | 50 | Mean Difference (IV, Random, 95% CI) | 0.00 [‐1.73, 1.73] |
3.2 Uraemic toxins: indoxyl sulfate at 6 weeks | 2 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.2.1 CKD stage G5D with diabetes | 2 | 64 | Mean Difference (IV, Random, 95% CI) | ‐0.20 [‐1.01, 0.61] |
3.3 Uraemic toxins: p‐cresol sulfate at 6 weeks | 2 | Std. Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.3.1 CKD stage G5D with diabetes | 2 | 64 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.04 [‐0.53, 0.45] |
3.4 GI function: change in any GI upset or intolerance (burping) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.4.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.17 [‐0.50, 0.84] |
3.5 GI function: change in any GI upset or intolerance (cramping) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.5.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐0.17 [‐0.50, 0.16] |
3.6 GI function: change in any GI upset or intolerance (distension) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.6.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.33 [‐0.04, 0.70] |
3.7 GI function: change in any GI upset or intolerance (flatulence) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.7.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 1.00 [0.25, 1.75] |
3.8 GI function: change in any GI upset or intolerance (nausea) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.8.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.00 [‐0.00, 0.00] |
3.9 GI function: change in any GI upset or intolerance (reflux) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.9.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.00 [‐0.50, 0.50] |
3.10 GI function: change in any GI upset or intolerance (rumblings) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.10.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.50 [‐0.14, 1.14] |
3.11 GI function: microbiota composition (Actinobacteria) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.11.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐1.26 [‐4.46, 1.94] |
3.12 GI function: microbiota composition (Bacteriodetes) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.12.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 3.23 [‐8.24, 14.70] |
3.13 GI function: microbiota composition (Proteobacteria) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.13.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.11 [‐1.61, 1.83] |
3.14 GI function: microbiota composition (Firmicutes) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.14.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐2.44 [‐14.19, 9.31] |
3.15 GI function: microbiota composition (Synergistetes) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.15.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐0.25 [‐0.89, 0.39] |
3.16 GI function: microbiota composition (Verrucomicrobia) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.16.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.96 [‐1.36, 3.28] |
3.17 GI function: microbiota composition (faecal acetate) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.17.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐69.91 [‐203.95, 64.13] |
3.18 GI function: microbiota composition (faecal propionate) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.18.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐19.35 [‐63.87, 25.17] |
3.19 GI function: microbiota composition (faecal butyrate) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.19.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐11.04 [‐39.57, 17.49] |
3.20 GI function: microbiota composition (faecal total short‐chain fatty acids) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.20.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐104.71 [‐293.34, 83.92] |
3.21 GI function: microbiota composition (faecal indoles) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.21.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 2.71 [‐69.78, 75.20] |
3.22 GI function: microbiota composition (faecal p‐cresol) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.22.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 28.84 [‐105.07, 162.75] |
3.23 GI function: faecal characteristics (bowel movements) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.23.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐0.27 [‐1.23, 0.69] |
3.24 GI function: faecal characteristics (ease of passage) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.24.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | 0.00 [‐0.90, 0.90] |
3.25 GI function: faecal characteristics (consistency) at 4 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
3.25.1 CKD stage G5D with diabetes | 1 | 24 | Mean Difference (IV, Random, 95% CI) | ‐0.19 [‐1.34, 0.96] |
3.26 Adverse events: number participants reporting an event | 2 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
3.26.1 CKD stage G5D | 2 | 79 | Risk Ratio (M‐H, Random, 95% CI) | 2.92 [0.10, 88.03] |
3.27 Withdrawals due to adverse events | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
3.27.1 CKD stage G5D | 1 | 39 | Risk Ratio (M‐H, Random, 95% CI) | 0.70 [0.13, 3.75] |
Comparison 4. Prebiotic versus probiotic.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
4.1 Dialysis outcomes: peritonitis at 24 weeks | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
4.1.1 CKD stage G5D with diabetes and hypertension | 1 | 47 | Risk Ratio (M‐H, Random, 95% CI) | Not estimable |
Comparison 5. Low versus high dose probiotic.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
5.1 Kidney function: GFR at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
5.1.1 CKD stage G3 to G4 | 1 | 30 | Mean Difference (IV, Random, 95% CI) | ‐0.64 [‐9.51, 8.23] |
5.2 Kidney function: serum creatinine at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
5.2.1 CKD stage G3 to G4 | 1 | 30 | Mean Difference (IV, Random, 95% CI) | ‐0.13 [‐0.89, 0.63] |
5.3 Uraemic toxins: urea at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
5.3.1 CKD stage G3 to G4 | 1 | 30 | Mean Difference (IV, Random, 95% CI) | 4.57 [‐9.52, 18.66] |
Comparison 6. Synbiotic versus placebo.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
6.1 Kidney function: eGFR at 6 or 12 weeks | 2 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
6.1.1 CKD stage G3b | 2 | 98 | Mean Difference (IV, Random, 95% CI) | 1.42 [0.65, 2.20] |
6.2 Kidney function: SrCr at 6 or 12 weeks | 2 | 98 | Mean Difference (IV, Random, 95% CI) | ‐0.57 [‐1.08, ‐0.07] |
6.2.1 CKD stage G3b | 2 | 98 | Mean Difference (IV, Random, 95% CI) | ‐0.57 [‐1.08, ‐0.07] |
6.3 Uraemic toxins: urea at 6 or 12 weeks | 2 | 117 | Mean Difference (IV, Random, 95% CI) | 3.34 [‐15.65, 22.32] |
6.3.1 CKD stage G3b | 1 | 75 | Mean Difference (IV, Random, 95% CI) | ‐3.48 [‐14.50, 7.54] |
6.3.2 CKD stage G5D with diabetes and hypertension | 1 | 42 | Mean Difference (IV, Random, 95% CI) | 17.10 [‐8.80, 43.00] |
6.4 GI function: GSRS Item 6 (rumbling) at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
6.4.1 CKD stage 3b | 1 | 23 | Mean Difference (IV, Random, 95% CI) | ‐0.54 [‐0.77, ‐0.31] |
6.5 GI function: GSRS Item 13 (hard stools) at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
6.5.1 CKD stage 3b | 1 | 23 | Mean Difference (IV, Random, 95% CI) | ‐0.09 [‐0.35, 0.17] |
6.6 GI function: abdominal pain at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
6.6.1 CKD stage 3b | 1 | 23 | Mean Difference (IV, Random, 95% CI) | 0.22 [‐0.02, 0.46] |
6.7 GI function: constipation syndrome at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
6.7.1 CKD stage 3b | 1 | 23 | Mean Difference (IV, Random, 95% CI) | ‐0.17 [‐0.72, 0.38] |
Comparison 7. Prebiotic versus placebo or no treatment.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
7.1 Kidney function: serum creatinine at 8 or 12 weeks | 3 | 145 | Mean Difference (IV, Random, 95% CI) | 0.52 [‐2.39, 3.44] |
7.1.1 CKD stage A2 with diabetic nephropathy | 1 | 70 | Mean Difference (IV, Random, 95% CI) | 4.70 [0.47, 8.93] |
7.1.2 CKD stage G5D | 2 | 75 | Mean Difference (IV, Random, 95% CI) | ‐0.75 [‐3.16, 1.66] |
7.2 Uraemic toxins: urea at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.2.1 CKD stage A2 with diabetic nephropathy | 1 | 70 | Mean Difference (IV, Random, 95% CI) | ‐0.40 [‐0.86, 0.06] |
7.3 Uraemic toxins: indoxyl sulfate at 8 weeks | 2 | Std. Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.3.1 CKD stage G5D | 2 | 75 | Std. Mean Difference (IV, Random, 95% CI) | ‐0.14 [‐0.60, 0.31] |
7.4 Uraemic toxins: p‐cresyl sulfate at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.4.1 CKD stage G5D | 1 | 44 | Mean Difference (IV, Random, 95% CI) | ‐1.68 [‐14.30, 10.94] |
7.5 GI function: microbiota composition (Facealibacterium) at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.5.1 CKD stage 5GD | 1 | 44 | Mean Difference (IV, Random, 95% CI) | 2.37 [0.23, 4.51] |
7.6 GI function: microbiota composition (Parabacteroides) at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.6.1 CKD stage 5GD | 1 | 44 | Mean Difference (IV, Random, 95% CI) | 0.22 [0.06, 0.38] |
7.7 GI function: microbiota composition (Bifidobacteria) at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.7.1 CKD stage 5GD | 1 | 44 | Mean Difference (IV, Random, 95% CI) | ‐3.92 [‐9.83, 1.99] |
7.8 GI function: microbiota composition (Ruminococcus) at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.8.1 CKD stage 5GD | 1 | 44 | Mean Difference (IV, Random, 95% CI) | 3.86 [‐0.32, 8.04] |
7.9 GI function: microbiota composition (Prevotella) at 8 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
7.9.1 CKD stage 5GD | 1 | 44 | Mean Difference (IV, Random, 95% CI) | ‐0.43 [‐1.45, 0.59] |
7.10 Adverse events: any adverse event (number of participants) | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
7.10.1 CKD stage G5D | 1 | 50 | Risk Ratio (M‐H, Random, 95% CI) | 2.50 [0.53, 11.70] |
7.11 Withdrawals due to adverse events | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
7.11.1 CKD stage G5D | 1 | 50 | Risk Ratio (M‐H, Random, 95% CI) | 3.00 [0.13, 70.30] |
Comparison 8. Probiotic versus placebo or no treatment.
Outcome or subgroup title | No. of studies | No. of participants | Statistical method | Effect size |
---|---|---|---|---|
8.1 Kidney function: GFR at 8, 12 or 15 weeks | 3 | 128 | Mean Difference (IV, Random, 95% CI) | 2.73 [‐2.28, 7.75] |
8.1.1 CKD stage 1 and type 2 diabetes | 1 | 40 | Mean Difference (IV, Random, 95% CI) | 12.10 [4.19, 20.01] |
8.1.2 CKD stage 3A with diabetes and hypertension | 1 | 28 | Mean Difference (IV, Random, 95% CI) | 0.40 [‐4.15, 4.95] |
8.1.3 CKD stage G5D with diabetes and hypertension | 1 | 60 | Mean Difference (IV, Random, 95% CI) | 0.02 [‐0.63, 0.67] |
8.2 Kidney function: serum creatinine at 8, 12 or 24 weeks | 6 | 303 | Mean Difference (IV, Random, 95% CI) | ‐0.51 [‐1.06, 0.04] |
8.2.1 CKD stage G5D | 1 | 33 | Mean Difference (IV, Random, 95% CI) | ‐0.70 [‐4.48, 3.08] |
8.2.2 Diabetic nephropathy all CKD stages | 2 | 120 | Mean Difference (IV, Random, 95% CI) | ‐1.19 [‐2.96, 0.57] |
8.2.3 CKD stage G5D with diabetes and hypertension | 2 | 110 | Mean Difference (IV, Random, 95% CI) | 0.08 [‐0.48, 0.64] |
8.2.4 CKD stage 1 and type 2 diabetes | 1 | 40 | Mean Difference (IV, Random, 95% CI) | ‐0.17 [‐0.26, ‐0.08] |
8.3 Kidney function: albuminuria at 12 or 24 weeks | 4 | 193 | Mean Difference (IV, Random, 95% CI) | 0.02 [‐0.08, 0.13] |
8.3.1 CKD stage G5D | 1 | 33 | Mean Difference (IV, Random, 95% CI) | 0.00 [‐0.19, 0.19] |
8.3.2 CKD stage G5D with diabetes and hypertension | 3 | 160 | Mean Difference (IV, Random, 95% CI) | 0.03 [‐0.10, 0.16] |
8.4 Kidney function: proteinuria at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
8.4.1 Diabetic nephropathy all CKD stages | 1 | 60 | Mean Difference (IV, Random, 95% CI) | ‐15.60 [‐34.30, 3.10] |
8.5 Uraemic toxins: urea at 12 or 24 weeks | 5 | 263 | Mean Difference (IV, Random, 95% CI) | ‐1.11 [‐2.58, 0.35] |
8.5.1 CKD stage G5D | 1 | 33 | Mean Difference (IV, Random, 95% CI) | 1.80 [‐9.59, 13.19] |
8.5.2 Diabetic nephropathy all CKD stages | 2 | 120 | Mean Difference (IV, Random, 95% CI) | ‐1.90 [‐5.06, 1.26] |
8.5.3 CKD stage G5D with diabetes and hypertension | 2 | 110 | Mean Difference (IV, Random, 95% CI) | 0.06 [‐5.61, 5.72] |
8.6 Uraemic toxins: indoxyl sulfate at 12 or 24 weeks | 2 | 83 | Mean Difference (IV, Random, 95% CI) | ‐4.24 [‐9.83, 1.35] |
8.6.1 CKD stage G5D | 1 | 33 | Mean Difference (IV, Random, 95% CI) | ‐6.00 [‐15.02, 3.02] |
8.6.2 CKD stage G5D with diabetes and hypertension | 1 | 50 | Mean Difference (IV, Random, 95% CI) | ‐3.14 [‐10.26, 3.98] |
8.7 Uraemic toxins: p‐cresyl sulfate at 4, 12 or 24 weeks | 3 | 125 | Mean Difference (IV, Random, 95% CI) | ‐2.12 [‐5.19, 0.95] |
8.7.1 CKD stage G5D | 2 | 75 | Mean Difference (IV, Random, 95% CI) | ‐1.27 [‐2.31, ‐0.24] |
8.7.2 CKD stage G5D with diabetes and hypertension | 1 | 50 | Mean Difference (IV, Random, 95% CI) | ‐6.21 [‐13.92, 1.50] |
8.8 Uraemic toxins: indole‐3‐acetic acid acid at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
8.8.1 CKD stage G5D | 1 | 33 | Mean Difference (IV, Random, 95% CI) | ‐288.10 [‐464.41, ‐111.79] |
8.9 GI function: any GI upset or intolerance (abdominal pain/diarrhoea) at 12 weeks | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
8.9.1 CKD stage G5D | 1 | 33 | Risk Ratio (M‐H, Random, 95% CI) | 2.12 [0.21, 21.22] |
8.10 GI function: any GI upset or intolerance (constipation) at 12 weeks | 1 | Risk Ratio (M‐H, Random, 95% CI) | Subtotals only | |
8.10.1 CKD stage G5D | 1 | 33 | Risk Ratio (M‐H, Random, 95% CI) | 3.18 [0.14, 72.75] |
8.11 GI function: faecal pH at 12 weeks | 1 | Mean Difference (IV, Random, 95% CI) | Subtotals only | |
8.11.1 CKD stage G5D | 1 | 20 | Mean Difference (IV, Random, 95% CI) | ‐0.30 [‐0.83, 0.23] |
8.12 Adverse events: any adverse event (number of participants) | 4 | 205 | Risk Ratio (M‐H, Random, 95% CI) | 1.96 [0.63, 6.12] |
8.12.1 CKD stage 1 and type 2 diabetes | 1 | 44 | Risk Ratio (M‐H, Random, 95% CI) | 0.80 [0.25, 2.59] |
8.12.2 CKD stage G5D | 2 | 105 | Risk Ratio (M‐H, Random, 95% CI) | 4.95 [0.90, 27.12] |
8.12.3 CKD stage G5D with diabetes and hypertension | 1 | 56 | Risk Ratio (M‐H, Random, 95% CI) | 5.00 [0.25, 99.67] |
8.13 Withdrawals due to adverse events | 4 | 205 | Risk Ratio (M‐H, Random, 95% CI) | 4.96 [1.13, 21.77] |
8.13.1 CKD stage G5D | 2 | 105 | Risk Ratio (M‐H, Random, 95% CI) | 4.95 [0.90, 27.12] |
8.13.2 CKD stage G5D with diabetes and hypertension | 1 | 56 | Risk Ratio (M‐H, Random, 95% CI) | 5.00 [0.25, 99.67] |
8.13.3 CKD stage 1 and type 2 diabetes | 1 | 44 | Risk Ratio (M‐H, Random, 95% CI) | Not estimable |
Characteristics of studies
Characteristics of included studies [ordered by study ID]
Abbasi 2017.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Randomization was done by the use of computer‐generated random numbers" |
Allocation concealment (selection bias) | Low risk | Quote: "Randomization and allocation were concealed from the researcher and volunteers till the analyses were finalised" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The bottles and soy milk were provided by the same soy milk factory. Bottles were identical in shape and probiotics soy milk was indistinguishable in colour, smell, and taste from conventional soy milk" Quote: "At each study visit, participants received sufficient bottles for a 3‐day period until the next visit, in a double‐blinded design" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "All the tests were performed in a blinded fashion, in pairs (before and after the intervention) at the same time, in the same analytic run, and in random order to reduce systematic error and inter‐assay variability" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition: 9% ITT analysis not undertaken |
Selective reporting (reporting bias) | High risk | Trial registration or a priori published protocol: Iranian Registry of Clinical Trials IRCT20161027479N2. Missing outcome data for several planned outcomes from the trial registration, including proteinuria and TNF‐alpha |
Control for confounding factors | Low risk | Pre‐treatment period: 2‐week run‐in phase: participants asked to avoid fermented or probiotic food, avoid consumption of any dietary supplements, report changes in medications Study period: All participants consumed a diet containing 0.8 g/kg protein, 2000 mg sodium, 2000 mg potassium, 1500 mg phosphorus. Obtained using 24‐hour recall food diary |
Other bias | Unclear risk | Conflicts declared: "None declared" Funding declared: Isfahan University of Medical Sciences |
Biruete 2017.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
Washout period
|
|
Outcomes | Outcomes reported by this study at 4 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Participants were randomized using a simple randomization technique (coin toss)" |
Allocation concealment (selection bias) | Low risk | Quote: "Randomization was performed by a research coordinator so that both researchers and participants were blinded to the treatment allocation" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Randomization was performed by a research coordinator so that both researchers and participants were blinded to the treatment allocation" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Not explicitly clear that the outcome assessors are part of the double‐blinding |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided One death not related to study drug Attrition = 8% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT02718885 |
Control for confounding factors | Unclear risk | Pre‐treatment period: no run‐in phase length of time was mentioned. However, patients were excluded if they had been taking antibiotics 1 month prior and could not be currently taking prebiotics or probiotics (length of time unstated) Study period: not reported |
Other bias | High risk | Conflicts declared: "Beneo GmbH donated Orafti Synergy, but had no input in the study design, data analyses, or manuscript preparation. AB was supported by a Predoctoral Fellowship from CONACyT (Mexico’s Council of Science and Technology), a postdoctoral fellowship NIH‐T32 DK120524, has received honoraria from AMGEN, research grants from Keryx Pharmaceuticals for work unrelated to the present manuscript, and is part of the AUGmeNt workgroup from the Academy of Nutrition and Dietetics. BMK has received consulting fees, research grants, and is a member of the AUGmeNt workgroup from the Academy of Nutrition and Dietetics. KRW has received funding from the National Institutes of Health and the Renal Research Institute." Funding declared: "This work was supported by a research grant from the Renal Research Institute (C2930) and the Division of Nutritional Sciences at the University of Illinois (USDA Vision 20/20 research program award)" |
Bliss 1992.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 4 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "Subjects were randomly divided into two groups during dietary period 1" Insufficient information provided regarding methodology used to undertake randomisation, unable to form judgement |
Allocation concealment (selection bias) | Unclear risk | No information provided regarding concealment of the allocation |
Blinding of participants and personnel (performance bias) All outcomes | High risk | "The investigator provided subjects in both groups with the juice mixtures and the subjects were not informed of their content" Single‐blind study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Single‐blind study |
Incomplete outcome data (attrition bias) All outcomes | High risk | No missing outcome data; however no details about which arm non‐completers were from Denominators for each group between cross‐over period are unclear Attrition = 20% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration: not reported |
Control for confounding factors | Low risk | Pre‐treatment period: low protein diet 4 months prior Study period: continued low‐protein diet |
Other bias | High risk | Conflicts declared: "Supported in part by an individual National Research Award (NR06335), the American Nurses' Foundation 1989 Bristol Myers Fund Scholar Award (to DZB), and the 1989 American Nurses' Foundation/Sigma Theta Tau International Scholar Award (to DZB). Welch's brand frozen fruit juice concentrates and Glad‐Lock freezer bags were generously provided by Welch's Foods, Inc (Westfied, NY) and by First Brands Corporation (Danbury, CT), respectively. The price of Nutriloid Gum Arabic Spray Dry Powder was discounted by TIC Gums, Inc (Belcamp, MD)." Funding declared: not reported |
Borges 2018.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | All outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The random sequence of treatment (probiotic and placebo) was manually generated for a simple randomization" |
Allocation concealment (selection bias) | Low risk | Quote: "None of the subjects involved in the study had access to the allocation sequence until the end of the statistical analyses" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The participants and the researchers who interviewed and visited the subjects were blinded to the contents of the bottles, which contained probiotic or placebo capsules" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Researchers who interviewed and visited the subjects were blinded to the contents of the bottles, which contained probiotic or placebo capsules. All laboratory measurements were centralized and performed in a blinded manner." |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided (GI issues related to study drug) Attrition = 30% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial Registration: not reported A priori published protocol: not reported Comment: insufficient information provided to permit judgement. Unclear whether pre‐specified outcome data are reported, if any. Lack of clinically important or relevant outcomes: no issue |
Control for confounding factors | Unclear risk | Pre‐treatment period: none reported Study period: no mention of control for dietary factors during study |
Other bias | High risk | Funding source
Conflicts of interest
|
Cosola 2021.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control Group
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The randomization was performed by an independent researcher by means of software, using gender as a blocking factor" |
Allocation concealment (selection bias) | Unclear risk | No information provided |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Quote: "The powder formulations were anonymously labelled and were undistinguishable for the patients" Single‐blind study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Single‐blind study |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided Attrition = 0% (in CKD participants) ITT analysis undertaken in CKD participants |
Selective reporting (reporting bias) | High risk | Trial registration or a priori published protocol: NCT03815786 Outcomes: "TMAO was not evaluated due to technical problems during the execution of the analysis" |
Control for confounding factors | Unclear risk | Pre‐treatment period: Unclear, "controlled diet" Study period: Unclear |
Other bias | Unclear risk | Conflicts declared: "S.F. is the Chief Executive Officer of Research Center « Sergio Fontana 1900–1982» (Farmalabor); F.M.L.F. is the research and development manager of the Research Center « Sergio Fontana 1900–1982» (Farmalabor). The other authors declare no conflict of interest." Funding declared: "This study has been funded from the XUANRO4‐NATURE‐Nuovo Approccio Per la Riduzione Delle Tossine Uremiche Renali, REGIONE PUGLIA‐FSC 2007–2013 Ricerca. Intervento 'Cluster Tecnologici Regionali' " |
de Andrade 2021.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Washout
Control group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The participants were assigned to sequential treatment with UBF and placebo, or vice versa, after a blocked randomization procedure using a random block of 4 participants in a 1:1 ratio." |
Allocation concealment (selection bias) | Low risk | Quote: "Supplements were packaged in identical sachets and identified by the numbers 225 and 653 in a handling pharmacy, under the responsibility of a pharmacist (Magister Pharmacy, Sao Paulo, Brazil)" Quote: "The list was handed over to another independent researcher who was responsible for separating and allocating supplements to participants" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Supplements were packaged in identical sachets and identified by the numbers 225 and 653 in a handling pharmacy, under the responsibility of a pharmacist (Magister Pharmacy, Sao Paulo, Brazil)" Quote: "The list was handed over to another independent researcher who was responsible for separating and allocating supplements to participants" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 40% Reasons for withdrawals not of major concern related to study treatment ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: Brazilian Clinical Trials Registry (www.ensaiosclinicos.gov.br, IDnumber: RBR‐4xxwwj |
Control for confounding factors | Unclear risk | Pre‐treatment period: "The majority of patients had been previously advised by a renal dietician, according to the nutritional guidelines for patients undergoing peritoneal dialysis" Study period: "During each intervention, the participants were advised to maintain a stable dietary pattern and not to take prebiotics, probiotics, or synbiotics. If necessary, dietary adjustments were advised or reinforced during the follow‐up" |
Other bias | High risk | Conflicts declared: "The authors declare no conflict of interest" Funding declared: "L.S.d.A., F.A.H.S., N.B.F.P., R.R.T., J.D.d.L. received a scholarship from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). SD. Rodrigues receives a scholarship from CAPES—Fundação Araucária and L.C. receives a scholarship from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (#302765/2017‐4). The production and analysis of UBF were supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (#13/07914‐8 (FoRC)). Support for this research was provided by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (#2018/12122‐7)" |
de Araujo 2022.
