Dialysate temperature reduction for intradialytic hypotension for people with chronic kidney disease requiring haemodialysis

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

This review aims to evaluate the benefits and harms of dialysate temperature reduction for IDH among patients with CKD requiring HD, compared with standard dialysate temperature. In addition, we will compare the benefits and harms of different types of dialysate temperature reduction for IDH.

Background

Description of the condition

Chronic kidney disease (CKD) is a global concern. According to the 2010 Global Burden of Disease study, CKD was ranked 27th in the list of causes of total number of global deaths in 1990 (age‐standardised annual death rate of 15.7 per 100,000), but rose to 18th in 2010 (annual death rate 16.3 per 100,000) (Lozano 2012). The number of end‐stage kidney disease (ESKD) patients receiving renal replacement therapy (RRT) was more than 2 million in 2011, and increased approximately 8% annually (Couser 2011; White 2008). Haemodialysis (HD) is the main modality of RRT, with almost 90% of dialysis patients under maintenance HD (Jain 2012). Patients with maintenance HD gain weight because of their disability to urine excretion. The excess water is removed by ultrafiltration during HD.

Intradialytic hypotension (IDH) is common complication of HD, and the result of an inadequate cardiovascular response to the reduction in blood volume that occurs when the ultrafiltration volume is large (Palmer 2008). IDH is defined as a decrease in systolic blood pressure (SBP) of ≥ 20 mm Hg or a decrease in mean arterial pressure (MAP) of 10 mm Hg, and is associated with hypotensive symptoms such as dizziness, weakness, nausea, cramps, blurred vision, and fatigue (K/DOQI 2005; Santoro 2002). The pathophysiology of IDH is diverse. One process may involve an imbalance between a reduced effective circulating volume and the compensatory plasma refilling mechanism, where in fluid from the interstitial and intracellular space is translocated into the intravascular compartment (Nesrallah 2013). Additionally, IDH can also be induced by several vasoactive substances such as adenosine or nitric oxide, which may be synthesized or released during dialysis (Sulowicz 2006). Recent studies have shown that haemodynamic instability is associated with impaired baroreflex sensitivity; a decrease in asymmetric dimethyl arginine (ADMA), a naturally occurring nitric oxide synthase inhibitor; and inadequate vasopressin response (Chesterton 2010; Csiky 2008; Dubin 2011; Thompson 2009). Another study using echocardiography suggests that a blood pressure (BP) drop within a HD session is associated with HD‐induced myocardial stunning (Burton 2009). Repeated decreases in organ perfusion due to IDH can introduce chronic organ injury over time (Nesrallah 2013). Moreover, several studies have shown an association between IDH and cardiovascular morbidity and mortality (Burton 2009; Sands 2014; Shoji 2004; Stefansson 2014; Tisler 2003). IDH also associated with vascular access thrombosis, dysrhythmias, and mesenteric venous infarction (K/DOQI 2005). Risk factors associated with IDH include old age, female gender, Hispanic ethnicity, long dialysis vintage, high intradialytic weight gain, high dialysis dose, diabetes, low predialysis BP, high osmolarity, and high body mass index (Mc Causland 2013; Mc Causland 2015; Sands 2014; Stefansson 2014). Haemofiltration (HF) and haemodiafiltration (HDF) can reduce the frequency of IDH, compared with HD (Locatelli 2010).

Description of the intervention

Dialysate is heated by heating elements in the HD machine as the blood temperature is decreasing through an extracorporeal circuit. The widely used dialysate temperature is 37°C (Daugirdas 2007; K/DOQI 2005; Toth‐Manikowski 2016). The body temperature is likely to increase during standard dialysis with the dialysate temperature of 37°C (Rosales 2000). The dialysis procedure itself affects body temperature regulation. There have been several clinical studies that investigated the effect of reduction of dialysate temperature for haemodynamic stability (Jost 1993; Maggiore 2002; van der Sande 2009; Zitt 2008). A simple intervention for lowering blood temperature is fixed empirical reduction of dialysate temperature. Alternative interventions are implemented by monitoring blood temperature (core temperature) in the arterial and venous bloodline (Selby 2006). This biofeedback system can adjust the dialysate temperature in response to the calculated body temperature and enable the implementation of isothermic dialysis, in which arterial temperature remains unchanged from the patient’s baseline level (van der Sande 2009). In contrast, lower dialysate temperature may cause high frequency of discomfort, cold sensation or shivering (K/DOQI 2005).

