Evaluation of effect of cooled haemodialysis on cognition in patients with end-stage kidney disease (ECHECKED) feasibility randomised controlled trial results
Bibliographic record
Abstract
BACKGROUND: Cognitive impairment is common in haemodialysis patients with no known beneficial interventions. Cooler dialysate slows brain white-matter changes, but its effect on cognition is unknown. This feasibility trial was performed to inform a fully-powered, randomised trial to assess this. METHODS: We aimed to randomise (1:1) 90 haemodialysis patients to this double-blinded, randomised controlled feasibility trial to standard care (dialysate-temperature 36.5 °C) or intervention (35 °C). Eligible patients were adult chronic haemodialysis recipients with no established diagnosis of dementia or psychiatric disease. The primary outcome was change in Montreal Cognitive Assessment (MoCA) score at 12-months. Secondary outcomes included recruitment and attrition rates, reasons for non-recruitment, intradialytic hypotension, depression, patient burden, computerised cognition test battery, and quality of life. FINDINGS: Of 334 patients screened, 160 were eligible. 99 declined mainly for the extra non-dialysis day study visits. Sixty-one patients consented, 43 randomised - 20 in standard care, 23 in intervention arms; 13 withdrew for non-dialysis day visits and 5 without reason before randomisation. 27 patients (12 standard care, 15 intervention) completed the trial - 5 died, 1 transplanted, 4 withdrew consent, and 6 could not attend due to the pandemic. Low temperature dialysis was well tolerated. There was no difference in change in MoCA from baseline to 12 months between the standard and intervention arms; 1.0 (-2.8-3.0, p = 0.755) and - 2.0 (-1.0 - -4.0, p = 0.047) respectively. There were no differences between groups on any secondary measures. There were no significant adverse events reported. DISCUSSION: The trial was significantly affected by the COVID-19 pandemic contributing to an attrition rate of 27%. The non-dialysis day research visits were mainly responsible for low recruitment and consent withdrawal. There are several learning points, described in the article, which will inform design of definitive trials in this area in the future. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT03645733. Registration date 24/08/2018.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".