Study characteristics | ||
Methods | Study design
Study duration
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Software program Research Randomizer® (www.randomizer.org) was used to randomly assign participants to study groups. Individuals in Group 1 (G1) were administered supplementation with probiotics and subjects in Group 2 (G2) were given placebo." |
Allocation concealment (selection bias) | Low risk | Quote: "The researcher and the participants were blinded for the sequential allocation and the codes assigned to supplementation or placebo" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The supplements and placebo offered to patients had equal organoleptic characteristics... The capsules had the same colour, physical appearance, and flavour" Insufficient information provided to permit judgement |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | No information provided to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 13% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: not reported |
Other bias | High risk | Conflicts of interest: "The authors have no conflict of interest to declare" Funding declared: "The authors would like to thank the following institutions for their support: Compounding pharmacies BioPhormula and Galena Farmacêutica for donating probiotics to the study; the authors of the study have no financial ties with the compounding pharmacies. The Ceará Foundation for Scientific and Technological Development (FUNCAP) for funding and encouraging the organization of this trial. The National Council for Scientific and Technological Development (CNPq) for offering performance scholarships to researchers AMCM, EFD e GBSJ." Industry funding |
Dehghani 2016.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | All outcomes reported by this study at 6 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "This study was a randomized ... clinical trial" |
Allocation concealment (selection bias) | Unclear risk | Quote: No information regarding the concealment of allocation to treatment groups |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "For blinding, placebo was produced in similar colour and appearance of the supplement capsules, as well as the shape of packaging (Zist Takhmir, Tehran, Iran). To differentiate the two types of capsules, a small code was written on the box of the capsules (‘A’ or ‘B’), and neither the patients nor the person delivering the capsule to the patients were informed of the codes and type of supplement capsules." |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | No information provided |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided Attrition = 13% ITT analysis not/undertaken Quote: "Attrition criteria were the use of antibiotics and lactulose during the study and starting treatment with haemodialysis." |
Selective reporting (reporting bias) | High risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Unclear risk | Pre‐treatment period: none reported Study period: no control for dietary factors reported |
Other bias | High risk | Funding source: not reported Conflicts of interest: "None declared" |
Ebrahim 2022.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 14 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Participants (were) randomized to the prebiotic supplement or the diet control group using a simple computer‐generated randomized list with an equal allocation ratio" |
Allocation concealment (selection bias) | High risk | Quote: "Sequentially numbered sealed opaque envelopes were used to assign group allocation" Single‐blind study, blinded to the investigators |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Quote: "The principal investigator (PI) was blinded to the treatment" Single‐blind study, blinded to the investigators |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information provided to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 24% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: PACTR202002892187265 |
Control for confounding factors | Low risk | Pre‐treatment period: "All participants had a 4 week run‐in period on diet only before being randomized to the prebiotic supplement or the diet control group" Study period: Co‐intervention was diet control |
Other bias | Low risk | Conflicts declared: "The authors declare no conflict of interest" Funding declared: "This study received funding from the Early Researcher Fund (Stellenbosch University), Thuthuka National Research Fund (Thuthuka grant number: 129901) and the Harry Crossley Foundation" |
Eidi 2018.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 4 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "Triple ‐blind randomized placebo‐controlled trial with an allocation ratio of (1:1)" Quote: "The eligible participants were randomly assigned to Lactobacillus Rhamnosus as probiotics or placebo groups by a randomization procedure and subject were matched in each arms regarding to age, sex and history of haemodialysis duration." |
Allocation concealment (selection bias) | Unclear risk | No information regarding the concealment of allocation to treatment groups. Insufficient information provided within abstract to permit judgement. |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Study states to be triple‐blind however no information regarding the methods use to keep participants or study personnel blinded treatment groups Insufficient information provided within abstract to permit judgement |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Study states to be triple‐blind however no information regarding the methods use to keep outcome assessors blinded treatment groups. Insufficient information provided within abstract to permit judgement. |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = unclear ITT analysis unclear Serious issues regarding ITT population, number of participants received intervention, whether ITT analysis was correctly performed. Numbers do not match. |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: IRCT201504182017N21. Study registration planned a 4‐arm trial: (1) Probiotic; Lactobacillus rhamnosus (16 Billion CFU) one capsule per day for 28 days; (2) Prebiotic; Inulin (10 grams) one sachet per day for 28 days; (3) Synbiotic; Lactobacillus Rhamnosus (16 Billion CFU, one capsule) with Inulin (10 grams, one sachet) per day for 28 days; (4) Corn starch (10 grams, one sachet) with Infant formula (one capsule) per day, for 28 days. Query on why this was not undertaken Lack of clinically important or relevant outcomes: no issue |
Control for confounding factors | Unclear risk | Pre‐treatment period: Nothing reported Study period: "All the participants were asked not to change their usual dietary intakes, recommended vitamin or minerals supplements, physical activity, medication or traditional medicine as adjuvant therapy over the course of the study." "Food intake was assessed using three 24‐h dietary recalls undertaken on separate days (one haemodialysis weekday, one non‐haemodialysis weekday and one non‐haemodialysis weekend day) using a visual aid photo album of real foods before and after treatment. Energy and nutrient intake were analyzed using Nutritionist IV (Axxya Systems, Stafford, TX)." |
Other bias | Low risk | Conflicts declared
Funding declared
|
Elamin 2017.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group 1
Intervention group 2
Intervention group 3
|
|
Outcomes | All outcomes reported by this study at 4 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "According to recruitment order, we divided patients into three equal groups using computer‐generated random number lists" |
Allocation concealment (selection bias) | Unclear risk | No information regarding the concealment of allocation to treatment groups |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Open‐label study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Open‐label study |
Incomplete outcome data (attrition bias) All outcomes | Unclear risk | All participants were accounted for with reasons for withdrawals provided Attrition = 25% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: not reported |
Other bias | Unclear risk | Conflicts declared: "The authors declared no conflicts of interest" Funding declared: "This clinical trial was funded by a generous grant from King Abdul‐Aziz City for Science and Technology (KACST) in Saudi Arabia (no. 35‐300). The authors would like to acknowledge their gratitude to Professor Yacine Badjah and the Chair of Advanced Materials Research at King Saud University in Riyadh for their kind assistance in performing the liquid chromatography assay." |
Esgalhado 2018.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
Cross‐over
|
|
Outcomes | All outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "An independent investigator, with no involvement in the study, randomized and allocated the patients in two groups. The randomization and the allocation were created using the statistical RStudio software version 1.1463, and the allocation of the patients to different groups was performed using a statistical tool that generates random samples without replacement." |
Allocation concealment (selection bias) | Low risk | Quote: "An independent investigator, with no involvement in the study, randomized and allocated the patients in two groups. The randomization and the allocation were created using the statistical RStudio software version 1.1463, and the allocation of the patients to different groups was performed using a statistical tool that generates random samples without replacement." |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Quote: "The study investigators were blinded until the end of the supplementations" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Quote: "The study investigators were blinded until the end of the supplementations" |
Incomplete outcome data (attrition bias) All outcomes | Unclear risk | All participants were accounted for with reasons for withdrawals provided Attrition = 28% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial Registration or a priori published protocol: NCT02706808 |
Control for confounding factors | Unclear risk | Pre‐treatment period: excluded if had been taking catabolic drugs, antioxidants or vitamin supplements, pre‐, pro‐, synbiotic and antibiotic in the last 3 months before this study Study period: none reported |
Other bias | High risk | Conflicts declared: "There are no conflicts to declare" Funding declared: "The resistant starch from Hi‐Maize® 260 used for supplementation was kindly provided by Ingredion, USA.This study was supported in parts by grants from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)" |
Guida 2014.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 4 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Patients were allocated to the two study groups by simple randomization using a computer‐generated random binary list" |
Allocation concealment (selection bias) | Low risk | Quote: "The medical doctor performing the first visit was responsible for enrolment and randomized group assignment. Neither the patients nor the medical doctors performing further patient evaluation were aware of group assignment." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Neither the patients nor the medical doctors performing further patient evaluation were aware of group assignment" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Neither the patients nor the medical doctors performing further patient evaluation were aware of group assignment" |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for Attrition = 0% ITT analysis undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT02008331 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: all participants remained on their standard diet and drug regimen during the study |
Other bias | Unclear risk | Conflicts declared: not reported Funding declared: "Sincere thanks to Dr. A. Caramelli (CadiGroup. Rome. Italy) for providing placebo and Probinul neutroÒ. There was no external funding for the present study." Potentially industry‐funded intervention |
Guida 2017.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
Co‐interventions or additional treatments
|
|
Outcomes | Outcomes reported by this study at 4 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Uneven randomization was chosen to encourage patient participation" Quote: "Using a computer‐generated random binary list, they were allocated to one of 2 arms" |
Allocation concealment (selection bias) | Unclear risk | Insufficient information provided to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Quote: "This was a single‐centre, parallel‐group, 2:1 synbiotic to placebo randomized and double‐blinded study" Methods used to ensure this blinding were not provided |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | No information provided to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided Attrition = 8% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial Registration or a priori published protocol: NCT02179229 |
Control for confounding factors | Low risk | Pre‐treatment period: "At the time of enrolment, patients were already taking the standard diet that we recommend to all kidney transplant recipients who attend our nutrition unit for consultation. This Mediterranean pattern diet is based on foods rich in monounsaturated fatty acids, such as olive oil—the primary source of fat in a Mediterranean diet—or in complex carbohydrates and fibres such as whole grains, fruit, vegetables, and legumes." Study period: "Both study groups remained on a standard diet and drug regimen during the study." "In accordance with current nutritional guidelines for kidney transplanted patients [35–37], our dietary plan fits an energy intake higher than 25/kcal/kg/ideal body weight/day, with 55% of carbohydrates and total fat not exceeding 30% of calories (fatty acids < 10% of calories and dietary cholesterol limited to 300 mg/day). In addition; protein intake is restricted to 0.8 g/kg of ideal body weight/day. Our diet includes both insoluble and soluble fibres in a ratio of about 3 to 1 because of the high content of insoluble fibres in whole grains and vegetables. Patients are left free to drink water as they need and the average volume of water intake ranges between 1.5 and 2.0 L/day. Diet composition was determined by expert dietitians who interviewed each patient using a detailed food frequency questionnaire that includes 130 foods and beverages [38]. This questionnaire inquires about amount and frequency of foods and beverages consumed everyday by the patient. Data on nutrient composition of the different foods were obtained using the tables of the Italian National Institute of Nutrition, Souci’s Food Composition and Nutrition Tables, and the European Institute of Oncology as reported elsewhere [33,39]. Data were analyzed with an Excel‐based computer program." |
Other bias | High risk | Conflicts declared: not reported Funding declared: not reported |
Haghighat 2019.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group 1
Intervention group 2
Control group
Co‐interventions or additional treatments
|
|
Outcomes | All outcomes recorded at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "A research assistant from Tak Gen Zist Pharmaceutical Company, who was not otherwise involved in the study, performed the randomization. Patients were randomly assigned to one of three study groups following a block randomization procedure with stratified patients in each block based on sex and age. Randomization assignment was carried out using computer‐generated random numbers." |
Allocation concealment (selection bias) | Low risk | Quote: "Supplement packaging was done in Tak Gen Zist Pharmaceutical Company" Quote: "A nutritionist at the haemodialysis centre, who was not a member of the core study team and not aware of random sequences, conducted the randomized allocation sequence, enrolling participants and allocating them to interventions. Randomization and allocation were hidden from the researchers and patients until the final analyses were completed." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Randomization and allocation were hidden from the researchers and patients until the final analyses were completed. Sachets (synbiotic, probiotic and placebo) were pre‐packaged according to the randomization code by Tak Gen Zist Pharmaceutical Company, Tehran, Iran." |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Randomization and allocation were hidden from the researchers and patients until the final analyses were completed. Sachets (synbiotic, probiotic and placebo) were pre‐packaged according to the randomization code by Tak Gen Zist Pharmaceutical Company, Tehran, Iran." |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided Attrition = 13% ITT not undertaken; analysis based on completers N = 65 |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: IRCT2017041233393N1 |
Control for confounding factors | Low risk | Pre‐treatment period: 3 months prior: no steroidal and/or nonsteroidal anti‐inflammatory drugs and antibiotics, antioxidant, and/or anti‐inflammatory supplements (e.g., vitamin E, vitamin C, and omega‐3 fatty acids), pre‐, pro‐, and synbiotic and other forms of probiotics (including probiotic yogurt, kefir, and other fermented foods) Study period: "Throughout the intervention, patients were requested to maintain stable dietary intakes, physical activity, medications, and not to consume any supplements other than the one provided to them by this trial" |
Other bias | High risk | Conflicts declared: "The authors declare that they have no conflicts of interest" Funding declared: Packaging provided by industry; "Supplement packaging was done in Tak Gen Zist Pharmaceutical Company"; "This study was supported by grants from Vice Chancellor of Research, Ahvaz University of Medical Sciences (Ahvaz, Iran)" |
Haghighat 2019 (second comparison).
Study characteristics | ||
Methods | ||
Participants | ||
Interventions | ||
Outcomes | ||
Notes | This study has been split into 2 for the meta‐analysis in this review. We needed to add a third arm under the same comparison: Synbiotic versus Prebiotic |
He 2022.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Washout
Control Group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The random allocation sequence was generated by an investigator without involvement in subject recruitment. Computer‐generated randomization numbers were obtained from the tool on the website http://tools.medsci.cn/rand/getNewNum to set the treatment order for eligible participants." |
Allocation concealment (selection bias) | Unclear risk | Quote: Insufficient information provided to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "All participants and investigators (except the research designer) were blinded to intervention allocation and data analysis" Quote: "The placebo was identical to the prebiotics in appearance, packaging and schedule of administration" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "All participants and investigators (except the research designer) were blinded to intervention allocation and data analysis" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 52% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: ChiCTR‐INR‐17013739 |
Control for confounding factors | Low risk | Pre‐treatment period: "The first intervention period was preceded by a 2‐week run‐in phase during which patients were instructed to maintain their habitual diet and physical activity" Study period: "Dietary intake data were collected via 3‐day food records completed by the participants in real time and reviewed by nutritionists during each intervention period" |
Other bias | Low risk | Conflicts declared: "The authors declare that they have no conflict of interest" Funding declared: "This work was supported by National Natural Science Foundation of China [grant numbers: 81673161]" |
Khosroshahi 2018.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | All outcomes measured at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Patients were ... randomly allocated to two groups: Intervention (HAM‐RS2) and comparison (placebo) using a randomization list generated by Randlist software (version 1.2), resulting 25 patients in each group" |
Allocation concealment (selection bias) | Unclear risk | Quote: "The crackers had the same rectangular shape, weight (60 g) and calories" Insufficient information regarding allocation concealment, but probably okay |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "As a double‐blind study, the patients and clinical investigators were blinded from knowing the per‐patient treatment regimen" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "As a double‐blind study, the patients and clinical investigators were blinded from knowing the per‐patient treatment regimen" Probably includes outcome assessors |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 16% ITT analysis not undertaken, based on completers N = 44 |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: IRCT2016062628644N1 |
Control for confounding factors | Unclear risk | Pre‐treatment period: none Study period: not reported |
Other bias | Unclear risk | Conflicts declared: “The authors declare that they have no competing interests” Funding declared: "No one"; "High fibre diet and placebo were prepared as cracker by Araspar Benis Inc. (Tabriz, Iran)" |
Kooshki 2019.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
Co‐interventions or additional treatments
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The subjects were randomly allocated to either the synbiotic or placebo group using blocked randomization" |
Allocation concealment (selection bias) | Unclear risk | Insufficient information provided to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Insufficient information provided to permit judgement |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information provided to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | Unclear risk | All participants were accounted for with reasons for withdrawals provided Attrition = 8% ITTt analysis not appear to be undertaken Quote: "Of the 50 randomized subjects, data from 2 participants from the synbiotic group and 2 from the placebo group were excluded due to lack of patient cooperation in the follow up period" |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Low risk | Pre‐treatment period: participants could not be consuming the following prior to study start: Nigella sativa oil, omega‐3 fatty acid, L‐carnitine, vitamin E and/or C supplements, or steroidal and/or nonsteroidal anti‐inflammatory drugs Study period: subjects in both groups were instructed not to otherwise change their dietary habits, physical activities or drug regimens |
Other bias | Low risk | Conflicts declared: "The authors affirm that they have no conflict of interest to declare" Funding declared: "None" |
Li 2020.
