Interventions for preventing haemodialysis dysequilibrium syndrome

Objectives

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

This review aims to look at the benefits and harms of interventions for preventing HD DDS.

Background

Description of the condition

Dialysis disequilibrium syndrome (DDS) refers to a range of neurological symptoms seen in patients during or after haemodialysis (HD), particularly in those who are newly started or following reinitiation of HD after missing multiple sessions (Arieff 1994). The incidence of DDS is not known and may have reduced owing to early initiation of dialysis and awareness of this condition but may be under reported due to its non‐specific symptomatology (Mistry 2019). First HD treatment, elevated blood urea level at the start of dialysis, extremes of age, and pre‐existing neurological conditions are considered common risk factors for developing DDS (Mistry 2019). 

The symptoms of DDS are due to cerebral oedema. The exact mechanism of which has not been elucidated. 'The reverse urea effect' is one theory proposed to explain cerebral oedema in DDS (Trinh‐Trang‐Tan 2005). During HD, differential removal of urea from blood compared to brain cells may generate an osmotic gradient which causes a shift of water into neurons leading to cerebral oedema. Other proposed theories to explain mechanisms of cerebral oedema are reduction in intracellular pH or increase of organic osmolytes in brain cells (Arieff 1976; Silver 1996).

Clinical manifestations of DDS may vary from mild to severe. Headache, nausea, blurred vision, and restlessness are mild manifestations. Somnolence, confusion and disorientation are moderate symptoms. Severe manifestations include seizures, stupor, coma and death. DDS is a clinical diagnosis made after excluding all other neurological conditions. 

Treatment of DDS is difficult, and hence the focus is on preventing the condition. Early recognition and timely prevention are crucial for DDS patients (Raina 2022). A number of interventions have been used in people at risk of DDS either to reduce urea clearance when initiating dialysis or to reduce transcellular osmotic shifts. 

Description of the intervention

Based on limited understanding of the pathophysiology of DDS, two main approaches have been used to prevent DDS:

Interventions to limit the clearance of blood urea

1. Lowering the dialysis blood flow

2. Lowering the dialysate flow

3. Using a low surface area dialyser

4. Shortening the length of the dialysis session

Interventions to limit osmotic shift during dialysis

1. Modelling the dialysate sodium concentration

2. Use of hypertonic solutions (mannitol, hypertonic saline)

3. Using dialysate with high glucose concentration

4. Adding urea into the dialysate

These interventions may be used alone or in combination for patients. 

How the intervention might work

Interventions to prevent DDS aim to mitigate the osmotic shifts by reducing urea clearance or administering an alternative osmotic agent. Interventions used include low blood flow during initial sessions of dialysis, using a small surface area dialyser, reducing dialysate flow rate, and short dialysis sessions ‐ all aimed at avoiding rapid reductions in blood urea.

Other interventions include modelling dialysate sodium and using intravenous (IV) hypertonic solutions like mannitol or hypertonic saline during or after dialysis to mitigate osmotic shifts associated with rapid blood urea removal.  

Why it is important to do this review

DDS is a clinical condition which may be under‐reported and under‐recognised but has morbidity and is potentially fatal. Interventions used at present to prevent DDS are based on presumed pathophysiologic mechanisms with the absence of evidence‐based guidelines regarding their efficacy and safety. We also do not know which patient is "at risk" of DDS. There is a need to collate available knowledge on interventions to prevent DDS regarding their benefits and harms. Though it is believed that the incidence of DDS is less in peritoneal dialysis (PD) and slow convective therapies, these modalities are not easily accessible and uniformly available for all. This review may aid clinicians in an evidence‐based approach to managing patients at risk of DDS.

Objectives

This review aims to look at the benefits and harms of interventions for preventing HD DDS.

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) looking at the interventions for preventing DDS in people receiving  HD. We will include published and unpublished studies, provided they are reported in full‐text or abstract format.

Types of participants

Inclusion criteria

• Chronic kidney disease (CKD stage 5D) or acute kidney injury (AKI) initiated on HD

• Adults and children

• Patients re‐initiated on HD after missed sessions of HD

Exclusion criteria

Patients initiated on dialysis using slow convective therapies or PD will be excluded. 

Types of interventions

All interventions used for preventing DDS compared with each other or standard care will be included in the review.

• High glucose dialysate versus placebo/standard care

• IV mannitol versus placebo/standard care

• Hypertonic saline versus placebo/standard care

• High glucose dialysate/IV mannitol/hypertonic saline versus each other and in combination

• Short duration dialysis: ≤ 2 hours versus ≥ 2 hours

• Low blood flow rate: ≤ 200 mL/min versus ≥ 200 mL/min

• Low dialysate flow rate: ≤ 300 mL/min versus ≥ 300 mL/min

• Sodium modelling versus placebo

• Low efficiency dialyser: < 500 mL/min KoA versus other interventions/placebo

• Low dialysate bicarbonate: < 35 mEq/L versus placebo/other interventions

• Co‐current flow of dialysate versus placebo/other interventions

• Newer interventions versus standard care

Types of outcome measures

This review will 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

Development of DDS. DDS will be defined as the appearance of any of the following symptoms which appear during or after the initial HD session, and other causes have been ruled out:

• Headache, nausea, blurred vision, and restlessness. somnolence, confusion and disorientation, seizures, stupor, coma and death. 

If the definition of the primary outcomes is not provided explicitly in the study, we will try to contact the authors for further information. If no information was available on how the DDS was defined, we will still include the data from that study, but we will do a sensitivity analysis to assess if the inclusion/exclusion of the study altered our findings and conclusions.