How the intervention might work

Peripheral and cutaneous vasoconstriction is considered an important component for the ultrafiltration‐induced decrease in blood volume (Schneditz 2003). HD patients tend to be hypovolaemic as ultrafiltration progresses during HD (Palmer 2008). Hypovolaemia causes underfilling in the cardiac chambers, then cardiovascular response increases the arteriolar or venous tone. However, patients with impaired cardiovascular response cannot offset the volume reduction, and suffer a drop in BP (Santoro 2002). In general, a decrease in body temperature is associated with a decrease in blood flow to the compliant cutaneous circulation, an increase in total peripheral resistance, and an increase in BP (Schneditz 2003). A study reported that left ventricular contractility increased during cool dialysis (Levy 1992), while another observed that SBP was higher in cool dialysate group but core temperature remained stable during dialysis (van der Sande 1999). Removal of heat with cool dialysate might activate autoregulatory mechanisms to preserve core temperature, which results in beneficial haemodynamic stability. In addition, a recent trial showed the protective effect of cooling dialysate on dialysis‐induced ischaemic brain injury (Eldehni 2015).

Why it is important to do this review

IDH remains an issue for chronic HD patients. The frequency of IDH was reported as 20% to 30% among patients undertaking HD (Palmer 2008). In addition, the incidence of IDH is likely to rise because increasing the number of older patients is expected to develop ESKD (K/DOQI 2005). Since IDH could introduce clinically relevant complications such as mortality and cardiovascular morbidity, evaluation of easy, cost‐effective, and safe intervention should be evaluated to address this problem. Reduction of dialysate temperature could be an easy intervention for preventing IDH. The intervention could also be applied to patients in various settings because standard dialysis consoles have a dialysate temperature regulator; therefore, it can be applied universally and reduce the need for nursing involvement (Eldehni 2015; Toth‐Manikowski 2016). Further, no additional cost is needed to conduct fixed reduction of dialysate temperature. While there are various methods of reducing dialysate temperature, optimal degree or types of reduction of the temperature to prevent IDH remains uncertain (Maggiore 2002; Santoro 2002; Selby 2006; Toth‐Manikowski 2016). A recent systematic review has reported the effect of cooling dialysis on IDH; however, the study has several limitations, including incomplete reporting of risk of bias, exclusion of comparisons between different types of cooling methods, and exclusion of children and modalities other than HD (Mustafa 2016). To that end, we will conduct a systematic review of the effects and harms of reduction of dialysate temperature.

Objectives

This review aims to evaluate the benefits and harms of dialysate temperature reduction for IDH among patients with CKD requiring HD, compared with standard dialysate temperature. In addition, we will compare the benefits and harms of different types of dialysate temperature reduction for IDH.

Methods

Criteria for considering studies for this review

Types of studies

We will include all published, unpublished and ongoing randomised controlled trials (RCTs) to compare the reduction of dialysate temperature and normal temperature for IDH in HD patients.

Cluster RCTs will be eligible if the number of clusters or the average size of each cluster, the outcome data ignoring cluster design for the total number of individuals, and an estimate of intracluster (or intraclass) correlation coefficient (ICC) are available.

We will include data from cross‐over RCTs but will only consider data from the first period.

We will include quasi‐randomised trials (RCTs in which allocation to treatment was obtained by alternation, use of alternate medical records, date of birth or other predictable methods) but exclude observational studies. No language restriction will be applied.

Types of participants

Inclusion criteria

All patients undergoing maintenance HD, HF, or HDF with minimal dialysis vintage of three months.

Exclusion criteria

• Patients on peritoneal dialysis

• Patients undergoing continuous RRT

• Patients undergoing sustained low‐efficiency dialysis (SLED)

• Patients undergoing home HD.

Types of interventions

The experimental conditions are any methods of reduction of dialysate temperature. We will consider the following comparisons.

1. Fixed reduction of dialysate temperature (below 36°C) versus standard dialysate temperature (37°C to 37.5°C)

2. Reduction of core temperature (below 36°C) using biofeedback device versus standard dialysate temperature (37°C to 37.5°C)

3. Isothermic dialysis defined as maintenance of core temperature using biofeedback device versus standard dialysate temperature (37°C to 37.5°C)

4. Reduction of arterial temperature using biofeedback device versus fixed reduction of dialysate temperature (below 36°C)

5. Isothermic dialysis defined as maintenance of artery temperature using biofeedback device versus fixed reduction of dialysate temperature (below 36°C)

6. Reduction of arterial temperature using biofeedback device versus isothermic dialysis defined as maintenance of arterial temperature using biofeedback device