Study characteristics | ||
Methods | Study design
Study duration
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Washout
Control group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The intervention order was randomly assigned using a computer‐based, pre generated intervention order" |
Allocation concealment (selection bias) | Low risk | Quote: "This allocation was concealed to patients, investigators, and data analysts other than the research designer (CY)" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The placebo ... was identical to the prebiotic ... in appearance and packaging and schedule of administration. To maintain overall quality and legitimacy, un‐blinding occurred only in exceptional circumstances when knowledge of the actual treatment was essential for further management" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "The placebo ... was identical to the prebiotic ... in appearance and packaging and schedule of administration. To maintain overall quality and legitimacy, un‐blinding occurred only in exceptional circumstances when knowledge of the actual treatment was essential for further management" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Deaths were not related to study drugs Attrition = 29% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: ChiCTR‐INR‐17013739 |
Control for confounding factors | Unclear risk | Pre‐treatment period: "There was a 2‐wk run‐in period during which participants were instructed to maintain their habitual diet and physical activity and not take prebiotic‐ or probiotic‐containing foods, drinks, and supplements" Study period: not reported |
Other bias | Low risk | Conflicts declared: "The authors report no conflicts of interest" Funding declared: "This project was supported by the National Natural Science Foundation of China (no. 81673161) and the Fundamental Research Funds for the Central Universities (HUST: 2016YXMS222). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript." |
Lim 2021.
Study characteristics | ||
Methods | Study design
Study duration
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 24 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Randomization assignment was performed by the use of computer‐generated block randomization, and the block size was 4" |
Allocation concealment (selection bias) | Low risk | Quote: "Professor Hsueh Fang Wang generated the randomization sequence. Participants, other research staff, and outcome assessors were all blinded to the group assignment process" Quote: "To maintain the conditions of a double‐blind parallel study, the statistician was not aware of the allocation of participants to each intervention. Code breaking was performed after the analysis was completed" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The sachets with probiotics or placebo were indistinguishable in appearance" Quote: "To maintain the conditions of a double‐blind parallel study, the statistician was not aware of the allocation of participants to each intervention. Code breaking was performed after the analysis was completed" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Participants, other research staff, and outcome assessors were all blinded to the group assignment process" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 11% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT03066921 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: "Participants’ diet, dialysis schedule, and the medications they used did not change during the study. A food frequency questionnaire was used to confirm unchanged diet habits" |
Other bias | High risk | Conflicts declared: "The authors declare that they have no relevant financial interests" Funding declared: "This study was supported by the Ministry of Science and Technology (grant no. MOST 104‐2622‐E‐241‐001‐CC3). The authors are thankful to the New Bellus Enterprise Co., Ltd. (Tainan, Taiwan) for providing us with a sample of Lactobacillus and for sponsoring our study" Industry funding |
Liu 2020.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 24 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Participants were randomly assigned in a 1:1 ratio to either the probiotics or placebo group for 6 months. A computer‐generated random binary list was produced" |
Allocation concealment (selection bias) | Low risk | Quote: "A computer‐generated random binary list was produced by an external statistical consultant and maintained by a member of the department staff who did not deal with patients." Quote: "Neither the patients nor the clinicians performing patient evaluations were aware of group assignments" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Neither the patients nor the clinicians performing patient evaluations were aware of group assignments. Placebo capsules were comparable in appearance, texture, and taste to the probiotics" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Neither the patients nor the clinicians performing patient evaluations were aware of group assignments" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for but reasons for withdrawals were not provided Attrition = 10% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT02929225 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: "Both study groups remained on their standard diet and drug regimen during the study" |
Other bias | High risk | Conflicts declared: "None declared" Funding declared: "The probiotics and placebo capsules were obtained from Sine Pharmaceutical Co., Ltd, Shanghai, China" Industry funding: "This study was supported by Shannxi Provincial Science and Technology Foundation (Grant no. 2017ZDXM‐SF‐057) and the National Natural Science Foundation of China (Grant no. 81570670)" |
Lopes 2018.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
Co‐interventions or additional treatments
Follow‐up details
|
|
Outcomes | Outcomes reported by this study at 7 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "...subjects were randomly distributed into two groups..." Insufficient information provided on methods how random sequence was generated |
Allocation concealment (selection bias) | Unclear risk | Insufficient information provided to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Single‐blind study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Single‐blind study |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Some concern for reasons for withdrawals Attrition = 41% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: www.ensaiosclinicos.gov.br RBR‐2d9ny6 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: not reported |
Other bias | Unclear risk | Conflicts declared: "The authors declare that they have no conflict of interest" Funding declared: "The authors thank the Foundation for Research Support of Minas Gerais (FAPEMIG CDS‐APQ‐01683‐15, Brazil), Coordination for the Improvement of Higher Education Personnel (CAPES, Brazil), National Counsel of Technological and Scientific Development (CNPq, Brazil) and the Embrapa Maize and Sorghum (Brazil) for granting of financial support for undergraduate research and scholarships." |
Lydia 2022.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "This study was a double‐blinded randomized controlled clinical trial" Insufficient information provided on randomization methods |
Allocation concealment (selection bias) | Low risk | Quote: "A third party (pharmacist) randomized the subjects into two study groups using a computer randomizer" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Synbiotics and placebo were both packed on an identical clear gastroenteric coated capsule. Each subject was given one plastic pot containing either intervention or placebo drugs; each identical pot contained 60 capsules. A white paper with information on drug use and administration was placed on the cover of the pot." |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "The drugs were distributed by a third party. None of the patients, researchers, or physicians in charge were aware of the treatment groups" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 5% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT04527640 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: "Food intake was assessed before and after the intervention was administered using 24‐hour food recall and was carried out by a nutritionist" |
Other bias | Low risk | Conflicts declared: "The authors have no conflicts of interest to declare" Funding declared: "The authors received no funding support for this research" |
Mafi 2018.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes measured by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Randomization was carried out using computer‐generated random numbers by a trained staff member at the internal clinic" |
Allocation concealment (selection bias) | Unclear risk | Unclear information, insufficient to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Study states to be double‐blind but provides no further methods on how this was ensured |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Unclear information, insufficient to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided (not related to study drugs) Attrition = 10% ITT analysis undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: IRCT2017061134458N1 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: not reported |
Other bias | High risk | Conflicts declared: "There are no conflicts to declare" Funding declared: "The present study was supported by a grant from the Vice‐Chancellor for Research, KaUMS, Iran (96043). We are grateful to thank LactoCare®, Zisttakhmir Company, in Tehran that provided probiotic capsules for the present study." |
Mazruei Arani 2019.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "Patients with DN were randomly divided into two groups" Insufficient information provided as to how randomization methods were undertaken |
Allocation concealment (selection bias) | Low risk | Quote: "Randomization was done using a random number table by one of the investigators who had no clinical involvement in the study" |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Study states to be double‐blind but insufficient information provided regarding methods to permit judgement |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information provided regarding methods to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for; however, reasons for withdrawals are not provided Attrition = 5% ITT analysis undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: IRCT201705035623N115 |
Control for confounding factors | Unclear risk | Pre‐treatment period: no intake of probiotic and/or synbiotic supplements within 3 months prior to study start Study period: not reported |
Other bias | Low risk | Conflicts declared: "The authors declare that they have no conflict of interest" Funding declared: "The present study was supported by a grant from the Vice‐chancellor for Research, KAUMS, and Iran. Special thanks to Gaz Sekkeh Company for providing probiotic and control honey." |
Meng 2019.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
Co‐interventions or additional treatments
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The patients were randomly divided into intervention group ... or control group ... by using computer‐generated 1:1 randomization sequences" |
Allocation concealment (selection bias) | High risk | Quote: "Delivery of the intervention and assessment of outcomes were not blinded to the treatment assignment" |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Quote: "Delivery of the intervention and assessment of outcomes were not blinded to the treatment assignment" Open‐label study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Quote: "Delivery of the intervention and assessment of outcomes were not blinded to the treatment assignment" Open‐label study |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 7% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: "During the 12‐week intervention, all patients with DN received low‐salt, low‐fat, and low‐protein dietary pattern and were given basic treatment such as glucose‐lowering, lipid‐lowering, and blood pressure–lowering treatment. But, patients were requested not to change their medicine and insulin treatment programs arbitrarily. All participants received dietary guidance from dietitians and completed 3‐day food records." |
Other bias | Low risk | Conflicts declared: "The authors declare that they have no relevant financial interests" Funding declared: "This work was supported by the Medical Health and Science Development Project of Shandong Province (grant number: 2016ws0428)" |
Miraghajani 2017.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control Group
Co‐interventions or additional treatments
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Patients ... were randomized (into) intervention arms using a simple random allocation sequence (www.randomization.com)" |
Allocation concealment (selection bias) | Low risk | Quote: "Concealed envelopes with consecutive numbers were locked up in a drawer and withdrawn in numerical order by the main author" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Patients and investigators, including those assessing outcomes and performing analyses, were masked to group assignment" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Patients and investigators, including those assessing outcomes and performing analyses, were masked to group assignment" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 17% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT02704884 |
Control for confounding factors | Low risk | Pre‐treatment period: 2‐week, single‐masked, run‐in period Study period: "All participants received individualized dietary counselling aimed at achieving a daily energy and restricting dietary protein, sodium, and potassium intake" |
Other bias | Low risk | Conflicts declared: "The authors declare that they have no conflict of interest" Funding declared: "The authors appreciate the financial support provided by the Research Council of the Food Security Research Center, Isfahan University of Medical Sciences, Isfahan, Iran" |
Miranda Alatriste 2014.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group 1
Intervention group 2
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "The present study is a ... simple randomized clinical trial" Insufficient details provided |
Allocation concealment (selection bias) | Low risk | Quote: "The size, color, flavor and physical aspects of the bottles were the same for both groups" |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Open‐label study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Open‐label study |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 3% ITT analysis not undertaken |
Selective reporting (reporting bias) | High risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: not reported |
Other bias | High risk | Conflicts declared: mot reported Funding declared: not reported |
Mirzaeian 2020.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group 1
Intervention group 2
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Patients were randomly allocated to block 1 or 2 with the use of stratified block randomization according to sex, age (± 5 years), and duration of HD (± 6 months)." |
Allocation concealment (selection bias) | Low risk | Quote: "The synbiotic and placebo capsules were identical in size, color, odor, and packaging." Quote: "Patients and investigators were blinded as to the arms of the study." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "To conduct the study in a double‐blinded nature, the placebo, containing maltodextrin, and synbiotic capsules were encoded as A and B, respectively, by a third person, and patients and investigators were blinded as to the arms of the study." |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "To conduct the study in a double‐blinded nature, the placebo, containing maltodextrin, and synbiotic capsules were encoded as A and B, respectively, by a third person, and patients and investigators were blinded as to the arms of the study." |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 13% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Unclear risk | Pre‐treatment period: "Before the start of the study, researchers introduced enriched dairy products with probiotics to all patients. All patients were asked not to consume foods such as yogurt, cheese, and kefir, which probably contain probiotic strains" Study period: not reported |
Other bias | High risk | Conflicts declared: not reported Funding declared: "The authors acknowledge the Zist Takhmir Company, Iran, for gifting the synbiotic supplements." |
Natarajan 2014.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Washout
Control group
Co‐interventions or additional treatments
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "Patient was examined, randomly assigned to either treatment or control group" |
Allocation concealment (selection bias) | Unclear risk | No information provided to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Study states to be double‐blind but no further information provided on how this was undertaken |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | No information provided to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 21% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT01450709 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: not reported |
Other bias | High risk | Conflicts declared: "The authors declare that they have no conflict of interests regarding the publication of this paper" Funding declared: "Kibow Biotech, Inc., a privately owned biotechnology company focused on probiotics, financed this clinical investigation at the Downstate Medical Center through 2009 Qualifying Therapeutic Discovery Project (QTDP) award, a US government special grant program to support promising and emerging technologies. Part of the data was also obtained in Kibow’s own fully equipped research laboratories" |
Pan 2021.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Eligible patients undergoing PD were randomized in a 1:1 ratio to one of two parallel groups (Randomization assignment was conducted using computer‐generated random numbers)" |
Allocation concealment (selection bias) | Unclear risk | Insufficient information provided to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Open‐label study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Open‐label study |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 16% ITT analysis not undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: "Medications known to affect the gut microbiome (such as proton pump inhibitor phosphate binders) were not used during the study" |
Other bias | High risk | Conflicts declared: "The authors declare that they have no relevant financial interests" Funding declared: "This study was not financially supported by any funding source"; "The probiotic supplements were produced by the Shanghai Xinyi pharmaceutical factory (S10950032, Shanghai, China)" Industry funding of intervention |
Poesen 2016.
Study characteristics | ||
Methods | Study design
Study duration
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Washout
Control Group
Co‐interventions or additional treatments
|
|
Outcomes | Outcomes reported by study at 4 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Randomization was performed by the sealed envelope system, in which the study nurse randomly opened a preformed envelope containing the allocated treatment regimen." |
Allocation concealment (selection bias) | Low risk | Quote: "Patients were randomized by the study nurse, blinded from both the investigator and study participant. Randomization was performed by the sealed envelope system, in which the study nurse randomly opened a preformed envelope containing the allocated treatment regimen. Patients were allocated to sequential treatment with AXOS and placebo, or vice versa, with a wash‐out period between both intervention periods. Quote: "Treatment with AXOS or placebo was offered to patients in identical vials and boxes. Each box was also labelled with a numerical code, unique to treatment allocation and again blinded from both the investigator and study participant, as an additional measure to allow review of the correct treatment allocation by the study nurse." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Treatment with AXOS or placebo was offered to patients in identical vials and boxes. Each box was also labelled with a numerical code, unique to treatment allocation and again blinded from both the investigator and study participant, as an additional measure to allow review of the correct treatment allocation by the study nurse." |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Quote: "... treatment allocation and again blinded from both the investigator and study participant, as an additional measure to allow review of the correct treatment allocation by the study nurse." |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided Attrition = 3% ITT analysis undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT02141815 |
Control for confounding factors | Unclear risk | Pre‐treatment period: use of antibiotics, prebiotics or probiotics in the past 4 weeks was not allowed Study period: not reported |
Other bias | High risk | Conflicts declared: "The authors have declared that no competing interests exist." Funding declared: "RP is the recipient of a Ph.D. fellowship of the Research Foundation ‐ Flanders (FWO) (grant 11E9813N) (www.fwo.be). Part of the research has been funded by the Research Foundation ‐ Flanders (FWO) (grant G077514N) (www.fwo.be). JAD and KV are jointly chair holders of the W.K. Kellogg Chair in Cereal Science and Nutrition at KU Leuven (www.wkkf.org). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." |
PREBIOTIC 2022.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 7 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Participants were randomly assigned in a 1:1 ratio to receive either prebiotic or placebo" Quote: "The randomization schedule was prepared by a researcher not involved with treatment allocation and involved stratification factors of age (,65 years, $65 years) and sex" |
Allocation concealment (selection bias) | Low risk | Quote: "The randomization schedule was prepared by a researcher not involved with treatment allocation and involved stratification factors of age (<65 years, >65 years) and sex" Quote: "A blinded allocation list was maintained in an Excel spreadsheet on a secure server in a folder not accessible to trial staff involved in recruitment" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "... a matched, identical placebo ... " Quote: "A blinded allocation list was maintained in an Excel spreadsheet on a secure server in a folder not accessible to trial staff involved in recruitment. Participants, caregivers, treating physicians and surgeons, laboratory staff, and members of the study team were blinded to the treatment." |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "A blinded allocation list was maintained in an Excel spreadsheet on a secure server in a folder not accessible to trial staff involved in recruitment. Participants, caregivers, treating physicians and surgeons, laboratory staff, and members of the study team were blinded to the treatment." |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 71% ITT analysis undertaken for originally randomized 56 High attrition rate but does not appear to be due to adverse effects of study treatment |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: ACTRN12618001057279 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: not reported |
Other bias | Low risk | Conflicts declared: "Samuel Chan is supported by the Australian National Health and Medical Research Council (NHMRC) Postgraduate Scholarship, the Microba recipient grant, the Metro South Research Support Scheme, and the Royal Australasian College of Physicians NHMRC Research Excellence top‐up award. Furthermore, Dr Chan is a current recipient of the 2018 Sir Gustav Nossal NHMRC Postgraduate Scholarship award. Carmel Hawley is the recipient of research grants paid to her institution from Baxter Healthcare and Fresenius Medical Care and from Otsuka, Janssen and GlaxoSmithKLline for trial steering committee activities, paid to her institution. David Johnson has received consultancy fees, research grants, speaker’s honoraria and travel sponsorships from Baxter Healthcare and Fresenius Medical Care. He has received consultancy fees from Astra Zeneca and travel sponsorships from Amgen. He is a current recipient of an Australian NHMRC Practitioner Fellowship. Nicole Isbel has received consultancy fees and speaker’s honoraria from Alexion Pharmaceuticals, Novo Nordisk and Amgen. The remaining authors have no conflicts of interest to declare with respect to the context and scope of this manuscript." Funding declared: "This study was funded by the Metro South Research Support Scheme Project Grant" |
ProbiotiCKD 2019.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 15 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Patients were randomized by a computer‐generated random number list to receive either placebo or probiotics" |
