Is there an association between subjective sleep quality and daily delirium occurrence in critically ill adults? A post hoc analysis of a randomised controlled trial
Bibliographic record
Abstract
OBJECTIVES: Whether and how delirium and sleep quality in the intensive care unit (ICU) are linked remains unclear. A recent randomised trial reported nocturnal low-dose dexmedetomidine (DEX) significantly reduces incident ICU delirium. Leeds Sleep Evaluation Questionnaire (LSEQ) scores were similar between intervention (DEX; n=50) and control (placebo (PLA); n=50) groups. We measured the association between morning LSEQ and delirium occurrence in the prior 24 hours (retrospective analysis) and the association between morning LSEQ and delirium occurrence in the following 24 hours (predictive analysis). DESIGN: Post hoc analysis of randomised controlled trial data. PARTICIPANTS: Adult ICU patients (n=100) underwent delirium screening twice a day using the Intensive Care Delirium Screening Checklist (ICDSC) if Richmond Agitation Sedation Scale (RASS) was ≥-3 and patient-reported sleep quality evaluations at 09:00 daily with the LSEQ if RASS was ≥-1. OUTCOMES: The analysis included all 24-hour study periods with LSEQ documentation and matched delirium screening in coma-free patients. Separate logistic regression models controlling for age, baseline Acute Physiology and Chronic Health Evaluation II score and DEX/PLA allocation evaluated the association between morning LSEQ and delirium occurrence for both retrospective and predictive analyses. RESULTS: The 100 patients spent 1115 24-hour periods in the ICU. Coma, delirium and no delirium occurred in 130 (11.7%), 114 (10.2%) and 871 (78.1%), respectively. In the retrospective analysis, when an LSEQ result was preceded by an ICDSC result (439/985 (44.6%) 24-hour periods), delirium occurred during 41/439 (9.3%) periods. On regression analysis, the LSEQ score had no relationship to prior delirium occurrence (OR (per every 1 point average LSEQ change) 0.97, 95% CI 0.72 to 1.31). For the predictive analysis, among the 387/985 (39.1%) 24-hour periods where an LSEQ result was followed by an ICDSC result, delirium occurred during 56/387 (14.5%) periods. On regression analysis, the LSEQ score did not predict subsequent delirium occurrence (OR (per 1 point LSEQ change) 1.02, 95% CI 0.99 to 1.05). CONCLUSIONS: The sleep quality ICU patients perceive neither affects nor predicts delirium occurrence. TRIAL REGISTRATION NUMBER: NCT01791296.
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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 | 0.025 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.013 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".