7. Any other methods of reduction of dialysate temperature versus standard dialysate temperature (37°C to 37.5°C).

Types of outcome measures

Primary outcomes

1. IDH rate (the proportion of dialysis sessions with episodes of IDH during follow‐up) defined as follows.

   • Intradialytic decrease in SBP by 20 mm Hg or more, or a decrease in MAP by 10 mm Hg associated with symptoms that include abdominal discomfort, yawning, sighing, nausea, vomiting, muscle cramps, restlessness, dizziness, and anxiety (K/DOQI 2005)

   • Decrease in SBP by 20 mm Hg or more, or in MAP by 10 mm Hg or more, associated with a clinical event and the need for nursing intervention (Kooman 2007)

   • Drop in SBP to < 90 mm Hg or an absolute value > 30 mm Hg, associated with symptoms of hypotension and lack of response to the supine position but necessitating resuscitation with intravenous normotonic or hypertonic fluid administration (Tisler 2003)

   • Decrease in SBP of at least 10 mm Hg or a SBP of < 100 mm Hg, with symptoms such as cramps, nausea, vomiting, and dizziness (Fortin 2010)

   • Drop in SBP < 90 mm Hg or of at least 20 mm Hg with accompanying clinical symptoms (Maheshwari 2015)

   • Hypotensive episode requiring either saline infusion, lowering of the ultrafiltration rate (UF) or reduction in blood flow during HD session (Mc Causland 2013)

   • Intradialytic decrease in SBP by > 30 mm Hg to a level of < 90 mm Hg (Sands 2014)

   • 40 mm Hg drop in SBP (Shoji 2004)

   • Similar to above criteria will be accepted.

2. All‐cause mortality

3. 3. Discomfort rate defined as cold sensation, shivering, and related symptoms.

Secondary outcomes

1. Acute coronary syndrome: diagnosis based on electrocardiographic changes, elevation of enzymes or confirmed during post‐mortem examination

2. All strokes: sudden focal neurologic deficit caused by cerebrovascular thrombosis, and categorized as ischaemic, haemorrhagic, or unspecified

3. Quality of life measured by a validated scale system such as Kidney Disease Quality of Life (KDQoL), or Choices for Healthy Outcomes in Caring for ESRD (CHOICE) Health Experience Questionnaire (CHEQ) (Hays 1994; Wu 2001).

4. Dropout rate due to adverse events

5. Rate of vasoconstrictor use

6. Lowest SBP during dialysis

7. Lowest body temperature during dialysis

8. Urea clearance‐based dialysis adequacy (Kt/V_urea)

9. Vascular thrombosis defined as an access that has clotted, without blood flow

10. New onset dysrhythmias

11. Mesenteric venous thrombosis

12. Post‐HD fatigue measured by a validated scale system such as the Fatigue Severity Scale (Krupp 1989).

Search methods for identification of studies

Electronic searches

We will search the Cochrane Kidney and Transplant Specialised Register through contact with the Information Specialist using search terms relevant to this review. The Specialised Register contains studies identified from the following sources.

1. Monthly searches of the Cochrane Central Register of Controlled Trials (CENTRAL)

2. Weekly searches of MEDLINE OVID SP

3. Handsearching of kidney‐related journals and the proceedings of major kidney conferences

4. Searching of the current year of EMBASE OVID SP

5. Weekly current awareness alerts for selected kidney and transplant journals

6. Searches of the International Clinical Trials Register (ICTRP) Search Portal and ClinicalTrials.gov.

Studies contained in the Specialised Register are identified through search strategies for CENTRAL, MEDLINE, and EMBASE based on the scope of Cochrane Kidney and Transplant. Details of these strategies, as well as a list of handsearched journals, conference proceedings and current awareness alerts, are available in the Specialised Register section of information about Cochrane Kidney and Transplant.

See Appendix 1 for search terms used in strategies for this review.

Searching other resources

1. Reference lists of review articles, relevant studies and clinical practice guidelines.

2. Letters seeking information about unpublished or incomplete trials to investigators known to be involved in previous studies.

Data collection and analysis

Selection of studies

The search strategy described will be used to obtain titles and abstracts of studies that may be relevant to the review. The titles and abstracts will be screened independently by two authors, who will discard studies that are not applicable; however, studies and reviews that might include relevant data or information on studies will be retained initially. Two authors will independently assess retrieved abstracts and, if necessary, the full text of these studies to determine which studies satisfy the inclusion criteria.