Allocation concealment (selection bias) | Low risk | Quote: "Placebo capsules were prepared ad hoc by a galenic local pharmacy to look exactly as probiotic capsules. Even placebo plastic containers looked exactly as those of probiotics." |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Open‐label study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Open‐label study |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for, no withdrawals Attrition = 0% ITT analysis undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Low risk | Pre‐treatment period: "To standardize baseline conditions, any prebiotic or probiotic supplement had to be suspended at least 1 month before enrolment"; "Enrolled subjects had to adhere to a protein dietary intake ranging 0.7–1 g/ kg/day, also assuring a daily consumption of two pieces of fruit (apple or pear) and 200 g of double‐boiled leafy green vegetables (the double boiling was used to discharge vegetables’ potassium content)" Study period: dietary recall |
Other bias | High risk | Conflicts declared: "The authors declare that they have no conflict of interest" Funding declared: "Probiotics were kindly provided by Bromatech Ltd, Viale Premuda, 46–20129 Milano" Industry funding |
Ramos 2019.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group 1
Intervention group 2
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Participants were randomly assigned to placebo or intervention group (blinded as A or B). The randomization was computer generated (ratio of 1:1, blocks of six) by an independent investigator, and stratified by gender and eGFR (from 45.0 to 22.5 mL/min/1.73 m²)." |
Allocation concealment (selection bias) | Low risk | Quote: "Both supplements were distributed in powdered form with the same texture and color, in identical sachets identified by the letters A and B, packaged off‐site by a food‐grade manufacturer (HileIndustria de Alimentos Ltda, Santa Catarina, Brazil) and labelled by an independent investigator." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Both supplements were distributed in powdered form with the same texture and color, in identical sachets identified by the letters A and B, packaged off‐site by a food‐grade manufacturer (HileIndstria de Alimentos Ltda, Santa Catarina, Brazil) and labelled by an independent investigator." |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information provided to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 8% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT02364869 |
Control for confounding factors | Low risk | Pre‐treatment period: no use of phosphate binders, immunosuppressants, antiinflammatories, antibiotics, laxatives, prebiotics, probiotics or synbiotics 3 months preceding baseline assessment Study period: "All participants had been previously advised by a renal dietitian to keep a diet composed by 0.6–0.8 g/kg/day of protein, 30–35 kcal/kg/day of energy, restricted in sodium and controlled in potassium if necessary. During the follow‐up, the participants were encouraged to maintain stable protein and fiber intake, and not to use laxatives, other prebiotics and/or probiotics." |
Other bias | Low risk | Conflicts declared: "None declared" Funding declared: "Conselho Nacional de Desenvolvimento Cientıfico e Tecnologico (CNPq, Brazil); Fundacao de Amparo a` Pesquisa do Estado de Sao Paulo (FAPESP, Brazil); Coordenacao de Aperfeicoamento de Pessoal de Nıvel Superior (CAPES, Brazil); Hospital do Rim–Fundacao Oswaldo Ramos (Sao Paulo, Brazil)" |
Ranganathan 2009.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Washout
Control group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Randomization sequence was generated by alternative patient sequential methodology" |
Allocation concealment (selection bias) | Unclear risk | Insufficient information provided to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The placebo was composed of wheat germ plus Psyllium husks. It was also matched in color, size and enteric coating identical to the interventional product" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information provided to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 19% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol |
Control for confounding factors | Unclear risk | Pre‐treatment period
Study period
|
Other bias | High risk | Conflicts declared
Funding declared
|
Shariaty 2017.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Convenience sampling and simple randomly allocation was used to designate the patients to intervention or control groups. The patients were randomly allocated to Groups A and B (n = 18 for each) using two sets of random numbers with codes 1 to 36 and were assigned probiotic capsules in one group and placebos in the other." |
Allocation concealment (selection bias) | Unclear risk | No information provided |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Quote: "The study was double blinded, so that neither the patients nor the evaluators had any information about either of the two groups. Indeed the participants did not know which groups they belonged to (probiotic or placebo group)" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Quote: "The study was double blinded, so that neither the patients nor the evaluators had any information about either of the two groups. Indeed the participants did not know which groups they belonged to (probiotic or placebo group)" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 6% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: Iranian Registry 2013072710325N2 |
Control for confounding factors | Unclear risk | Pre‐treatment period: not reported Study period: "Participants’ diet, levels of activity, and medications used did not change during the study and all the patients received the necessary training on these subjects"; "Both groups received daily folic acid supplements and monthly vitamin B12 supplements and received no other additional supplements" |
Other bias | Low risk | Conflicts declared: "There are no conflicts of interest" Funding declared: "This study was financed by Golestan Medical Sciences University. This study recorded and approved by the Iranian Registry of Clinical Trial Code: 2013072710325N2" |
Sirich 2014.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 6 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Permuted‐block randomization was utilized to assign patients to fibre or control starch" |
Allocation concealment (selection bias) | Unclear risk | No information provided |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Fiber and control supplements were provided as white powder in identical sachets" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | No information provided |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 29% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: ClinicalTrials.gov NCT0118627 |
Control for confounding factors | Unclear risk | Pre‐treatment period: participants must not have used antibiotics in the 4 weeks prior to starting study treatment Study period: not reported |
Other bias | High risk | Conflicts declared: "None." Funding declared: "Supplements were provided ... by Ingredion Incorporated (Bridgewater, NJ)" |
Soleimani 2017.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control Group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Randomization assignment was conducted using computer‐generated random numbers" |
Allocation concealment (selection bias) | Low risk | Quote: "Randomization and allocation were hidden from the researchers and patients until the final analyses were completed" Quote: "The randomized allocation sequence, enrolling participants and allocating them to interventions, was conducted by a trained nutritionist at the dialysis clinic" |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Randomization and allocation were hidden from the researchers and patients until the final analyses were completed" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided Attrition = 8% ITT undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: http://www.irct.ir: IRCT201601025623N69 |
Control for confounding factors | Low risk | Pre‐treatment period: "Taking probiotic supplements and other forms of probiotics (including probiotic yogurt, kefir, and other fermented foods), taking prebiotic, antioxidant, and/or anti‐inflammatory supplements (e.g., vitamin E, vitamin C, and omega‐3 fatty acids), or taking antibiotics and immunosuppressive medications within 3 months before enrolment in the study" Study period: "Patients were requested not to change their routine physical activity, and not to take any anti‐inflammatory medications and supplements that might affect their nutritional status during the 12‐week intervention" |
Other bias | High risk | Conflicts declared: "All the authors declared no competing interests" Funding declared: "Probiotic supplements were produced by Tak Gen Zist Pharmaceutical Company (Tehran, Iran)"; "The present study was supported by a grant from the Vice‐chancellor for Research, KUMS, and Iran" |
Soleimani 2019.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 12 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Participants were randomized using computer‐generated random numbers." |
Allocation concealment (selection bias) | Low risk | Quote: "Randomization and allocation were concealed from both researchers and patients until the completion of final analyses. The randomized allocation sequence, enrolling participants, and allocating them to interventions were conducted by a trained nutritionist in dialysis clinic." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "Randomization and allocation were concealed from both researchers and patients until the completion of final analyses." |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information to permit judgement |
Incomplete outcome data (attrition bias) All outcomes | Low risk | All participants were accounted for with reasons for withdrawals provided Attrition = 0% ITT analysis undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: http://www.irct.ir: IRCT2017090133941N17 |
Control for confounding factors | Low risk | Pre‐treatment period: No probiotic, synbiotic, antioxidant, anti‐inflammatory supplements 3 months prior to enrolment. Study period: "Patients were requested not to change their routine physical activity or usual diets throughout the study and not take any anti‐inflammatory and antioxidant medications or supplements during the 12‐week intervention which might affect the results of the study." |
Other bias | High risk | Conflicts declared: "The authors declare that they have no conflict of interest" Funding declared: "Synbiotic supplements and placebos (corn starch) were produced by Tak Gen Zist Pharmaceutical Company, Tehran, Iran"; "The research grant provided by Research Deputy of Kashan University of Medical Sciences (KAUMS)" |
SYNERGY 2014.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Washout
Control group
|
|
Outcomes | Outcomes reported by this study at 6 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Participants underwent ... randomization in a 1:1 ratio to either synbiotic supplements or placebo" Quote: "A computer–generated blocked randomization list with blocks of size 2 was produced" |
Allocation concealment (selection bias) | Low risk | Quote: "A computer–generated blocked randomization list with blocks of size 2 was produced by an external statistical consultant and maintained on a secure server not accessible to those recruiting for the trial. Random allocation was performed by telephoning the list custodian, who reported the next numbered supplement kit in the list. Supplement packaging was done offsite." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The synbiotic therapy (prebiotic powder and probiotic capsule) and the identically matched placebo (maltodextrin powder and capsule)" |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Insufficient information to permit judgement. |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 16% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: Australian New Zealand Clinical Trials Registry: ACTRN12613000493741 |
Control for confounding factors | Low risk | Pre‐treatment period: "Participants underwent a 2‐week run–in period followed by randomization"; "All participants underwent face‐to‐face dietary education and counselling with a qualified dietitian to achieve evidence–based guideline–recommended targets during the first week of run‐in" Study period: "Throughout the intervention, patients were encouraged to maintain stable dietary intakes, with a focus on stabilizing protein and fibre intake. Participants were also provided with a standard evening meal preceding their overnight fast before each blood collection." |
Other bias | Low risk | Conflicts declared: "None." Funding declared: "This study was funded through a project grant from the Princess Alexandra Private Practice Trust Fund (PPTF). M.R. is a recipient of the Princess Alexandra PPTF Postgraduate Scholarship. D.W.J. is supported by a Queensland Government Health and Medical Research (HMR) Health Research Fellowship. K.L.C. is supported by a Queensland Government HMR Health Research Fellowship and a Lions Senior Medical Research Fellowship." |
SYNERGY II 2021.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
|
|
Outcomes | Outcomes reported by this study at 3, 6, 9, 12 months
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "The randomization was completed by a computer‐generated random number (1:1 ratio, blocks of 4, stratified by CKD stage and presence of diabetes)" |
Allocation concealment (selection bias) | Unclear risk | Quote: "randomization ... was carried out by an independent investigator not involved in the recruitment or implementation of the study protocol" |
Blinding of participants and personnel (performance bias) All outcomes | Unclear risk | Quote: "a ... double‐blind ... trial" Comment: study states to be double‐blind but no detailed description of how these methods were undertaken |
Blinding of outcome assessment (detection bias) All outcomes | Unclear risk | Quote: "a ... double‐blind ... trial" Comment: study states to be double‐blind but no detailed description of how these methods were undertaken |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawal provided Attrition = 18% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or an a priori published protocol: ANZCTR (ACTRN12617000324314) All outcomes planned in the methods were reported in the results |
Control for confounding factors | Low risk | Quote: "Throughout the intervention, participants were provided individualized and tailored dietary advice in line with best practice guidelines and were encouraged to maintain a stable dietary intake, focusing on not altering protein and fiber intake." |
Other bias | Low risk | Conflicts declared: "The authors declare no conflict of interest." Funding declared: "This study was funded through project grants from the Princess Alexandra Research Foundation; Wishlist Research Grant Scheme, Study Education and Research Trust Fund, Sunshine Coast; and BEAT‐CKD via Australasian Kidney Trial Network." |
Viramontes‐Horner 2015.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Control group
Cointerventions
|
|
Outcomes | Outcomes reported by this study at 8 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "Patients were randomly allocated ..." Insufficient information to permit judgement |
Allocation concealment (selection bias) | Unclear risk | Insufficient information to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "The placebo had identical color, size, and flavor to the interventional product" |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Every month, tolerability and safety of the symbiotic gel were evaluated by direct interview by the same experienced dietician (D.V.H.), who was blinded to the intervention treatment" |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 17% ITT analysis not undertaken |
Selective reporting (reporting bias) | High risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Low risk | Pre‐treatment period: participants must not have been taking probiotics, omega‐3 fatty acids, pentoxifylline, immunosuppressants, nonsteroidal anti‐inflammatory drugs prior to start Study period: nutritional counselling provided as a co‐intervention throughout study to maintain similar and regular nutrient intakes |
Other bias | Low risk | Conflicts declared: "Special acknowledgment is made to chemists of Central Laboratory and nurses of the haemodialysis units for all the support given during the study. FMC works for Nutrimentos Inteligentes, S.A. de C.V. Nevertheless, her participation in the present study consisted in provide methodological and statistical advisory. During all her participation, she did her assigned activities completely blinded. Although D.V.H., BSc, started working for Nutrimentos Inteligentes, S.A. de C.V. after the conclusion of the study, during the fieldwork and the statistical analysis, she also did all her tasks totally blinded." Funding declared: "The present study was supported from CONACYT (Consejo Nacional de Ciencia y Tecnologıa) (supportive number: 174193) and Nutrimentos Inteligentes, S.A. de C.V." |
Wang 2015a.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group
Controlgroup
|
|
Outcomes | Outcomes reported by this study at 24 weeks
|
|
Notes | Baseline differences between groups
Publication type
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Low risk | Quote: "Patients were randomised into probiotic or control groups using a random‐number table sequence." |
Allocation concealment (selection bias) | Low risk | Quote: "Randomisation was performed using sequential numbers generated at the computer centre of China Medical University Hospital. The allocations were contained in opaque, sequentially numbered, sealed envelopes." |
Blinding of participants and personnel (performance bias) All outcomes | Low risk | Quote: "While the placebo group received similar capsules". Quote: "Both investigators and patients were blind as to the assignment." |
Blinding of outcome assessment (detection bias) All outcomes | Low risk | Quote: "Both investigators and patients were blind as to the assignment." |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were accounted for with reasons for withdrawals provided Attrition = 17% ITT analysis not undertaken |
Selective reporting (reporting bias) | Low risk | Trial registration or a priori published protocol: NCT01391468 |
Control for confounding factors | Low risk | Pre‐treatment period: No immunosuppressive agents or the consumption of antibiotics within 30 days prior to enrolment Study period: "Patients were advised not to change their dietary habit during the study period" |
Other bias | Low risk | Conflicts declared: "The authors state that they have no conflict of interest" Funding declared: "This study is supported in part by Taiwan Ministry of Health and Welfare Clinical Trial and Research Center of Excellence (MOHW103‐TDU‐B‐212‐113002), the research laboratory of pediatrics, Children’s Hospital of China Medical University, and China Medical University Hospital (grant numbers DMR‐101‐016 and DMR‐103‐013)" |
Xie 2015a.
Study characteristics | ||
Methods | Study design
Time frame
|
|
Participants | Study characteristics
Baseline characteristics
|
|
Interventions | Intervention group 1
Intervention group 2
Control Group
Co‐interventions
|
|
Outcomes | Outcomes reported by this study at 6 weeks
|
|
Notes | Baseline differences between groups
Publication type
Available data
|
|
Risk of bias | ||
Bias | Authors' judgement | Support for judgement |
Random sequence generation (selection bias) | Unclear risk | Quote: "This 6‐week randomized controlled trial was conducted" Insufficient information to permit judgement. |
Allocation concealment (selection bias) | Unclear risk | Insufficient information to permit judgement |
Blinding of participants and personnel (performance bias) All outcomes | High risk | Open‐label study |
Blinding of outcome assessment (detection bias) All outcomes | High risk | Open‐label study |
Incomplete outcome data (attrition bias) All outcomes | High risk | All participants were not accounted for, and completers or withdrawals were not reported Attrition = not reported ITT analysis unclear if undertaken |
Selective reporting (reporting bias) | Unclear risk | Trial registration or a priori published protocol: not reported |
Control for confounding factors | Low risk | Pre‐treatment period: "This study consisted of one week on regular diet to establish baseline dietary intake" Study period: Regular diet: "caloric intake 35 kcal/kg/bw, protein intake 1‐1.2 g/kg/bw, fats < 35%, and with sodium and potassium restriction" |
Other bias | Low risk | Conflicts declared: "None" Funding declared: "This study was supported by Shanghai Municipal Education Commission Scientific Research Fund (14ZZ043)" |
AIDs: acquired immunodeficiency disorder; APD: automated peritoneal dialysis; BMI: body mass index; BP: blood pressure; BW: body weight (in kilograms); BUN: blood urea nitrogen; CAPD: continuous ambulatory peritoneal dialysis; CaxP: calcium‐phosphorus product; CFU: colony forming units; CKD: chronic kidney disease; CrCl: creatinine clearance; CRP: C‐reactive protein; CVD: cardiovascular disease; DM: diabetes mellitus; eGFR: estimated glomerular filtration rate; EPO: erythropoietin; EQ‐5D: EuroQol‐5‐Dimension; FGID: functional gastrointestinal disorders; GI: gastrointestinal; Hb: haemoglobin; HbA1c: glycated Hb; GN: glomerulonephritis; GSRS: Gastrointestinal Symptom Rating Scale; HCY: haematocrit; HD: haemodialysis; HDL: high‐density lipoprotein; HIV: human immunodeficiency virus; HRQoL: health‐related quality of life; IFN: interferon; IQR: interquartile range; IL: interleukin; ITT; intention‐to‐treat; IV: intravenous; KDQoL: Kidney Disease Quality of Life; KRT: kidney replacement therapy; LDL: low‐density lipoprotein; M/F: males/females; MET: metabolic equivalent; MI: myocardial infarction; NGAL: neutrophil gelatinase‐associated lipocalin; PTH: parathyroid hormone; RCT: randomised controlled trial; SCr: serum creatinine; SD: standard deviation; SEM: standard error of the mean; SF: short‐form; SGA: subjective global assessment; TGF: transforming growth factor; TNF: tumour necrosis factor; UACR: urinary albumin‐creatinine ratio; VLDL: very low density lipoprotein
Characteristics of excluded studies [ordered by study ID]
Study | Reason for exclusion |
---|---|
Afaghi 2016 | Wrong intervention: the intervention is multi‐vitamin and multi‐mineral powder that contains 2 probiotics and 1 prebiotic, but these are not the majority of the dose, and there are too many other ingredients to be able to ascertain any effect.
Group A: ISOWHEY oral nutritional supplement Whey protein concentrate (whey protein, soy lecithin), Litesse® (polydextrose), xylitol, maltodextrin, medium chain triglycerides, calcium carbonate (calcium), cream flavour, vanilla flavour, whey protein isolate, magnesium oxide heavy (magnesium), potassium citrate (potassium), glutamine, xanthan gum, seagreens (Ascophyllum nodosum seaweed), enzyme mix, ascorbic acid (vitamin C), ferrous fumarate (iron), Lactobacillus acidophilus, chromium picolinate (chromium), zinc oxide (zinc), d‐alpha tocopheryl succinate (vitamin E), nicotinamide (vitamin B3), potassium iodide (iodine), manganese sulfate monohydrate (manganese), vitamin A acetate (vitamin A), Bifidobacterium lactis, biotin, cupric sulfate pentahydrate (copper), folic acid (vitamin B9), selenomethionine (selenium), pyridoxine hydrochloride (vitamin B6), calcium d‐pantothenate (vitamin B5), riboflavin (vitamin B2), thiamine hydrochloride (vitamin B1), cholecalciferol (vitamin D3), cyanocobalamin (vitamin B12), sodium. Contains milk and soy. Group B: BCAA (branded‐chain amino acid) oral nutritional supplement BCAA (L‐Leucine, L‐Isoleucine, L‐Valine), Citrulline Malate, L‐Glutamine, Minerals (Magnesium Phosphate, Calcium Phosphate, Sodium Chloride, Potassium Chloride), Flavour, Citric Acid, Sucralose, Vitamins (Calcium Ascorbate, Vitamin B6, Vitamin B12), Colour (Beta Carotene or Anthocyanins) Group C: routine diet without any supplements |
Cruz‐Mora 2014 | Wrong intervention: blended with nutritional counselling, albeit in both groups; however, nutritional counselling directly related to diet and too similar to taking dietary supplement probiotics, so it wouldn't be possible to ascertain what has an effect |
Eguchi 2011 | Wrong population: liver transplantation |
Ferrara 2009 | Wrong population: girls with recurrent UTI, not CKD population |
Firouzi 2015a | Wrong population: type 2 diabetes "Exclusion criteria include subjects who … have any acute or chronic disease other than diabetes, hyperlipidemia, and hypertension." |
Fitschen 2015 | Wrong intervention: not pre or probiotics |
Fortes 2020 | Wrong population: not CKD |
Grat 2017 | Wrong population: liver transplantation |
Hassan 2017 | Wrong intervention: not a prebiotic or probiotic treatment |
Jiang 2021a | Wrong population: not entirely CKD study population |
Lin 2021 | Wrong intervention: Chinese Herbal Medicine |
Orr 2016 | Wrong population: liver transplantation |
Pavan 2016 | Wrong study design and intervention: quasi‐observational study with mixed controls |
PrePro 2018 | Wrong population: liver transplantation |
ProLow CKD 2022 | Wrong intervention: the primary intervention is a low‐protein diet compared to no‐protein control diet. Probiotics and prebiotics are mixed into these treatment arms, however there are too many variables and interventions to be able to ascertain a causal pathway for efficacy. |
Rayes 2002 | Wrong population: liver transplantation |
Rayes 2002a | Wrong population: post‐op major abdominal surgery |
Rayes 2005 | Wrong population: liver transplantation |
Saxena 2022 | Wrong intervention: not including enzobiotics |
Tayebi‐Khosroshahi 2016 | Wrong intervention: not synbiotic, prebiotic or probiotic intervention treatment |
Wang 2018e | Wrong intervention: not pre or probiotics |
CKD: chronic kidney disease; RCT: randomised controlled trial; UTI: urinary tract infection
Characteristics of studies awaiting classification [ordered by study ID]
Chen 2019b.
