Predialysis volume overload and patient‐reported sleep duration and quality in patients receiving hemodialysis
Bibliographic record
Abstract
INTRODUCTION: Previous studies of patients with end-stage renal disease have examined the role of fluid shifts on apnea-hypopnea episodes, but the association between volume overload and patient-reported sleep quality or duration has not been well-established. METHODS: We studied the association between predialysis bioimpedance spectroscopy-derived volume estimates and self-reported sleep quality and duration in 638 patients in the United States Renal Data System ACTIVE/ADIPOSE study receiving hemodialysis from 2009 to 2011. We used questionnaires to assess self-reported sleep duration and quality. We used relative hydration status (fluid overload/extracellular water; FO/ECW) as the primary predictor and examined associations with hours of sleep duration using linear regression. We used multivariable ordinal logistic regression to determine the association between categories of relative hydration status (normal hydration [FO/ECW < 6.8%], mild overhydration [FO/ECW 6.8%-15%], and hyperhydration [FO/ECW > 15%]) and four levels of difficulty with falling asleep, waking, and returning to sleep. FINDINGS: Higher relative hydration status was associated with fewer hours of sleep (-0.31 hours per 10%, 95% confidence interval (CI) -0.49 to -0.13). Compared to the normal hydration group, there was a statistically significant association between higher relative hydration status category and more frequent nighttime waking (OR: mild overhydration 1.92 [95% CI 1.23-2.99], hyperhydration 1.87 [95% CI 1.16-2.99]), a trend toward more difficulty returning to sleep (OR: mild overhydration 1.46 [95% CI 0.94-2.27], hyperhydration 1.52 [95% CI 0.95-2.43]), and no association between relative hydration category and difficulty falling asleep. DISCUSSION: Hydration status was associated with self-reported sleep duration in patients on dialysis. Future studies should prospectively examine the effects of optimizing fluid status on sleep duration and quality.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".