Data extraction and management

Data extraction will be carried out independently by two authors using a structured, pilot‐tested Excel data extraction form. Any disagreement will be resolved by discussion with a further author acting as an arbiter. The data extraction form included the following items.

• General information: title, authors, year of publication, trial registration number, language, and country

• Study characteristics including design, and setting

• Participants: total number, number of each age, sex, and comorbidity

• Interventions and comparisons: types of reduction of dialysate, duration, and co‐intervention

• Outcome: definition of outcomes, number of participants allocated, number of missing participants, number of events (dichotomous outcomes), standard deviation and mean (continuous outcomes)

• Risk of bias and publication status.

Studies reported in non‐English language journals will be translated before assessment. Where more than one publication of one study exists, reports will be grouped together and the publication with the most complete data will be used in the analyses. Where relevant outcomes are only published in earlier versions, these data will be used. Any discrepancy between published versions will be highlighted.

Assessment of risk of bias in included studies

The following items will be independently assessed by two authors using the risk of bias assessment tool (Higgins 2011) (Appendix 2).

• 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 a risk of bias?

Measures of treatment effect

Dichotomous outcomes results will be expressed as risk ratio (RR) with 95% confidence intervals (CI). For rate outcomes, results will be expressed as rate ratio with 95% CI.

Where continuous scales of measurement are used to assess the effects of treatment (BP, body temperature, and heart rate), the mean difference (MD) or the standardised mean difference (SMD) will be used, if different scales have been used.

If the studies included in a review may include a mixture of change‐from‐baseline and final value scores, we will use the (unstandardised) mean difference method in RevMan according to Chapter 9.4.5.2 of the Cochrane handbook (Higgins 2011).

Unit of analysis issues

Cluster randomised studies

For dichotomous data, we will apply the design effect and calculate effective sample size and number of events using ICC and the average cluster size, as described in chapter 16.3.5 of the Cochrane handbook (Higgins 2011).

If ICC hasn't been reported, we will use ICC of similar study as a substitute. For continuous data, only the sample size will be reduced; means and standard deviation will remain unchanged (Higgins 2011).

Randomised cross‐over studies

We will consider only data from the first period.

Multiple arm studies may be found and included. In such cases, all intervention groups that are relevant to the review will be included.

Dealing with missing data

Any further information required from the original author will be requested by written correspondence (e.g. emailing or writing to corresponding authors) and any relevant information obtained in this manner will be included in the review. Evaluation of important numerical data such as screened, randomised patients as well as intention‐to‐treat, as‐treated and per‐protocol population, will be carefully performed. Attrition rates, for example drop‐outs, losses to follow‐up and withdrawals will be investigated. Issues of missing data and imputation methods (for example, last‐observation‐carried‐forward) will be critically appraised (Higgins 2011).

Assessment of heterogeneity

We will first assess the heterogeneity by visual inspection of the forest plot. Heterogeneity will then be analysed using a Chi² test on N‐1 degrees of freedom, with an alpha of 0.10 used for statistical significance since we expect that there are not many relevant studies, and with the I² test (Higgins 2003). A guide to the interpretation of I² values will be 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 confidence interval for I²) (Higgins 2011).

Assessment of reporting biases

We will first assess the heterogeneity by visual inspection of the forest plot.

If the number of eligible studies is 10 or more, Egger’s test will be used to assess for the potential existence of reporting bias (Higgins 2011).

Data synthesis

Data will be pooled using the random‐effects model.

Subgroup analysis and investigation of heterogeneity

Subgroup analysis for primary outcomes will be used to explore possible sources of heterogeneity. We will treat a trial as a subgroup with a covariate if more than 80% of the included participants in a trial have a covariate. We will test the following subgroups.

• Age: children (< 18 years), adults (18 to 75 years), and elderly (≥ 75 years)

• Comorbid conditions: history of diabetes mellitus, acute coronary syndrome, IDH, and current use of antihypertensive drugs

• Dialysis vintage: < 10 years and ≥ 10 years

• Dialysis modality: HD, HF, HDF

• We will perform the following subgroup analysis for IDH outcome:

  • IDH definition: IDH defined by symptoms or intervention for hypotensive episode (e.g. saline flush, or lowering of the UF), and IDH defined by SBP irrespective of symptoms or intervention.

Adverse effects will be tabulated and assessed with descriptive techniques, as they are likely to be different for the various agents used. Where possible, the risk difference with 95% CI will be calculated for each adverse effect, either compared with no treatment or with another agent.