Methods | |
Participants | |
Interventions | |
Outcomes | |
Notes | Publication type
Trial registration details
|
Mady 2018.
Methods | Study design
Study duration
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Outcomes reported
|
Notes | Publication type
Trial registration details
|
Marks 2010.
Methods | Study design
Time frame
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Outcomes reported
|
Notes | Publication type
Trial registration details
Attrition Notes
Baseline differences between groups
|
Ogawa 2020.
Methods | Study design
Time frame
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Outcomes reported
|
Notes | Publication type
Trial registration details
|
Prado 2020.
Methods | |
Participants | |
Interventions | |
Outcomes | |
Notes | Publication type
Trial registration details
|
Ranganathan 2019a.
Methods | |
Participants | |
Interventions | |
Outcomes | |
Notes | Publication type
Trial registration details
|
Soliman 2018.
Methods | |
Participants | |
Interventions | |
Outcomes | |
Notes | Publication type
Trial registration details
|
Takayama 2003.
Methods | Study design
Study duration
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Outcomes reported
|
Notes | Publication type
Trial registration details
|
TCTR20220317007.
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Notes | Abstract‐only publication Funding: not reported |
Wu 2012.
Methods | |
Participants | |
Interventions | |
Outcomes | |
Notes | Publication type
Trial registration details
|
Younes 2006.
Methods | Study design
Time frame
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Outcomes reported
|
Notes | Publication type
Trial registration details
|
Zhang 2019a.
Methods | |
Participants | |
Interventions | |
Outcomes | |
Notes | Publication type
Trial registration details
|
CFU: colony‐forming units; CKD: chronic kidney disease; CRP: C‐reactive protein; HD: haemodialysis; RCT: randomised controlled trial
Characteristics of ongoing studies [ordered by study ID]
ChiCTR2200061930.
Study name | Effects of non‐protein energy supplements and exercise on protein‐energy wasting and gut microbes in maintenance hemodialysis patients |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Group 1
Group 2
Group 3
|
Outcomes | Planned outcomes
|
Starting date | Date of first enrolment: 1 August 2022 |
Contact information | Chunrong Tang 18 Zhongshan 2nd Road, Baise, Guangxi +86 18778676788 yyfyxt@163.com Affiliated Hospital of Youjiang Medical University for Nationalities |
Notes | Funding: Foundation for High‐level Talents of Affiliated Hospital of Youjiang Medical University for Nationalities (No. R202011705) |
ChiCTR2200064821.
Study name | Clinical effect and mechanism of modified Shenling Baizhu powder on peritoneal dialysis |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Date of first enrolment: 1 November 2022 |
Contact information | Luan Min 1 Qianjiang Road, Xinzhan District, Hefei, Anhui +86 18040010378 1782406861@qq.com Anhui University of Chinese Medicine |
Notes | Funding: Key Project of Natural Science Research in Anhui Universities |
ChiCTR2300070381.
Study name | Effects of dietary fiber‐added diets on protein‐binding toxoids and microinflammatory states in patients with chronic kidney disease |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | First enrolment: 1 November 2018 |
Contact information | Yao Xu 453 Stadium Road, West Lake District, Hangzhou City, Zhejiang Province 13018868203 1002591331@qq.com Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University |
Notes | Funding: Medical Scientific Research Foundation of All appendix sections must Zhejiang province |
ChiCTR2300072339.
Study name | Probiotics improve immune metabolism in maintenance hemodialysis patients by regulating intestinal flora |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
Healthy control group
|
Outcomes | Planned outcomes
|
Starting date | First enrolment: 18 October 2022 |
Contact information | Yan Lv No. 99, Longcheng street, Taiyuan, Shanxi Province +86 138 3414 8662 lvyanrcx@126.com Shanxi Bethune hospital,Shanxi Academy of Medical Sciences |
Notes | Funding: Four “Batches” Innovation Project of Invigorating Medical through Science and Technology ofShanxi Province |
CTRI/2022/02/040296.
Study name | A study to assess the effect of probiotic in prevention of progression of kidney disease in patients with chronic kidney disease |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Planned date: 18 February 2022 |
Contact information | Dr C Prabhakar Reddy Clinical Pharmacology and Therapeutics NIMS Punjagutta Hyderabad Punjagutta Hyderabad 500082 500082 Mahbubnagar, TELANGANA India 7416512888 cptnims@gmail.com Nizams Institute of Medical Sciences |
Notes | Funding: Nizams Institute of Medical Sciencess for infrastructure support |
CTRI/2022/11/047767.
Study name | Global phase 2 clinical trial to evaluate safety and efficacy of US‐APR2020 in subjects with chronic kidney disease stage IV |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Planned first enrolment: 30 November 2022 |
Contact information | Mr Rajendra M Sawant 5th and 6th floor, B‐wing, Centaur House, Near Hotel Grand Hyatt, Santacruz East, Mumbai 400055, India 400055 Mumbai (Suburban), MAHARASHTRA India 91‐22‐66499154 drzarapkar@lifesan.in LifeSan Clinical Research, division of Centaur Pharmaceuticals Pvt. Ltd. |
Notes | Funding: Kibow Biotech, Inc 4781 West Chester Pike, Newtown Square, PA 19073, USA Tel: 888‐271‐2560 Email: info@kibowbiotech.com; CRO LifeSan Clinical Research a division of Centaur Pharmaceuticals Pvt Ltd |
Ghoreishy 2022.
Study name | Effect of daily consumption of probiotic yoghurt on albumin to creatinine ratio, eGFR and metabolic parameters in patients with type 2 diabetes with microalbuminuria: study protocol for a randomised controlled clinical trial |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | 11 November 2021 |
Contact information | Dr Ahmad Esmaillzadeh Email: a‐esmaillzadeh@tums.ac.ir |
Notes | Trial registration or a priori published protocol
Publication type
Available data
|
Headley 2020.
Study name | The effects of 16‐weeks of prebiotic supplementation and aerobic exercise training on inflammatory markers, oxidative stress, uraemic toxins, and the microbiota in pre‐dialysis kidney patients: a randomized controlled trial‐protocol paper |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group 1
Intervention group 2
Intervention group 3
Control group
Time: 16 weeks |
Outcomes | Planned outcomes
|
Starting date | September 2018 (ongoing) |
Contact information | Samuel A Headley, PhD Springfield College, USA |
Notes | Trial registration or a priori published protocol
Publication type
Available data
|
IRCT20100223003408N5.
Study name | Effect of synbiotic dessert fortified with vitamin D and calcium on nutritional indices, inflammation, oxidative stress, malnutrition and quality of life in hemodialysis patients |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date
Other dates
|
Contact information | Maryam Ekramzadeh Shiraz University of Medical Sciences, Nutrition Department Iran (Islamic Republic of) +98 917 317 3891 ekramzadeh@sums.ac.ir |
Notes | IRCT registration number: IRCT20100223003408N5 Status: recruitment complete |
IRCT20131013014994N7.
Study name | The effect of synbiotic supplementation on plasma levels of Advanced Glycation End Products and cardiovascular risk factors in hemodialysis patients: a double‐blind clinical trial |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group 1
Control group 2
|
Outcomes | Planned outcomes
|
Starting date | Date of enrolment: 22 May 2022 |
Contact information | Hadi Abdollahzad Isaar Square, Faculty of Nutrition Sciences and Food Industry 6719851552 kermanshah Iran (Islamic Republic of) +98 83 3710 2008 abdollahzad@kums.ac.ir Kermanshah University of Medical Sciences |
Notes | Funding: Kermanshah University of Medical Sciences |
IRCT20160206026390N11.
Study name | Evaluation of the efficacy of probiotic supplementation on bio‐markers of inflammation and oxidative stress in paediatric patients under treatment with haemodialysis: randomized double blind clinical trial |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date
Other dates
|
Contact information | Ehsan Ghaedi Ahwaz Jundishapoor, University of Medical Sciences Iran (Islamic Republic of) +98 61 3374 3285 ghaedi.e@ajums.ac.ir |
Notes | Funding: Mashhad University of Medical Sciences IRCT registration number: IRCT20160206026390N11 |
IRCT20230608058421N1.
Study name | The effect of probiotics on patients with end‐stage renal failure |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Date of 1st enrolment: 23 August 2023 |
Contact information | Melika Gholizadeh South Kargar 1333635445 Tehran Iran (Islamic Republic of) +98 21 5541 9005 Melika_g1368@yahoo.com Shahid Beheshti University of Medical Science |
Notes | Funding: Shahid Beheshti University of Medical Sciences |
KCT0007834.
Study name | The effect of carboneceous oral adsorbent and synbiotics on the gut microbiome and muscle health in chronic kidney disease patients |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group 1
Intervention group 2
Control group
Co‐interventions
|
Outcomes | Planned outcomes
|
Starting date | Planned date of first enrolment: 2 January 2023 |
Contact information | Chun Soo Lim 20, Boramae‐ro 5‐gil, Dongjak‐gu +82‐2‐870‐2215 cslimjy@snu.ac.kr Seoul Metropolitan Government Seoul National University Boramae Medical Center |
Notes | Funding: HK inno.N |
Mitrovic 2023.
Study name | The impact of synbiotic treatment on the levels of gut‐derived uraemic toxins, inflammation, and gut microbiome of chronic kidney disease patients‐ A randomized trial |
Methods | Study design
Time frame
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Outcomes reported by this study at 12 weeks
|
Starting date | Unpublished manuscript
|
Contact information | Corresponding author: Miloš Mitrović Address: Dunavski Kej 13 11000 Belgrade Telephone: +381637603510 E‐mail: dr.milosh.mitrovic@gmail.com |
Notes | Publication type
Funding
|
NCT03770611.
Study name | Effect of prebiotics and/or probiotics on uremic toxins and inflammation markers in peritoneal dialysis patients |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group 1
Intervention group 2
Intervention group 3
Control group
|
Outcomes | Planned outcomes
|
Starting date | Planned starting date
Other dates
|
Contact information | Alfonso Martín Cueto Manzano Unidad de Investigacion Medica en Enfermedades Renales +52 (33) 38097269 a_cueto_manzano@hotmail.com Fabiola Martín‐del‐Campo, MSc +52 (33) 10711190 fabi_mc@hotmail.com |
Notes | Funding: Unidad de Investigacion Medica en Enfermedades Renales |
NCT03789708.
Study name | Effects of gum arabic supplementation in hemodialysis patients |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group 1
Intervention group 2
Intervention group 3
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date
Other dates
|
Contact information | Sarra Elamin, MD Consultant Nephrologist University of Khartoum |
Notes | Funding: University of Khartoum |
NCT03924089.
Study name | Oral nutritional supplement on nutritional and functional status, and biomarkers in malnourished hemodialysis patients (RENACARE) |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group 1
Intervention group 2
Control group
|
Outcomes | Planned outcomes
|
Starting date | Start date
Other dates
|
Contact information | Gabriel Olveira, MD, PhD Instituto de Investigación biomédica de Málaga 0034951290343 gabrielm.olveira.sspa@juntadeandalucia.es |
Notes | Funding: Fundación Pública Andaluza para la Investigación de Málaga en Biomedicina y Salud |
NCT05183737.
Study name | Effects of microencapsulated propolis and turmeric in patients with chronic kidney disease |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date: 7 March 2022 |
Contact information | Denise Mafra, PhD Universidade Federal Fluminense |
Notes | Funding: Universidade Federal Fluminense |
NCT05336305.
Study name | Polydextrose for patients with chronic kidney disease |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date: 30 March 2021 |
Contact information | Denise Mafra, Universidade Federal Fluminense |
Notes | Funding: Universidade Federal Fluminense |
NCT05359094.
Study name | Probiotic supplements in chronic kidney disease |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date: 1 June 2022 |
Contact information | Cheng‐Hsu Chen, MDPHD Division of Nephrology in Taichung Veterans General Hospital |
Notes | Funding: Taichung Veterans General Hospital |
NCT05540431.
Study name | Evaluation of protective effect of activated charcoal and probiotic against progression of chronic kidney disease |
Methods | Study design
|
Participants | Study design
|
Interventions | Intervention group 1
Intervention group 2
Control group
|
Outcomes | Planned outcomes
|
Starting date | Planned starting date: 20 September 2023 |
Contact information | Waleed Khaild Rahman Kareem Al‐kabi, Kufa University |
Notes | Funding: not reported |
NCT05674981.
Study name | To evaluate the beneficial effect of probiotics on DKD patients and the role of gut microbiota modulation |
Methods | Study design
|
Participants | Study design
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date: 24 April 2023 |
Contact information | Yi‐Sun Yang, PhD Chung Shan Medical University |
Notes | Funding: GenMont Biotech Incorporation |
NCT05724511.
Study name | The effect of probiotics on depression syndrome and risk factors of cardiovascular disease in hemodialysis patients |
Methods | Study design
|
Participants | Study design
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Starting date: 27 February 2023 |
Contact information | Pei‐Yu Wu China Medical University Hospital |
Notes | Funding: China Medical University Hospital |
NCT05835648.
Study name | Effect of dietary fiber on non‐dialysis patients with chronic kidney disease |
Methods | Study design
|
Participants | Study characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Planned starting date: 30 April 2023 |
Contact information | Zunsong Wang Qianfoshan Hospital |
Notes | Funding: not reported |
RBR‐3WRNF.
Study name | Effect of fibers on intestinal transit and inflammation of patients with pre‐dialytic chronic renal disease |
Methods | Study design
Time frame
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | Unclear |
Contact information | Marina Nogueira Berbel Bufarah Address: Rua Paulo Bruder, 412 Residencial Parque Laguna 2City: Botucatu / Brazil Zip code: 18615‐412 Phone: +55‐14‐997402119 Email: mnberbel@fmb.unesp.br Affiliation: Faculdade de Medicina de Botucatu ‐ Unesp |
Notes | Trial registration
Funding
|
ReSPECKD 2022.
Study name | A randomized double‐blind cross‐over trial to study the effects of resistant starch prebiotic in chronic kidney disease (ReSPECKD) |
Methods | Study design
Study duration
|
Participants | Study characteristics
Baseline characteristics
|
Interventions | Intervention group
Control group
|
Outcomes | Planned outcomes
|
Starting date | September 2021 |
Contact information | Dylan Mackay Email: dylan.mackay@umanitoba.ca Address: Department of Human Nutritional Sciences, University of Manitoba, Winnipeg, MB, Canada |
Notes | Publication type
|
ACR: albumin to creatinine ratio; AIDS: Acquired Immunodeficiency Syndrome; AKI: acute kidney injury; APD: automated peritoneal dialysis; BMI: body mass index; BP: blood pressure; BUN: blood urea nitrogen; CKD: chronic kidney disease; CRP: C‐reactive protein; CVD: cardiovascular disease; DM: diabetes mellitus; eGFR: estimated glomerular filtration rate; EPO: erythropoietin; GI: gastrointestinal; GN: glomerulonephritis; GSRC: gastrointestinal symptom rating scale; HADS: Hospital Anxiety and Depression Scale; Hb: haemoglobin; HbA1C: haemoglobin A1; HDL: high‐density lipoprotein; IL: interleukin; LDL: low‐density lipoprotein; M/F: males/females; KT/V: dialyser clearance time/volume; MI: myocardial infarction; QoL: quality of life; RCT: randomised controlled trial; SCr: serum creatinine; SD: standard deviation; TNF: tumor‐necrosis factor; VLDL: very low density lipoprotein
Differences between protocol and review
Abstracts were not eligible studies in this review due to not being peer reviewed and a lack of available detail to assess quality.
Contributions of authors
Draft the protocol: TC, RK, JC, CH, MH, DJ, ATP, AT, GW
Study selection: TC, RK
Extract data from studies: TC, RK
Enter data into RevMan: TC, RK
Carry out the analysis: TC, RK, ATP
Interpret the analysis: TC, RK, ATP
Draft the final review: TC, RK, SC, JC, CH, MH, DJ, ATP, AT, GW
Disagreement resolution: SC
Update the review: TC
Sources of support
Internal sources
No sources of support provided
External sources
-
BEAT‐CKD Funding Grant 1092957, Australia
TC and RK are employed under funding from this grant.