Secondary outcomes

1. Death (any cause)

2. Severe DDS: seizures, stupor, coma and death

3. Duration of hospital stay

4. Adverse events (e.g. hypotension, hypertension, ventilator requirement)

Search methods for identification of studies

Electronic searches

We will search the Cochrane Kidney and Transplant Register of Studies through contact with the Information Specialist using search terms relevant to this review. The 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. Searches of kidney and transplant journals and the proceedings and abstracts from major kidney and transplant conferences

4. Searching 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 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 under CKT Register of Studies.

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. Contacting relevant individuals/organisations seeking information about unpublished or incomplete studies.

3. Grey literature sources (e.g. abstracts, dissertations and theses), in addition to those already included in the Cochrane Kidney and Transplant Register of Studies, will be searched.

Data collection and analysis

Selection of studies

The search strategies 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. Disagreements will be resolved in consultation with a third author.

Data extraction and management

Data extraction will be carried out independently by two authors using standard data extraction forms. Disagreements will be resolved in consultation with a third author. 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 2022) (see 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 risk of bias?

Measures of treatment effect

For dichotomous outcomes (e.g. DDS, seizures, coma, adverse events and death), results will be expressed as risk ratio (RR) with 95% confidence intervals (CI). Where continuous scales of measurement are used to assess the effects of treatment (e.g. hospital stay, urea reduction ratio (URR), serum sodium, serum bicarbonate), the mean difference (MD) will be used, or the standardised mean difference (SMD) if different scales have been used.

For outcome measurements, the change from baseline will be the most preferred data to use. We will use the end‐of‐treatment value if change from baseline data are not available. 

Adverse effects will be tabulated and assessed with descriptive techniques, as they are likely to be different for the various interventions used. Where possible, the risk difference with 95% CI will be calculated for each adverse effect, compared to the other intervention.

Unit of analysis issues

We will only include the randomisation of the individual participant. We will not include cluster RCTs or cross‐over studies. If we identify multi‐arm trials, where two or more active treatment arms are compared with a placebo or control arm, we will avoid double‐counting of participants in the placebo/control arm by splitting the total number between the active arms. 

Dealing with missing data

Any further information required from the original author will be requested by written correspondence (e.g. emailing and/or writing to the corresponding author), and any relevant information obtained in this manner will be included in the review. Evaluation of important numerical data, such as screened, randomised patients, 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 2022).

Assessment of heterogeneity

We will first assess the heterogeneity by visual inspection of the forest plot. We will quantify statistical heterogeneity using the I² statistic, which describes the percentage of total variation across studies due to heterogeneity rather than sampling error (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 CI for I²) (Higgins 2022).

Assessment of reporting biases

If possible, funnel plots will be used to assess for the potential existence of small study bias (Higgins 2022).

Data synthesis

We will only pool data if studies are sufficiently similar in terms of heterogeneity. Data will be pooled using the random‐effects model, but the fixed‐effect model will also be used to ensure the robustness of the model chosen and susceptibility to outliers.

Subgroup analysis and investigation of heterogeneity

We will conduct subgroup analyses to explore possible sources of heterogeneity.

• Age: < 18 years versus ≥ 18 years

• Comorbidities: diabetics versus non‐diabetics

• Dialysis: new initiation versus "reinitiation" after missed sessions

• Glycaemic status: hyperglycaemia versus normoglycaemia

• Patients with and without pre‐existing neurological disease. 

Sensitivity analysis

We will perform sensitivity analyses 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 will present 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 (Schunemann 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 will be assessed by two authors. The certainty of a body of evidence involves consideration of within‐trial risk of bias (methodological quality), directness of evidence, heterogeneity, the precision of effect estimates and risk of publication bias (Schunemann 2022b). We plan to present the following outcomes in the 'Summary of findings' tables.

• Incidence of DDS

• Death

• Severe DDS

• Duration of hospital stay

• Adverse events

If no data for individual outcomes are available, that row in the table will be identified by stating 'data not reported'.

Appendices

Appendix 1. Electronic search strategies

Database	Search terms
CENTRAL	((dialysis or hemodialysis or haemodialysis or hemodiafiltration or haemodiafiltration or hemofiltration or haemofiltration or renal replacement or uremia)):ti,ab,kw (disequilibrium or dis‐equilibrium or disequilibrium or dysequilibrium) #1 AND #2
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. uremia/ or/1‐10 disequilibr*.tw. dysequilibr*.tw. dis‐equilibr*.tw. or/12‐14 and/11,15
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/ uremia/ or/1‐12 disequilibr*.tw. 2 dis‐equilibr*.tw. dysequilibr*.tw. or/14‐16 and/13,17

 

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: MK, RP, IR, SP

2. Study selection: MK, RP, IR

3. Extract data from studies: MK, RP, IR

4. Enter data into RevMan: MK, RP, IR

5. Carry out the analysis: MK, RP

6. Interpret the analysis: MK, RP

7. Draft the final review: MK, SP

8. Disagreement resolution: SP, IR

9. Update the review: MK, RP

Sources of support

Internal sources

• No internal support, Other

External sources

• No external support, Other

Declarations of interest

• Manjunath Kulkarni: no relevant interests were disclosed

• Attur Ravindra Prabhu: no relevant interests were disclosed

• Indu Ramachandra Rao: no relevant interests were disclosed

• Shankar Prasad Nagaraju: no relevant interests were disclosed

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