Effect of extended hours dialysis on sleep quality in a randomized trial
Bibliographic record
Abstract
AIM: Poor sleep quality is common in haemodialysis patients and associated with worse outcomes. In this pre-specified analysis, we examined the impact of extended hours haemodialysis on sleep quality. METHODS: The ACTIVE Dialysis trial randomized 200 participants to extended (≥24 h/week) or standard (target 12-15 h) hours haemodialysis over 12 months. Sleep quality was measured in the Kidney Disease Quality of Life Short Form 1.3 (KDQOL-SF) by overall sleep quality score (0-10, 10 = 'very good') and the sleep subscale (0-100, 100 = 'best possible sleep') every 3 months via blinded telephone interview. The average intervention effect was calculated by mixed linear regression adjusted by time point and baseline score. Factors predicting sleep quality were assessed by multivariate regression analysis. RESULTS: Overall sleep quality score and sleep subscale at baseline were similar in both groups (5.9 [95%CI 5.4-6.4] vs. 6.3 [5.9-6.8]; 65.0 [60.9-69.1] vs. 63.2 [59.1-67.3]; extended and standard hours, respectively). Extended hours haemodialysis led to a non-significant improvement in overall sleep quality score (average intervention effect 0.44 (-0.01 to 0.89), P = 0.053) and sleep subscale (average intervention effect 3.58 (-0.02 to 7.18), P = 0.051). Poor sleep quality was associated with being female and with current smoking. Sleep quality was positively associated with EuroQol-5D (EQ5D) and the SF-36 Physical Component and Mental Component Summary Scores but not with hospitalizations. CONCLUSION: Sleep quality was not significantly improved by extended hours dialysis in this study. Sleep quality is positively correlated with quality of life in haemodialysis patients and is poorer in women and current smokers.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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".