Declarations of interest
TC: none known
RK: none known
SC: none known
JC: none known
Carmel Hawley has received fees paid to her institution from Janssen and GlaxoSmithKline; Advisory Board fees paid to her from Otsuka; Research Grants to her institution from Otsuka, Shire, Fresenius, and Baxter; none of these are related to the current study. In addition, she has received grants paid to her institution from the Polycystic Kidney Disease foundation of Australia and from Otsuka for work that is related to the current study
MH: none known
David Johnson has received consultancy fees, research grants, speaker's honoraria and travel sponsorships from Baxter Healthcare and Fresenius Medical Care. He has received consultancy fees from AstraZeneca and AWAK, and travel sponsorships from Amgen
ATP: none known
AT: none known
GW: none known
New
References
References to studies included in this review
Abbasi 2017 {published data only}
- Abbasi B, Ghiasvand R, Mirlohi M. Kidney function improvement by soy milk containing lactobacillus plantarum A7 in type 2 diabetic patients with nephropathy: a double-blinded randomized controlled trial. Iranian Journal of Kidney Diseases 2017;11(1):36-43. [MEDLINE: ] [PubMed] [Google Scholar]
- Abbasi B, Mirlohi M, Daniali M, Ghiasvand R. Effects of probiotic soy milk on lipid panel in type 2 diabetic patients with nephropathy: a double-blind randomized clinical trial. Progress in Nutrition 2018;20:70-8. [EMBASE: 2001649336] [Google Scholar]
Biruete 2017 {published data only}
- Biruete A, Cross TL, Allen JM, Kistler BM, Loor H, Evenepoel P, et al. Effect of dietary inulin supplementation on the gut microbiota composition and derived metabolites of individuals undergoing hemodialysis: a pilot study. Journal of Renal Nutrition 2021;31(5):512-22. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Biruete A, Kistler B, Allen J, Bauer L, Fahey G, Swanson K, et al. Effect of inulin supplementation on mineral metabolism and short-chain fatty acid excretion in hemodialysis patients [abstract no: MP434]. Nephrology Dialysis Transplantation 2017;32(Suppl 3):iii588-9. [EMBASE: 617289888] [Google Scholar]
Bliss 1992 {published data only}
- Bliss DZ, Stein TP, Schleifer CR, Settle RG. Supplementation with gum arabic fiber increases fecal nitrogen excretion and lowers serum urea nitrogen concentration in chronic renal failure patients consuming a low-protein diet. American Journal of Clinical Nutrition 1996;63(3):392-8. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Bliss DZ. Effect of a gum Arabic supplement on the nitrogen excretion and serum urea nitrogen concentration of chronic renal failure patients on a low protein diet [PhD thesis]. University of Pennsylvania 1992:1-206. [CINAHL: 109870911]
Borges 2018 {published data only}
- Borges NA, Carmo FL, Stockler-Pinto MB, Brito JS, Dolenga CJ, Ferreira DC, et al. Probiotic supplementation in chronic kidney disease: a double-blind, randomized, placebo-controlled trial. Journal of Renal Nutrition 2018;28(1):28-36. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Borges NA, Stenvinkel P, Bergman P, Qureshi AR, Lindholm B, Moraes C, et al. Effects of probiotic supplementation on trimethylamine-N-oxide plasma levels in hemodialysis patients: a pilot study. Probiotics & Antimicrobial Proteins 2019;11(2):648-54. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Mafra D, Borges NA, Moraes C, Stockler-Pinto MB, Bergman P, Stenvinkel P. Effects of probiotic supplementation on trimethylamine-N-oxide plasma levels in chronic kidney disease patients [abstract no: TH-PO764]. Journal of the American Society of Nephrology 2016;27(Abstract Suppl):270A. [EMBASE: 641135082] [Google Scholar]
- Mafra D, Borges NA, Nakau L, Dolenga C, Bergman P, Stenvinkel P. Effects of probiotic supplementation on uremic toxins levels in non-dialysis CKD patients [abstract no: MP431]. Nephrology Dialysis Transplantation 2017;32(Suppl 3):iii587-8. [EMBASE: 617289825] [Google Scholar]
- Mafra D, Borges NA, Stockler-Pinto MB, Fouque D, Barros AF. Does a probiotic supplementation alter the indoxyl sulfate levels in non-dialysis chronic kidney disease patients? A randomized placebo-controlled clinical trial [abstract no: FR-PO862]. Journal of the American Society of Nephrology 2015;26(Abstract Suppl):563A. [EMBASE: 641102246] [Google Scholar]
Cosola 2021 {published data only}
- Cosola C, Rocchetti MT, di Bari I, Acquaviva PM, Maranzano V, Corciulo S, et al. An innovative synbiotic formulation decreases free serum indoxyl sulfate, small intestine permeability and ameliorates gastrointestinal symptoms in a randomized pilot trial in stage IIIb-IV CKD patients. Toxins 2021;13(5):334. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
de Andrade 2021 {published data only}
- Andrade LS, Sarda FA, Pereira NB, Teixeira RR, Rodrigues SD, Lima JD, et al. Effect of unripe banana flour on gut-derived uremic toxins in individuals undergoing peritoneal dialysis: a randomized, double-blind, placebo-controlled, crossover trial. Nutrients 2021;13(2):646. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
de Araujo 2022 {published data only}
- De Araujo EM, Meneses GC, Martins AM, De Francesco Daher E, Da Silva Junior GB. Effect of probiotic supplementation on endothelial injury and inflammation biomarkers among patients with chronic kidney diseases on hemodialysis [abstract no: MO584]. Nephrology Dialysis Transplantation 2022;37(Suppl 3):i429. [DOI: 10.1093/ndt/gfac074.029] [DOI] [Google Scholar]
- Araujo EM, Meneses GC, Carioca AA, Martins AM, Daher EF, da Silva Junior GB. Use of probiotics in patients with chronic kidney disease on hemodialysis: a randomized clinical trial. Jornal Brasileiro de Nefrologia 2022;45(2):152-61. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Dehghani 2016 {published data only}
- Dehghani H, Heidari F, Mozaffari-Khosravi H, Nouri-Majelan N, Dehghani A. Synbiotic supplementations for azotemia in patients with chronic kidney disease: a randomized controlled trial. Iranian Journal of Kidney Diseases 2016;10(6):351-7. [MEDLINE: ] [PubMed] [Google Scholar]
Ebrahim 2022 {published data only}
- Ebrahim Z, Proost S, Tito RY, Raes J, Glorieux G, Moosa MR, et al. The effect of s-glucan prebiotic on kidney function, uremic toxins and gut microbiome in stage 3 to 5 chronic kidney disease (CKD) predialysis participants: a randomized controlled trial. Nutrients 2022;14(4):805. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Eidi 2018 {published data only}
- Eidi F, Poor-Reza GF, Ostadrahimi A, Dalili N, Samadian F, Barzegari A. Effect of Lactobacillus rhamnosus on serum uremic toxins (phenol and P-cresol) in hemodialysis patients: A double blind randomized clinical trial. Clinical Nutrition ESPEN 2018;28:158-64. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Gholi FP, Dalili N, Eidi F, Ostadrahimi A. Effect of lactobacillus rhamnosus on serum uremic toxins in hemodialysis patients [abstract no: SP705]. Nephrology Dialysis Transplantation 2017;32(Suppl 3):iii375. [EMBASE: 617290088] [Google Scholar]
Elamin 2017 {published data only}
- Elamin S, Alkhawaja MJ, Bukhamsin AY, Idris MA, Abdelrahman MM, Abutaleb NK, et al. Gum Arabic reduces C-reactive protein in chronic kidney disease patients without affecting urea or indoxyl sulfate levels. International Journal of Nephrology 2017;2017:9501470. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Esgalhado 2018 {published data only}
- Azevedo R, Esgalhado M, Kemp JA, Regis B, Cardozo LF, Nakao LS, et al. Resistant starch supplementation effects on plasma indole 3-acetic acid and aryl hydrocarbon receptor mRNA expression in hemodialysis patients: Randomized, double blind and controlled clinical trial [Efeitos da suplementacao de amido resistente no acido indol-3-acetico plasmatico e na expressao do mRNA do receptor aril-hidrocarboneto em pacientesemhemodialise:ensaioclinicorandomizado,duplo-cegoecontrolado]. Jornal Brasileiro de Nefrologia 2020;42(3):273-9. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Esgalhado M, Kemp JA, Azevedo R, Paiva BR, Stockler-Pinto MB, Dolenga CJ, et al. Could resistant starch supplementation improve inflammatory and oxidative stress biomarkers and uremic toxins levels in hemodialysis patients? A pilot randomized controlled trial. Food & Function 2018;9(12):6508-16. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Esgalhado M, Kemp JA, Paiva BR, Brito JS, Cardozo LF, Azevedo R, et al. Resistant starch type-2 enriched cookies modulate uremic toxins and inflammation in hemodialysis patients: a randomized, double-blind, crossover and placebo-controlled trial. Food & Function 2020;11(3):2617-25. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Kemp JA, Dos Santos HF, Jesus HE, Esgalhado M, Paiva BR, Azevedo R, et al. Resistant starch type-2 supplementation does not decrease trimethylamine n-oxide (TMAO) plasma level in hemodialysis patients. Journal of the American Nutrition Association 2022;41(8):788-95. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Kemp JA, Regis de Paiva B, Fragoso Dos Santos H, Emiliano de Jesus H, Craven H, Z Ijaz U, et al. The impact of enriched resistant starch type-2 cookies on the gut microbiome in hemodialysis patients: a randomized controlled trial. Molecular Nutrition & Food Research 2021;65(19):e2100374. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Mafra D, Ann Kemp J, Esgalhado M, Paiva B, De Jesus HE, Santos HF. Effects of resistant starch (RS) type 2 cookies on gut microbiota profile in hemodialysis (HD) patients [abstract no: PO2051]. Journal of the American Society of Nephrology 2020;31(Abstract Suppl):629-30. [EMBASE: 633701738] [Google Scholar]
- Mafra D, Ann Kemp J, Santos HF, De Jesus HE, Esgalhado M, Paiva B, et al. High-amylose resistant starch (RS) cookies supplementation does not decrease trimethylamine n-oxide (TMAO) plasma level in hemodialysis (HD) patients [abstract no: PO2039]. Journal of the American Society of Nephrology 2020;31(Abstract Suppl):626-7. [EMBASE: 633701431] [Google Scholar]
- Mafra D, Esgalhado M, Macedo RD, Kemp J, Paiva B, Nakao LS, et al. Resistant starch supplementation reduces indoxyl sulfate levels in hemodialysis patients: a randomized, double-blind, crossover, placebo-controlled study [abstract no: FR-OR127]. Journal of the American Society of Nephrology 2018;29(Abstract Suppl):72. [EMBASE: 633737357] [Google Scholar]
- Mafra D, Esgalhado M, Stockler-Pinto MB, Borges NA, Cardozo LF, Paiva B, et al. Effects of resistant starch supplementation on inflammatory and oxidative stress status in hemodialysis patients: a pilot randomized, double-blind, placebo-controlled clinical trial [abstract no: SA-PO149]. Journal of the American Society of Nephrology 2017;28(Abstract Suppl):716. [EMBASE: 633701761] [Google Scholar]
- Mafra D, Macedo RD, Cardozo LF, Borges NA, Nakao LS, Jardim MZ, et al. Effect of resistant starch supplementation on the indole-3-acetic acid levels and aryl hydrocarbon receptor expression in hemodialysis patients [abstract no: FR-PO545]. Journal of the American Society of Nephrology 2018;29(Abstract Suppl):561. [EMBASE: 633736002] [Google Scholar]
- Mafra D, Paiva B, Esgalhado M, Borges NA, Kemp JA, Cardozo LF, et al. Resistant starch supplementation attenuates inflammation in hemodialysis patients [abstract no: SA-PO818]. Journal of the American Society of Nephrology 2019;30(Abstract Suppl):974. [EMBASE: 633769632] [Google Scholar]
- Paiva BR, Esgalhado M, Borges NA, Kemp JA, Alves G, Leite PE, et al. Resistant starch supplementation attenuates inflammation in hemodialysis patients: a pilot study. International Urology & Nephrology 2020;52(3):549-55. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Guida 2014 {published data only}
- Guida B, Germano R, Trio R, Russo D, Memoli B, Grumetto L, et al. Effect of short-term synbiotic treatment on plasma p-cresol levels in patients with chronic renal failure: a randomized clinical trial. Nutrition Metabolism & Cardiovascular Diseases 2014;24(9):1043-9. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Guida 2017 {published data only}
- Guida B, Cataldi M, Memoli A, Trio R, di Maro M, Grumetto L, et al. Effect of a short-course treatment with synbiotics on plasma p-cresol concentration in kidney transplant recipients. Journal of the American College of Nutrition 2017;36(7):586-91. [PMID: ] [DOI] [PubMed] [Google Scholar]
Haghighat 2019 {published data only}
- Haghighat N, Mohammadshahi M, Shayanpour S, Haghighizadeh MH, Rahmdel S, Rajaei M. The effect of synbiotic and probiotic supplementation on mental health parameters in patients undergoing hemodialysis: A double-blind, randomized, placebo-controlled trial. Indian Journal of Nephrology 2021;31(2):149-56. [EMBASE: 634933481] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Haghighat N, Mohammadshahi M, Shayanpour S, Haghighizadeh MH. Effect of synbiotic and probiotic supplementation on serum levels of endothelial cell adhesion molecules in hemodialysis patients: a randomized control study. Probiotics & Antimicrobial Proteins 2019;11(4):1210-8. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Haghighat N, Mohammadshahi M, Shayanpour S, Haghighizadeh MH. Effects of synbiotics and probiotics supplementation on serum levels of endotoxin, heat shock protein 70 antibodies and inflammatory markers in hemodialysis patients: a randomized double-blinded controlled trial. Probiotics & Antimicrobial Proteins 2020;12(1):144-51. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Haghighat N, Rajabi S, Mohammadshahi M. Effect of synbiotic and probiotic supplementation on serum brain-derived neurotrophic factor level, depression and anxiety symptoms in hemodialysis patients: a randomized, double-blinded, clinical trial. Nutritional Neuroscience 2019;24(6):490-9. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Haghighat N, Rajabi S, Mohammadshahi M. Effect of synbiotic and probiotic supplementation on serum brain-derived neurotrophic factor level, depression and anxiety symptoms in hemodialysis patients: a randomized, double-blinded, clinical trial. Nutritional Neuroscience 2021;24(6):490-9. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Haghighat 2019 (second comparison) {published data only}
He 2022 {published data only}
- He S, Xiong Q, Tian C, Li L, Zhao J, Lin X, et al. Inulin-type prebiotics reduce serum uric acid levels via gut microbiota modulation: a randomized, controlled crossover trial in peritoneal dialysis patients. European Journal of Nutrition 2022;61(2):665-77. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Khosroshahi 2018 {published data only}
- Khosroshahi HT, Abedi B, Ghojazadeh M, Samadi A, Jouyban A. Effects of fermentable high fiber diet supplementation on gut derived and conventional nitrogenous product in patients on maintenance hemodialysis: a randomized controlled trial. Nutrition & Metabolism 2019;16:18. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Laffin MR, Tayebi Khosroshahi H, Park H, Laffin LJ, Madsen K, Kafil HS, et al. Amylose resistant starch (HAM-RS2) supplementation increases the proportion of Faecalibacterium bacteria in end-stage renal disease patients: microbial analysis from a randomized placebo-controlled trial. Hemodialysis International 2019;23(3):343-7. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Tayebi Khosroshahi H, Vaziri ND, Abedi B, Asl BH, Ghojazadeh M, Jing W, et al. Effect of high amylose resistant starch (HAM-RS2) supplementation on biomarkers of inflammation and oxidative stress in hemodialysis patients: a randomized clinical trial. Hemodialysis International 2018;22(4):492-500. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Kooshki 2019 {published data only}
- Kooshki A, Tofighiyan T, Miri M. A synbiotic supplement for inflammation and oxidative stress and lipid abnormalities in hemodialysis patients. Hemodialysis International 2019;23(2):254-60. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Li 2020 {published data only}
- Li L, Xiong Q, Zhao J, Lin X, He S, Wu N, et al. Inulin-type fructan intervention restricts the increase in gut microbiome-generated indole in patients with peritoneal dialysis: a randomized crossover study [Erratum in: Am J Clin Nutr. 2022 Jun 7;115(6):1659]. American Journal of Clinical Nutrition 2020;111(5):1087-99. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Xiong Q, Li L, Xiao Y, He S, Zhao J, Lin X, et al. The effect of inulin-type fructans on plasma trimethylamine n-oxide levels in peritoneal dialysis patients: a randomized crossover trial. Molecular Nutrition & Food Research 2023;67(9):e2200531. [DOI: 10.1002/mnfr.202200531] [DOI] [PubMed] [Google Scholar]
Lim 2021 {published data only}
- Lim PS, Wang HF, Lee MC, Chiu LS, Wu MY, Chang WC, et al. The efficacy of lactobacillus-containing probiotic supplementation in hemodialysis patients: a randomized, double-blind, placebo-controlled trial. Journal of Renal Nutrition 2021;31(2):189-98. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Liu 2020 {published data only}
- Liu S, Liu H, Chen L, Liang SS, Shi K, Meng W, et al. Effect of probiotics on the intestinal microbiota of hemodialysis patients: a randomized trial. European Journal of Nutrition 2020;59(8):3755-66. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Lopes 2018 {published data only}
- Lopes RC, Theodoro JM, da Silva BP, Queiroz VA, Castro Moreira ME, Mantovani HC, et al. Synbiotic meal decreases uremic toxins in hemodialysis individuals: a placebo-controlled trial. Food Research International 2019;116:241-8. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Lopes RC, Lima SL, da Silva BP, Toledo RC, Moreira ME, Anunciacao PC, et al. Evaluation of the health benefits of consumption of extruded tannin sorghum with unfermented probiotic milk in individuals with chronic kidney disease. Food Research International 2018;107:629-38. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Lydia 2022 {published data only}
- Lydia A, Indra TA, Rizka A, Abdullah M. The effects of synbiotics on indoxyl sulphate level, constipation, and quality of life associated with constipation in chronic haemodialysis patients: a randomized controlled trial. BMC Nephrology 2022;23(1):259. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Mafi 2018 {published data only}
- Mafi A, Namazi G, Soleimani A, Bahmani F, Aghadavod E, Asemi Z. Metabolic and genetic response to probiotics supplementation in patients with diabetic nephropathy: a randomized, double-blind, placebo-controlled trial [Expression of Concern in: Food Funct. 2022 Apr 4;13(7):4229]. Food & Function 2018;9(9):4763-70. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Mazruei Arani 2019 {published data only}
- Mazruei Arani N, Emam-Djomeh Z, Tavakolipour H, Sharafati-Chaleshtori R, Soleimani A, Asemi Z. The effects of probiotic honey consumption on metabolic status in patients with diabetic nephropathy: a randomized, double-blind, controlled trial. Probiotics & Antimicrobial Proteins 2019;11(4):1195-201. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Meng 2019 {published data only}
- Meng Y, Bai H, Yu Q, Yan J, Zhao L, Wang S, et al. High-resistant starch, low-protein flour intervention on patients with early type 2 diabetic nephropathy: a randomized trial. Journal of Renal Nutrition 2019;29(5):386-93. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Miraghajani 2017 {published data only}
- Miraghajani M, Zaghian N, Dehkohneh A, Mirlohi M, Ghiasvand R. Probiotic soy milk consumption and renal function among type 2 diabetic patients with nephropathy: a randomized controlled clinical trial. Probiotics & Antimicrobial Proteins 2019;11(1):124-32. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Miraghajani M, Zaghian N, Mirlohi M, Feizi A, Ghiasvand R. Impact of probiotic soy milk consumption on oxidative stress among type 2 diabetic kidney disease patients: a randomized controlled clinical trial. Journal of Renal Nutrition 2017;27(5):317-24. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Miranda Alatriste 2014 {published data only}
- Miranda Alatriste PV, Urbina AR, Gomez Espinosa CO, Espinosa Cuevas ML. Effect of probiotics on human blood urea levels in patients with chronic renal failure. Nutricion Hospitalaria 2014;29(3):582-90. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Mirzaeian 2020 {published data only}
- Mirzaeian S, Saraf-Bank S, Entezari MH, Hekmatdoost A, Feizi A, Atapour A. Effects of synbiotic supplementation on microbiota-derived protein-bound uremic toxins, systemic inflammation, and biochemical parameters in patients on hemodialysis: A double-blind, placebo-controlled, randomized clinical trial. Nutrition 2020;73:110713. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Natarajan 2014 {published data only}
- Natarajan R, Pechenyak B, Vyas U, Ranganathan P, Weinberg A, Liang P, et al. Randomized controlled trial of strain-specific probiotic formulation (Renadyl) in dialysis patients. BioMed Research International 2014;2014:568571. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Pan 2021 {published data only}
- Pan Y, Yang L, Dai B, Lin B, Lin S, Lin E. Effects of probiotics on malnutrition and health-related quality of life in patients undergoing peritoneal dialysis: a randomized controlled trial. Journal of Renal Nutrition 2021;31(2):199-205. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Poesen 2016 {published data only}
- Poesen R, Evenepoel P, Loor H, Delcour JA, Courtin CM, Kuypers D, et al. The influence of prebiotic arabinoxylan oligosaccharides on microbiota derived uremic retention solutes in patients with chronic kidney disease: a randomized controlled trial. PLoS ONE {Electronic Resource] 2016;11(4):e0153893. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
PREBIOTIC 2022 {published data only}
- Chan S, Hawley CM, Pascoe EM, Cao C, Campbell KL, Campbell SB, et al. PREBIOTIC: a study protocol of a randomised controlled trial to assess prebiotic supplementation in kidney transplant recipients for preventing infections and gastrointestinal upset — a feasibility study. Pilot & Feasibility Studies 2023;9(1):11. [DOI: 10.1186/s40814-023-01236-y] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Chan S, Hawley CM, Pascoe EM, Cao C, Campbell SB, Campbell KL, et al. Prebiotic supplementation in kidney transplant recipients for preventing infections and gastrointestinal upset: a randomized controlled feasibility study. Journal of Renal Nutrition 2022;32(6):718-25. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Chan S, Hawley CM, Pascoe EM, Cao CZ, Campbell SB, Campbell KL, et al. Prebiotic supplementation in kidney transplant recipients for preventing infections and gastrointestinal upset: a randomized controlled feasibility study. American Journal of Transplantation 2022;22:783. [DOI: 10.1111/ajt.17073] [DOI] [PubMed] [Google Scholar]
ProbiotiCKD 2019 {published data only}
- Simeoni M, Cianfrone P, Capria M, Deodato F, Citraro M, Cerantonio A, et al. ProbiotiCKD: A monocentric, randomized, openlabel, placebo-controlled study to reveal and correct gut dysbiosis in early CKD stages [abstract no: SP367]. Nephrology Dialysis Transplantation 2018;33(Suppl 1):i469-70. [EMBASE: 622605912] [Google Scholar]