Sensitivity analysis

We will perform sensitivity analyses in order to explore the influence of the following factors on effect size:

• Repeating the analysis excluding unpublished studies

• Repeating the analysis restricting study with low risk of selection bias (i.e. adequate random sequence generation and random allocation)

• Repeating the analysis excluding any very long or large studies to establish how much they dominate the results

• Repeating the analysis using fixed effect model instead of random effects model

• Repeating the analysis with restriction of the study to a trial protocol which excludes co‐interventions for IDH, such as mannitol, hypertonic saline, or vasoconstrictors.

'Summary of findings' tables

We will present the main results of the review in 'Summary of findings' tables. These tables present key information concerning the quality of the evidence, the magnitude of the effects of the interventions examined, and the sum of the available data for the main outcomes (Schunemann 2011a).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).

The GRADE approach defines the quality 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. The quality 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 (Schunemann 2011b).

We plan to present the following outcomes in the 'Summary of findings' tables.

• All‐cause mortality

• Acute coronary syndrome

• All strokes

• IDH rate

• Rate of dropout due to adverse events

• Discomfort rate.

Appendices

Appendix 1. Electronic search strategies

Database	Search terms
CENTRAL	dialysis:ti,ab,kw hemodialysis or haemodialysis):ti,ab,kw hemodiafiltration or haemodiafiltration):ti,ab,kw (hemofiltration or haemofiltration):ti,ab,kw {or #1‐#4} (dialysis next solution*):ti,ab,kw ((hemodialysis next solution*) or (haemodialysis next solution*)):ti,ab,kw (dialysis next fluid*):ti,ab,kw ((hemodialysis next fluid*) or (haemodialysis next fluid*)):ti,ab,kw dialy*ate*:ti,ab,kw {or #6‐#10} temperature:ti,ab,kw heat*:ti,ab,kw cold*:ti,ab,kw cool*:ti,ab,kw warm*:ti,ab,kw tepid:ti,ab,kw lukewarm:ti,ab,kw {or #12‐#18} {and #5, #11, #19}
MEDLINE	Renal Replacement Therapy/ Renal Dialysis/ Hemodiafiltration/ Hemodialysis, home/ exp Hemofiltration/ dialysis.tw. (hemodialysis or haemodialysis).tw. (hemofiltration or haemofiltration).tw. (hemodiafiltration or haemodiafiltration).tw. or/1‐9 exp Dialysis Solutions/ dialysis solution$.tw. dialysis fluid$.tw. (hemodialysis solution$ or haemodialysis solution$).tw. (hemodialysis fluid$ or haemodialysis fluid$).tw. dialy#ate$.tw. or/11‐16 exp Temperature/ temperature.tw. reduc$.tw. heat$.tw. cool$.tw. cold$.tw. warm$.tw. tepid.tw. lukewarm.tw. or/18‐26 and/10,17,27
EMBASE	exp renal replacement therapy/ extended daily dialysis/ hemodialysis/ home dialysis/ hemofiltration/ hemodiafiltration/ dialysis.tw. (hemodialysis or haemodialysis).tw. (hemofiltration or haemofiltration).tw. (hemodiafiltration or haemodiafiltration).tw. renal replacement therapy‐dependent renal disease/ or/1‐11 Hemodialysis Fluid/ Dialysis Fluid/ Dialysate/ dialysis solution$.tw. dialysis fluid$.tw. (hemodialysis solution$ or haemodialysis solution$).tw. (hemodialysis fluid$ or haemodialysis fluid$).tw. dialy#ate$.tw. or/13‐20 Temperature/ Heat/ Cold/ High Temperature/ Low Temperature/ temperature.tw. heat$.tw. cool$.tw. cold$.tw. warm$.tw. tepid.tw. lukewarm.tw. or/22‐33 and/12,21,34

Appendix 2. 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.

Contributions of authors

1. Draft the protocol: YT, HT, YN, YK, MK, SS, TI, S Fukuma, YY, S Fukuhara

2. Study selection: YT, HT

3. Extract data from studies: YT, HT

4. Enter data into RevMan: YT

5. Carry out the analysis: YT, YN, YK, MK, YY

6. Interpret the analysis: YT, HT, YK, MK, SS, TI, S Fukuma, YY, S Fukuhara

7. Draft the final review: YT

8. Disagreement resolution: YK

9. Update the review: YT, HT, YN, YK, MK, SS, TI, S Fukuma, YY, S Fukuhara

Declarations of interest

All authors declare there are no conflict of interests.

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