Evaluation of the effect of Cooled HaEmodialysis on Cognitive function in patients suffering with end-stage KidnEy Disease (E-CHECKED): feasibility randomised control trial protocol
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is common in haemodialysis (HD) patients and is associated independently with depression and mortality. This association is poorly understood, and no intervention is proven to slow cognitive decline. There is evidence that cooler dialysis fluid (dialysate) may slow white matter changes in the brain, but no study has investigated the effect of cooler dialysate on cognition. This study addresses whether cooler dialysate can prevent the decline in cognition and improve quality of life (QOL) in HD patients. METHODS: This is a multi-site prospective randomised, double-blinded feasibility trial. SETTING: Four HD units in the UK. PARTICIPANTS AND INTERVENTIONS: Ninety HD patients randomised (1:1) to standard care (dialysate temperature 36.5 °C) or intervention (dialysate temperature 35 °C) for 12 months. PRIMARY OUTCOME MEASURE: Change in cognition using the Montreal Cognitive Assessment (MoCA). SECONDARY OUTCOME MEASURES: Recruitment and attrition rates, reasons for non-recruitment, frequency of intradialytic hypotension, depressive symptom scores, patient and carers burden, a detailed computerised cognitive test and QOL assessments. ANALYSIS: mixed method approach, utilising measurement of cognition, questionnaires, physiological measurements and semi-structured interviews. DISCUSSION: The results of this feasibility trial will inform the design of a future adequately powered substantive trial investigating the effect of dialysate cooling on prevention and/or slowing in cognitive decline in patients undergoing haemodialysis using a computerised battery of neuro-cognitive tests. The main hypothesis that would be tested in this future trial is that patients treated with regular conventional haemodialysis will have a lesser decline in cognitive function and a better quality of life over 1 year by using cooler dialysis fluid at 35 °C, versus a standard dialysis fluid temperature of 36.5 °C. This also should reflect in improvements in their abilities for activities of daily living and therefore reduce carers' burden. If successful, the treatment could be universally applied at no extra cost. TRIAL REGISTRATION: ClinicalTrials.gov NCT03645733 . Registered retrospectively on 24 August 2018.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.017 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.033 | 0.006 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".