- Simeoni M, Citraro ML, Cerantonio A, Deodato F, Provenzano M, Cianfrone P, et al. An open-label, randomized, placebo-controlled study on the effectiveness of a novel probiotics administration protocol (ProbiotiCKD) in patients with mild renal insufficiency (stage 3a of CKD) [Erratum in: Eur J Nutr. 2018 58(5):2157]. European Journal of Nutrition 2019;58(5):2145-56. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Simeoni M, Citraro ML, Cerantonio A, Deodato F, Provenzano M, Cianfrone P, et al. Correction to: An open-label, randomized, placebo-controlled study on the effectiveness of a novel probiotics administration protocol (ProbiotiCKD) in patients with mild renal insufficiency (stage 3a of CKD) (European Journal of Nutrition, (2019), 58, 5, (2145-2156), 10.1007/s00394-018-1785-z). European Journal of Nutrition 2019;58(5):2157. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Ramos 2019 {published data only}
- Armani R, Ishikawa C, Hong V, Bortolotto LA, Cassiolatto JL, Klassen A, et al. Effect of frutooligosaccharide on endothelial function in CKD patients: a randomized controlled trial [abstract no: SAT-206]. Kidney International Reports 2019;4(7 Suppl):S93. [EMBASE: 2002179674] [Google Scholar]
- Armani RG, Carvalho AB, Ramos CI, Hong V, Bortolotto LA, Cassiolato JL, et al. Effect of fructooligosaccharide on endothelial function in CKD patients: a randomized controlled trial. Nephrology Dialysis Transplantation 2021;37(1):85-91. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Armani RG, Ramos CI, Cuppari L, Canziani ME. Effect of fructooligosaccharide on endothelium function in CKD patients: a randomized controlled trial [abstract no: TH-PO1138]. Journal of the American Society of Nephrology 2018;29(Abstract Suppl):417. [EMBASE: 633736090] [Google Scholar]
- Ramos CI, Armani RG, Canziani MEF, Dalboni MA, Dolenga CJR, Nakao LS, et al. Effect of prebiotic (fructooligosaccharide) on uremic toxins of chronic kidney disease patients: a randomized controlled trial. Nephrology Dialysis Transplantation 2019;34(11):1876-84. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Ramos CI, Armani RG, Nakao LS, Canziani MEF, Campbell KL, Cuppari L. Effect of fructooligosaccharide on microbiota-derived uremic toxins in predialysis patients: a randomized controlled trial [abstract no: SA-PO161]. Journal of the American Society of Nephrology 2017;28(Abstract Suppl):720. [EMBASE: 633702127] [Google Scholar]
Ranganathan 2009 {published data only}
- Ranganathan N, Friedman EA, Tam P, Rao V, Ranganathan P, Dheer R. Probiotic dietary supplementation in patients with stage 3 and 4 chronic kidney disease: a 6-month pilot scale trial in Canada. Current Medical Research & Opinion 2009;25(8):1919-30. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
- Ranganathan N, Friedman EA, Tam PY, Rao V, Ranganathan PL. Dietary supplementation with a probiotic formulation (Kibow biotics) on CKD III and IV patients- a short term pilot scale study in Canada [abstract no: SA-PO2755]. Journal of the American Society of Nephrology 2009;20(Abstract Suppl):741A. [Google Scholar]
- Ranganathan N, Ranganathan P, Friedman EA, Joseph A, Delano B, Goldfarb DS, et al. Pilot study of probiotic dietary supplementation for promoting healthy kidney function in patients with chronic kidney disease. Advances in Therapy 2010;27(9):634-47. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Shariaty 2017 {published data only}
- Shariaty Z, Mahmoodi Shan GR, Farajollahi M, Amerian M, Behnam PN. The effects of probiotic supplement on hemoglobin in chronic renal failure patients under hemodialysis: a randomized clinical trial. Journal of Research in Medical Sciences 2017;22:74. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Sirich 2014 {published data only}
- Sirich TL, Plummer N, Hostetter TH, Meyer T. Increasing dietary fiber reduces plasma levels of colon-derived uremic solutes in hemodialysis patients [abstract no: FR-PO793]. Journal of the American Society of Nephrology 2013;24(Abstract Suppl):545A. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sirich TL, Plummer NS, Gardner CD, Hostetter TH, Meyer TW. Effect of increasing dietary fiber on plasma levels of colon-derived solutes in hemodialysis patients. Clinical Journal of the American Society of Nephrology: CJASN 2014;9(9):1603-10. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Soleimani 2017 {published data only}
- Soleimani A, Zarrati Mojarrad M, Bahmani F, Taghizadeh M, Ramezani M, Tajabadi-Ebrahimi M, et al. Probiotic supplementation in diabetic hemodialysis patients has beneficial metabolic effects. Kidney International 2017;91(2):435-42. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Soleimani 2019 {published data only}
- Soleimani A, Motamedzadeh A, Zarrati Mojarrad M, Bahmani F, Amirani E, Ostadmohammadi V, et al. The effects of synbiotic supplementation on metabolic status in diabetic patients undergoing hemodialysis: a randomized, double-blinded, placebo-controlled trial. Probiotics & Antimicrobial Proteins 2019;11(4):1248-56. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
SYNERGY 2014 {published data only}
- Rossi M, Johnson D, Pascoe E, Coombes J, Forbes J, Szeto CC, et al. Synbiotic therapy in pre-dialysis: a randomised controlled trial [abstract no: SAO029]. Nephrology Dialysis Transplantation 2015;30(Suppl 3):iii38. [EMBASE: 72206363] [Google Scholar]
- Rossi M, Johnson DW, Morrison M, Pascoe E, Coombes JS, Forbes JM, et al. SYNbiotics Easing Renal failure by improving Gut microbiologY (SYNERGY): a protocol of placebo-controlled randomised cross-over trial. BMC Nephrology 2014;15:106. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rossi M, Johnson DW, Morrison M, Pascoe EM, Coombes JS, Forbes JM, et al. Synbiotics easing renal failure by improving gut microbiology (SYNERGY): a randomized trial. Clinical Journal of the American Society of Nephrology: CJASN 2016;11(2):223-31. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Rossi M, Johnson DW, Xu H, Carrero JJ, Pascoe E, French C, et al. Dietary protein-fiber ratio associates with circulating levels of indoxyl sulfate and p-cresyl sulfate in chronic kidney disease patients. Nutrition Metabolism & Cardiovascular Diseases 2015;25(9):860-5. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
SYNERGY II 2021 {published data only}ACTRN12617000324314
- McFarlane C, Krishnasamy R, Stanton T, Savill E, Snelson M, Mihala G, et al. Synbiotics easing renal failure by improving gut microbiology II (SYNERGY II): a feasibility randomized controlled trial. Nutrients 2021;13(12):4481. [PMID: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Viramontes‐Horner 2015 {published data only}
- Viramontes-Horner D, Marquez-Sandoval F, Martin-del-Campo F, Vizmanos-Lamotte B, Sandoval-Rodriguez A, Armendariz-Borunda J, et al. Effect of a symbiotic gel (Lactobacillus acidophilus + Bifidobacterium lactis + inulin) on presence and severity of gastrointestinal symptoms in hemodialysis patients. Journal of Renal Nutrition 2015;25(3):284-91. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Wang 2015a {published data only}
- Wang IK, Wu YY, Yang YF, Ting IW, Lin CC, Yen TH, et al. The effect of probiotics on serum levels of cytokine and endotoxin in peritoneal dialysis patients: a randomised, double-blind, placebo-controlled trial. Beneficial Microbes 2015;6(4):423-30. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Xie 2015a {published data only}
- Xie LM, Ge YY, Huang X, Zhang Y, Li JX. Effects of fermentable dietary fiber supplementation on oxidative and inflammatory status in hemodialysis patients. International Journal of Clinical & Experimental Medicine 2015;8(1):1363-9. [EMBASE: 602272251] [PMC free article] [PubMed] [Google Scholar]
References to studies excluded from this review
Afaghi 2016 {published data only}
- Afaghi E, Tayebi A, Ebadi A, Sobhani V, Einollahi B, Tayebi M. The effect of BCAA and ISO-WHEY oral nutritional supplements on dialysis adequacy. Nephrourology Monthly 2016;8(6):e34993. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Cruz‐Mora 2014 {published data only}
- Cruz-Mora J, Martinez-Hernandez NE, Martin del Campo-Lopez F, Viramontes-Horner D, Vizmanos-Lamotte B, Munoz-Valle JF, et al. Effects of a symbiotic on gut microbiota in Mexican patients with end-stage renal disease. Journal of Renal Nutrition 2014;24(5):330-5. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Eguchi 2011 {published data only}
- Eguchi S, Takatsuki M, Hidaka M, Soyama A, Ichikawa T, Kanematsu T. Perioperative synbiotic treatment to prevent infectious complications in patients after elective living donor liver transplantation: a prospective randomized study. American Journal of Surgery 2011;201(4):498-502. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Ferrara 2009 {published data only}
- Ferrara P, Romaniello L, Vitelli O, Gatto A, Serva M, Cataldi L. Cranberry juice for the prevention of recurrent urinary tract infections: a randomized controlled trial in children. Scandinavian Journal of Urology & Nephrology 2009;43(5):369-72. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Firouzi 2015a {published data only}
- Firouzi S, Mohd-Yusof BN, Majid HA, Ismail A, Kamaruddin NA. Effect of microbial cell preparation on renal profile and liver function among type 2 diabetics: a randomized controlled trial. BMC Complementary & Alternative Medicine 2015;15:433. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Fitschen 2015 {published data only}
- Fitschen PJ, Kistler B, Wu PT, Chung HR, Jeong JH, Phillips S, et al. Effects of intradialytic whey protein supplementation on body composition in non-malnourished hemodialysis patients [abstract no: SA-PO543]. Journal of the American Society of Nephrology 2012;23(Abstract Suppl):763A. [Google Scholar]
- Tomayko E, Wu PT, Chung HR, Fitschen P, Kistler B, Yudell B, et al. Intradialytic protein supplementation attenuates dialysis-associated inflammation and reduces co-morbid disease risk [abstract no: SA-OR401]. Journal of the American Society of Nephrology 2011;22(Abstract Suppl):96A. [Google Scholar]
- Tomayko E, Yudell B, Jeanes E, Kistler B, Fitschen P, Jeong JH, et al. Intradialytic protein supplementation improves co-morbid disease risk in hemodialysis patients [abstract]. FASEB Journal 2012;26(Suppl 1):na. [EMBASE: 70854879] [Google Scholar]
- Tomayko EJ, Kistler BM, Fitschen PJ, Wilund KR. Intradialytic protein supplementation reduces inflammation and improves physical function in maintenance hemodialysis patients. Journal of Renal Nutrition 2015;25(3):276-83. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Fortes 2020 {published data only}
- Fortes PM, Teles Filho RV, Azevedo LH, Queiroz VC, da Costa PS. Inflammatory cytokines and lipid profile in children and adolescents with nephrotic syndrome receiving L. Plantarum: a randomized, controlled feasibility trial. Revista Da Associacao Medica Brasileira 2020;66(11):1487-92. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Grat 2017 {published data only}
- Grat M, Krawczyk M, Wronka K, Lewandowski Z, Grat K, Krasnodebski M, et al. Impact of pre-transplant use of probiotics on allograft function after liver transplantation: post-hoc analysis of a randomized controlled trial [abstract]. HPB 2018;20(Suppl 2):S798. [EMBASE: 2001142904] [Google Scholar]
- Grat M, Wronka KM, Lewandowski Z, Grat K, Krasnodebski M, Stypulkowski J, et al. Effects of continuous use of probiotics before liver transplantation: a randomized, double-blind, placebo-controlled trial. Clinical Nutrition 2017;36(6):1530-9. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Hassan 2017 {published data only}
- Hassan K, Armaly Z, Hassan D, Khayr M, Rubinchik I, Khazim K, et al. Does whey protein supplementation affect systemic inflammation in hypoalbuminemic peritoneal dialysis patients? [abstract no: SP496]. Nephrology Dialysis Transplantation 2017;32(Suppl 3):iii295-6. [EMBASE: 617291379] [Google Scholar]
Jiang 2021a {published data only}
- Jiang H, Zhang Y, Xu D, Wang Q. Probiotics ameliorates glycemic control of patients with diabetic nephropathy: a randomized clinical study. Journal of Clinical Laboratory Analysis 2021;35(4):e23650. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
- Liu S, Jiang H. Probiotic dietary supplementation in hemodialysis patients: a double-blind,randomized, placebo-controlled trial [abstract no: FR-OR128]. Journal of the American Society of Nephrology 2018;29(Abstract Suppl):73. [EMBASE: 633737360] [Google Scholar]
Lin 2021 {published data only}
- Lin W, Jiang C, Yu H, Wang L, Li J, Liu X, et al. The effects of fushen granule on the composition and function of the gut microbiota during peritoneal dialysis-related peritonitis. Phytomedicine 2021;86:153561. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Orr 2016 {published data only}
- Orr DW, Myint H, Murphy R. Probiotic supplementation after very low calorie diet does not aid improvement of the metabolic syndrome or maintenance of weight loss post liver transplant. A randomised double-blind placebo controlled trial [abstract no: 214]. Hepatology 2016;64(1 Suppl 1):113-4A. [EMBASE: 612594308] [Google Scholar]
Pavan 2016 {published data only}
- Pavan M. Influence of prebiotic and probiotic supplementation on the progression of chronic kidney disease. Minerva Urologica e Nefrologica 2016;68(2):222-6. [MEDLINE: ] [PubMed] [Google Scholar]
PrePro 2018 {published data only}
- Mallick S, Kathirvel M, Thillai M, Sethi P, Durairaj MS, Nair K, et al. PrePro Trial: randomized double-blind placebo controlled trial to analyze the effect of synbiotics on infectious complications following living donor liver transplantion [CTRI no. - CTRI/2017/09/009869]. HPB 2018;20(Suppl 2):S283-4. [EMBASE: 2000962392] [Google Scholar]
- Mallick S, Mathew JS, Binoj S, Unnikrishnan G, Menon RN, Dinesh B, et al. PrePro trial: a randomized double blind placebo controlled trial to analyze the effect of synbiotics on infectious complications following living donor liver transplant (LDLT). [CTRI/2017/09/009869]. Transplantation 2018;102(5 Suppl 1):63. [EMBASE: 622538666] [Google Scholar]
ProLow CKD 2022 {published data only}
- De Mauri A, Carrera D, Bagnati M, Rolla R, Vidali M, Chiarinotti D, et al. Probiotics-supplemented low-protein diet for microbiota modulation in patients with advanced chronic kidney disease (ProLowCKD): results from a placebo-controlled randomized trial. Nutrients 2022;14(8):1637. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Rayes 2002 {published data only}
- Rayes N, Seehofer D, Hansen S, Boucsein K, Muller AR, Serke S, et al. Early enteral supply of lactobacillus and fiber versus selective bowel decontamination: a controlled trial in liver transplant recipients. Transplantation 2002;74(1):123-7. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Rayes 2002a {published data only}
- Rayes N, Seehofer D, Muller AR, Hansen S, Bengmark S, Neuhaus P. Influence of probiotics and fibre on the incidence of bacterial infections following major abdominal surgery - results of a prospective trial [Einfluss von Probiotika und Ballaststoffen auf die Inzidenz bakterieller Infektionen nach viszeralchirurgischen Eingriffen - Ergebnisse einer prospektiven Studie]. Zeitschrift fur Gastroenterologie 2002;40(10):869-76. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Rayes 2005 {published data only}
- Rayes N, Seehofer D, Theruvath T, Schiller RA, Langrehr JM, Jonas S, et al. Supply of pre- and probiotics reduces bacterial infection rates after liver transplantation--a randomized, double-blind trial. American Journal of Transplantation 2005;5(1):125-30. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Saxena 2022 {published data only}
- Saxena A, Jacob CK, Sreenivasa S, Veerappan I, Mahaldar AR, Gupta A, et al. A prospective, double-blind, randomized, placebo-controlled interventional study to evaluate the safety and efficacy of enzobiotics in pre-dialysis CKD patients [abstract no: PO2628]. Journal of the American Society of Nephrology 2020;31(Abstract Suppl):B5. [EMBASE: 633696629] [Google Scholar]
- Saxena A, Srinivasa S, Veerappan I, Jacob C, Mahaldar A, Gupta A, et al. Enzobiotics-a novel therapy for the elimination of uremic toxins in patients with CKD (EETOX Study): a multicenter double-blind randomized controlled trial. Nutrients 2022;14(18):3804. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Tayebi‐Khosroshahi 2016 {published data only}
- Tayebi-Khosroshahi H, Habibzadeh A, Niknafs B, Ghotaslou R, Yeganeh Sefidan F, Ghojazadeh M, et al. The effect of lactulose supplementation on fecal microflora of patients with chronic kidney disease; a randomized clinical trial. Journal of Renal Injury Prevention 2016;5(3):162-7. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Wang 2018e {published data only}
- Wang M, Liu H. Dietary advanced glycation end products restriction effects on intestinal bacterial flora and microinflammation state in maintenance hemodialysis patients [abstract no: SA-PO1013]. Journal of the American Society of Nephrology 2019;30(Abstract Suppl):1027. [EMBASE: 633768911] [Google Scholar]
- Wang M. Dietary advanced glycation end products restriction effects on intestinal bacterial flora and microinflammation state in maintenance hemodialysis patients [abstract no: SP664]. Nephrology Dialysis Transplantation 2018;33(Suppl 1):i569-70. [EMBASE: 622605572] [Google Scholar]
References to studies awaiting assessment
Chen 2019b {published data only}
- Chen X, Chen S, Huang L, Mao Z. Probiotics decreased concentrations of indoxylsulphate in PD patients [abstract no: SA-PO954]. Journal of the American Society of Nephrology 2019;30(Abstract Suppl):1011. [EMBASE: 633767865] [Google Scholar]
Mady 2018 {published data only}
- Mady G, Sarhan I, Shawki S, Halim A, Mahanna N, Abdallah M. Effect of probiotics on serum indoxyl sulphate in hemodialysis patients [abstract]. Hemodialysis International 2018;22(1):A15. [EMBASE: 620701234] [Google Scholar]
Marks 2010 {published data only}
- Marks WH, Spinelli TY, Olmstead SF. Probiotics to reduce immunosuppression-associated diarrhea following kidney transplantation - a prospective double-blinded randomized placebo-controlled trial [abstract no: 96]. American Journal of Transplantation 2010;10(Suppl 4):68. [EMBASE: 70463457] [Google Scholar]
Ogawa 2020 {published data only}
- Ogawa T, Hosoda Y, Horimoto A, Nishizawa Y, Omae K, Nagano N. Probiotic bio-three decreases serum phosphate levels with involvement of bacteria in gut microbioma in hemodialysis patients: A prospective, randomized, double-blind, placebo-contolled study [abstract no: SO055]. Nephrology Dialysis Transplantation 2020;35(Suppl 3):iii61. [EMBASE: 633421401] [Google Scholar]
Prado 2020 {published data only}
- Prado L, Aguilar K, Arellano J, Mariscal L, Campos I, Tuz F, et al. Lipid profile improvement in chronic kidney disease patients using a symbiotic supplement with agave inulin, Lactobacillus rhamnosus and Bifidobacterium longum. A post-hoc analysis from a randomized controlled trial [abstract no: 21]. Blood Purification 2020;49(1-2):243. [EMBASE: 631196086] [Google Scholar]
Ranganathan 2019a {published data only}
- Ranganathan N, Vyas UN, Ranganathan P, Irvin A, Weinberg AD. A double-blind, randomized, placebo-controlled with an open-label rollover extension phase 2/3 clinical trial to evaluate safety and efficacy of US-APR2020 in subjects with CKD stage IV [abstract no: PUB036]. Journal of the American Society of Nephrology 2020;31(Abstract Suppl):801. [EMBASE: 633696783] [Google Scholar]
- Ranganathan N, Vyas UN, Ranganathan P, Irvin A, Weinberg AD. Kibow multisite hope study dialysis randomized clinical trial protocol: a unique double-blind placebo-controlled cross-over design using renadyl standard-care therapy (n=100, 5 sites in the United States) [abstract no: PUB134]. Journal of the American Society of Nephrology 2019;30(Abstract Suppl):1108. [EMBASE: 633771192] [Google Scholar]
- Ranganathan N, Vyas UN, Ranganathan P, Irvin A, Weinberg AD. Kibow multisite hope study-CKD IV randomized clinical trial protocol: a unique double-blind placebo-controlled cross-over design using renadyl with standard-of-care therapy (n=500-600, 20-25 sites in the United States) [abstract no: FR-PO339]. Journal of the American Society of Nephrology 2019;30(Abstract Suppl):524-5. [EMBASE: 633768784] [Google Scholar]
Soliman 2018 {published data only}
- Soliman Ahmed Y, Ibrahim Sarhaan E, Shaker Mehanna N, Saeed Hassan M, Abd-El Nasier Abd-El Gawad M, Nagdy Madbouli N. The effect of synbiotics on serum indoxyl sulfate in maintenance haemodialysis patients [abstract]. QJM 2018;111(Suppl 1):i84-5. [EMBASE: 631035999] [Google Scholar]
- Soliman Y, Sarhan I, Mahanna N, Saeed M, Abd-ElNasier M, Nagdy N. The effect of synbiotic on serum indoxyl sulfate in maintenance hemodialysis patients [abstract]. Hemodialysis International 2018;22(1):A15. [EMBASE: 620701232] [Google Scholar]
Takayama 2003 {published data only}
- Takayama F, Enomoto A, Aoyama I. Oral administration of bifidobacteria in gastro-resistant seamless capsule reduces serum levels of indoxyl sulfate in patients on hemodialysis [abstract no: T297]. Nephrology Dialysis Transplantation 2002;17(Suppl 1):271. [CENTRAL: CN-00644305] [Google Scholar]
- Takayama F, Taki K, Niwa T. Bifidobacterium in gastro-resistant seamless capsule reduces serum levels of indoxyl sulfate in patients on hemodialysis. American Journal of Kidney Diseases 2003;41(3 Suppl 1):S142-5. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
TCTR20220317007 {published data only}
- Amelioration of uremic toxin indoxyl sulfate by oral chito-oligosaccharide in predialysis patients: a randomized controlled trial. https://trialsearch.who.int/Trial2.aspx?TrialID=TCTR20220317007 (date posted 1 March 2022). [DOI] [PubMed]
- Sirisuksakun C, Thimachai P, Tasanavipas P, Siriwattanasit N, Inkong P, Varothai N, et al. Amelioration of uremic toxin indoxyl sulfate by oral chito-oligosaccharide in predialysis patients: a randomized controlled trial [abstract no: SA-PO901]. Journal of the American Society of Nephrology 2022;33:852. [Google Scholar]
Wu 2012 {published data only}
- Wu AB, Wang MC, Chang YT, Tseng CC. Probiotics decrease the incidence of gram negative peritonitis in patients on peritoneal dialysis [abstract no: SA-PO864]. Journal of the American Society of Nephrology 2012;23(Abstract Suppl):840A. [Google Scholar]
Younes 2006 {published data only}
- Younes H, Egret N, Hadj-Abdelkader M, Remesy C, Demigne C, Gueret C, et al. Fermentable carbohydrate supplementation alters nitrogen excretion in chronic renal failure. Journal of Renal Nutrition 2006;16(1):67-74. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Zhang 2019a {published data only}
- Zhang Q. Effect of probiotic on gut microbiota in peritoneal dialysis patient with protein-energy wasting: 1 year follow up of a randomised controlled trial [abstract no: P0917]. European Journal of Immunology 2019;49(Suppl 3):1127-8. [EMBASE: 631545578] [Google Scholar]
References to ongoing studies
ChiCTR2200061930 {published data only}
- Effects of non-protein energy supplements and exercise on protein-energy wasting and gut microbes in maintenance hemodialysis patients. https://trialsearch.who.int/Trial2.aspx?TrialID=ChiCTR2200061930 (date posted 11 July 2022).
ChiCTR2200064821 {published data only}
- Clinical effect and mechanism of modified Shenling Baizhu powder on peritoneal dialysis. https://trialsearch.who.int/Trial2.aspx?TrialID=ChiCTR2200064821 (date posted 19 October 2022).
ChiCTR2300070381 {published data only}
- Effects of dietary fiber-added diets on protein-binding toxoids and microinflammatory states in patients with chronic kidney disease. https://trialsearch.who.int/Trial2.aspx?TrialID=ChiCTR2300070381 (date posted 11 April 2023).
ChiCTR2300072339 {published data only}
- Probiotics improve immune metabolism in maintenance hemodialysis patients by regulating intestinal flora. https://trialsearch.who.int/Trial2.aspx?TrialID=ChiCTR2300072339 (date posted 9 June 2023).
CTRI/2022/02/040296 {published data only}
- A study to assess the effect of probiotic in prevention of progression of kidney disease in patients with chronic kidney disease [A controlled randomized study to evaluate the effect of probiotic on uremic solutes,inflammatory status and oxidative stress in chronic kidney disease subjects - PRO-URE-CKD]. https://trialsearch.who.int/Trial2.aspx?TrialID=CTRI/2022/02/040296 (date posted 15 February 2022).
CTRI/2022/11/047767 {published data only}
- Global phase 2 clinical trial to evaluate safety and efficacy of US-APR2020 in subjects with chronic kidney disease stage IV. https://trialsearch.who.int/Trial2.aspx?TrialID=CTRI/2022/11/047767 (date posted 29 November 2022).
Ghoreishy 2022 {published data only}
- Ghoreishy SM, Shirzad N, Nakhjavani M, Esteghamati A, Djafarian K, Esmaillzadeh A. Effect of daily consumption of probiotic yoghurt on albumin to creatinine ratio, eGFR and metabolic parameters in patients with type 2 diabetes with microalbuminuria: study protocol for a randomised controlled clinical trial. BMJ Open 2022;12(3):e056110. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Headley 2020 {published data only}
- Headley SA, Chapman DJ, Germain MJ, Evans EE, Hutchinson J, Madsen KL, et al. The effects of 16-weeks of prebiotic supplementation and aerobic exercise training on inflammatory markers, oxidative stress, uremic toxins, and the microbiota in pre-dialysis kidney patients: a randomized controlled trial-protocol paper. BMC Nephrology 2020;21(1):517. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
IRCT20100223003408N5 {published data only}
- Ekramzadeh M, Azad F, Hamidianshirazi M, Mazloomi SM, Shafiee M. Efficacy of fortified synbiotic dessert on malnutrition and oxidative stress outcomes in hemodialysis patients: a randomized double-blind controlled trial [abstract]. American Journal of Kidney Diseases 2023;81(4):S113. [DOI: 10.1053/j.ajkd.2023.01.390] [DOI] [Google Scholar]
- Ekramzadeh M. Synbiotic dessert fortified with vitamin D and dalcium in hemodialysis patients [Effect of synbiotic dessert fortified with vitamin d and calcium on nutritional indices, inflammation, oxidative stress, malnutrition and quality of life in hemodialysis patients]. en.irct.ir/trial/35600 (date posted 6 April 2019).
IRCT20131013014994N7 {published data only}
- The effect of synbiotic supplementation on plasma levels of Advanced Glycation End Products and cardiovascular risk factors in hemodialysis patients: a double-blind clinical trial. https://trialsearch.who.int/Trial2.aspx?TrialID=IRCT20131013014994N7 (date posted 27 April 2022). [DOI] [PMC free article] [PubMed]
IRCT20160206026390N11 {published data only}
- Ghaedi E. Probiotics and children under hemodialysis treatment [Evaluation of the efficacy of probiotic supplementation on bio-markers of inflammation and oxidative stress in pediatric patients under treatment with hemodialysis: randomized double blind clinical trial]. en.irct.ir/trial/35899 (date posted 10 June 2019).
IRCT20230608058421N1 {published data only}
- The effect of probiotics on patients with end-stage renal failure. https://trialsearch.who.int/Trial2.aspx?TrialID=IRCT20230608058421N1 (date posted 29 June 2023).
KCT0007834 {published data only}
- The effect of carboneceous oral adsorbent and synbiotics on the gut microbiome and muscle health in chronic kidney disease patients. https://trialsearch.who.int/Trial2.aspx?TrialID=KCT0007834 (date posted 21 October 2022).
Mitrovic 2023 {published data only}
- Mitrovic M, Stankovic-Popovic V, Tolinacki M, Golic N, Sokovic Bajic S, Veljovic K, et al. The impact of synbiotic treatment on the levels of gut-derived uremic toxins, inflammation, and gut microbiome of chronic kidney disease patients- a randomized trial. Journal of Renal Nutrition 2023;33(2):278-88. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
NCT03770611 {published data only}
- Cueto-Manzano A. Effect of prebiotics and/or probiotics on uremic toxins and inflammation markers in peritoneal dialysis patients [Effect of a nutritional supplement of probiotics and/or prebiotics vs placebo on serum concentrations of uremic toxins and inflammatory cytokines in automated peritoneal dialysis patients]. www.clinicaltrials.gov/show/NCT03770611 (date posted 10 December 2018).
NCT03789708 {published data only}
- Elamin S. Effects of gum arabic supplementation in hemodialysis patients [Study of some pharmacological and biochemical effects of gum arabic supplementation to hemodilaysis patients]. www.clinicaltrials.gov/show/NCT03789708 (date posted 31 December 2018).
NCT03924089 {published data only}
- Olveira G. Oral nutritional supplement on nutritional and functional status, and biomarkers in malnourished hemodialysis patients (RENACARE) [Effect of an oral nutritional supplement on nutritional and functional status, biological markers (inflammation and oxidative stress, intestinal microbiota, circulating microRNA And its target genes) in malnourished hemodialysis patients]. clinicaltrials.gov/show/NCT03924089 (date posted 23 April 2019).
NCT05183737 {published data only}
- Effects of microencapsulated propolis and turmeric in patients with chronic kidney disease. https://clinicaltrials.gov/show/NCT05183737 (date posted 11 January 2022).
NCT05336305 {published data only}
- Polydextrose for patients with chronic kidney disease. https://clinicaltrials.gov/show/NCT05336305 (date posted 20 April 2022).
NCT05359094 {published data only}
- Probiotic supplements in chronic kidney disease. https://clinicaltrials.gov/show/NCT05359094 (date posted 3 May 2022).
NCT05540431 {published data only}
- Evaluation of protective effect of activated charcoal and probiotic against progression of chronic kidney disease. https://clinicaltrials.gov/show/NCT05540431 (date posted 14 September 2022).
NCT05674981 {published data only}
- To evaluate the beneficial effect of probiotics on DKD patients and the role of gut microbiota modulation. https://clinicaltrials.gov/show/NCT05674981 (date posted 9 January 2023).
NCT05724511 {published data only}
- The effect of probiotics on depression syndrome and risk factors of cardiovascular disease in hemodialysis patients. https://clinicaltrials.gov/show/NCT05724511 (date posted 13 February 2023).
NCT05835648 {published data only}
- Effect of dietary fiber on non-dialysis patients with chronic kidney disease. https://clinicaltrials.gov/show/NCT05835648 (date posted 28 April 2023).
RBR‐3WRNF {published data only}
- Moraes da Silva A. Effect of prebiotics on intestinal transit and inflammation of patients with pre-dialytic chronic renal disease. www.ensaiosclinicos.gov.br/rg/RBR-3wrnrf/ (date posted 13 December 2018).
ReSPECKD 2022 {published data only}
- Shamloo M, Mollard R, Wang H, Kingra K, Tangri N, MacKay D. A randomized double-blind cross-over trial to study the effects of resistant starch prebiotic in chronic kidney disease (ReSPECKD). Trials [Electronic Resource] 2022;23(1):72. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Additional references
Aron‐Wisnewsky 2016
- Aron-Wisnewsky J, Clement K. The gut microbiome, diet, and links to cardiometabolic and chronic disorders. Nature Reviews Nephrology 2016;12(3):169-81. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Azad 2018
- Azad MA, Sarker M, Li T, Yin J. Probiotic species in the modulation of gut microbiota: an overview. BioMed Research International 2018;2018:9478630. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Balshem 2011
- Balshem H, Helfand M, Schünemann HJ, Oxman AD, Kunz R, Brozek J, et al. GRADE guidelines: 3. Rating the quality of evidence. Journal of Clinical Epidemiology 2011;64(4):401-6. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Beerepoot 2016
- Beerepoot M, Geerlings S. Non-antibiotic prophylaxis for urinary tract infections. Pathogens 2016;5(2):36. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Bromberg 2015
- Bromberg JS, Fricke WF, Brinkman CC, Simon T, Mongodin EF. Microbiota - implications for immunity and transplantation. Nature Reviews Nephrology 2015;11(6):342-53. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Cao 2022
- Cao C, Zhu H, Yao Y, Zeng R. Gut dysbiosis and kidney diseases. Frontiers in Medicine 2022;3(9):829349. [PMID: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Chan 2020
- Chan S, Cao C, Pascoe EM, Johnson DW, Shah A, Holtman GA, et al. Patient-reported gastrointestinal symptoms and the association with quality of life following kidney transplantation. Kidney International Reports 2020;6(1):138-45. [PMID: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Chen 2022
- Chen C, Wang J, Li J, Zhang W, Ou S. Probiotics, prebiotics, and synbiotics for patients on dialysis: a systematic review and meta-analysis of randomized controlled trials. Journal of Renal Nutrition 2023;33(1):129-39. [DOI: ] [DOI] [PubMed] [Google Scholar]
Cremon 2018
- Cremon C, Barbaro MR, Ventura M, Barbara G. Pre- and probiotic overview. Current Opinion in Pharmacology 2018;43:87-92. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Davani‐Davari 2019
- Davani-Davari D, Negahdaripour M, Karimzadeh I, Seifan M, Mohkam M, Masoumi SJ, et al. Prebiotics: definition, types, sources, mechanisms, and clinical applications. Foods 2019;8(3):92. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
FAO/WHO 2002
- Joint FAO/WHO Working Group Report on Drafting Guidelines for the Evaluation of Probiotics in Food London, Ontario, Canada, April 30 and May 1, 2002. Guidelines for the evaluation of probiotics in food. www.who.int/foodsafety/fs_management/en/probiotic_guidelines.pdf (last accessed 7 May 2020).
GBD 2017
- GBD 2017 Causes of Death Collaborators. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017 [Erratum in: Lancet. 2019 Jun 22;393(10190):e44; PMID: 31232379] [Erratum in: Lancet. 2018 Nov 17;392(10160):2170; PMID: 31329658]. Lancet 2018;392(10159):1736-88. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Gibson 2017
- Gibson GR, Hutkins R, Sanders ME, Prescott SL, Reimer RA, Salminen SJ, et al. Expert consensus document: the International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of prebiotics. Nature Reviews. Gastroenterology & Hepatology 2017;14(8):491-502. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
GRADE 2008
- Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ 2008;336(7650):924-6. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
GRADE 2011
- Guyatt G, Oxman AD, Akl EA, Kunz R, Vist G, Brozek J, et al. GRADE guidelines: 1. Introduction-GRADE evidence profiles and summary of findings tables. Journal of Clinical Epidemiology 2011;64(4):383-94. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Higgins 2003
- Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003;327(7414):557-60. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Higgins 2022
- Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.
Hill 2016
- Hill NR, Fatoba ST, Oke JL, Hirst JA, O'Callaghan CA, Lasserson DS, et al. Global prevalence of chronic kidney disease - a systematic review and meta-analysis. PLoS ONE [Electronic Resource] 2016;11(7):e0158765. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Jha 2013
- Jha V, Garcia-Garcia G, Iseki K, Li Z, Naicker S, Plattner B, et al. Chronic kidney disease: global dimension and perspectives [Erratum in: Lancet. 2013 Jul 20;382(9888):208]. Lancet 2013;382(9888):260-72. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Kato 2008
- Kato S, Chmielewski M, Honda H, Pecoits-Filho R, Matsuo S, Yuzawa Y, et al. Aspects of immune dysfunction in end-stage renal disease. Clinical Journal of The American Society of Nephrology: CJASN 2008;3(5):1526-33. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
KDIGO 2013
- Stevens PE, Levin A. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Annals of Internal Medicine 2013;158(11):825-30. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Lehto 2018
- Lehto M, Groop PH. The gut-kidney axis: putative interconnections between gastrointestinal and renal disorders. Frontiers in Endocrinology 2018;9:553. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Lewis 1997
- Lewis SJ, Heaton KW. Stool form scale as a useful guide to intestinal transit time. Scandinavian Journal of Gastroenterology 1997;32(9):920-4. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Luyckx 2018
- Luyckx VA, Tonelli M, Stanifer JW. The global burden of kidney disease and the sustainable development goals. Bulletin of the World Health Organization 2018;96(6):414-22D. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Mafra 2019
- Mafra D, Borges N, Alvarenga L, Esgalhado M, Cardozo L, Lindholm B, et al. Dietary components that may influence the disturbed gut microbiota in chronic kidney disease. Nutrients 2019;11(3):496. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
March 2020
- March DS, Jones AW, Bishop NC, Burton JO. The efficacy of prebiotic, probiotic, and synbiotic supplementation in modulating gut-derived circulatory particles associated with cardiovascular disease in individuals receiving dialysis: a systematic review and meta-analysis of randomized controlled trials. Journal of Renal Nutrition 2020;30(4):347-59. [PMID: ] [DOI] [PubMed] [Google Scholar]
McFarlane 2019
- McFarlane C, Ramos CI, Johnson DW, Campbell KL. Prebiotic, probiotic, and synbiotic supplementation in chronic kidney disease: a systematic review and meta-analysis. Journal of Renal Nutrition 2019;9(3):209-20. [PMID: ] [DOI] [PubMed] [Google Scholar]
Pan 2018
- Pan W, Kang Y. Gut microbiota and chronic kidney disease: implications for novel mechanistic insights and therapeutic strategies. International Urology & Nephrology 2018;50(2):289-99. [MEDLINE: ] [DOI] [PubMed] [Google Scholar]
Sampai‐Maia 2016
- Sampaio-Maia B, Simões-Silva L, Pestana M, Araujo R, Soares-Silva IJ. The role of the gut microbiome on chronic kidney disease. Advances in Applied Microbiology 2016;96:65-94. [PMID: ] [DOI] [PubMed] [Google Scholar]
Schünemann 2022a
- Schünemann HJ, Higgins JP, Vist GE, Glasziou P, Akl EA, Skoetz N, et al. Chapter 14: Completing ‘Summary of findings’ tables and grading the certainty of the evidence. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. www.training.cochrane.org/handbook.
Schünemann 2022b
- Schünemann HJ, Vist GE, Higgins JP, Santesso N, Deeks JJ, Glasziou P, et al. Chapter 15: Interpreting results and drawing conclusions. In: Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.
SONG 2017
- SONG Initiative. The SONG Handbook Version 1.0. www.songinitiative.org/reports-and-publications/ 2017.
Valdes 2018
- Valdes AM, Walter J, Segal E, Spector TD. Role of the gut microbiota in nutrition and health. BMJ 2018;361:k2179. [MEDLINE: ] [DOI] [PMC free article] [PubMed] [Google Scholar]
Zheng 2020
- Zheng JH, Guo J, Wang Q, Wang L, Wang Y, Zhang F, et al. Probiotics, prebiotics, and synbiotics for the improvement of metabolic profiles in patients with chronic kidney disease: A systematic review and meta-analysis of randomized controlled trials. Critical Reviews in Food Science & Nutrition 2020;61(4):577–98. [PMID: ] [DOI] [PubMed] [Google Scholar]
References to other published versions of this review
Cooper 2020
- Cooper TE, Khalid R, Craig JC, Hawley CM, Howell M, Johnson DW, et al. Synbiotics, prebiotics and probiotics for people with chronic kidney disease. Cochrane Database of Systematic Reviews 2020, Issue 5. Art. No: CD013631. [DOI: 10.1002/14651858.CD013631] [DOI] [PMC free article] [PubMed] [Google Scholar]