A Systematic Review of Risk Factors for Sleep Disruption in Critically Ill Adults
Bibliographic record
Abstract
OBJECTIVES: Numerous risk factors for sleep disruption in critically ill adults have been described. We performed a systematic review of all risk factors associated with sleep disruption in the ICU setting. DATA SOURCES: PubMed, EMBASE, CINAHL, Web of Science, Cochrane Central Register for Controlled Trials, and Cochrane Database of Systematic Reviews. STUDY SELECTION: English-language studies of any design published between 1990 and April 2018 that evaluated sleep in greater than or equal to 10 critically ill adults (> 18 yr old) and investigated greater than or equal to 1 potential risk factor for sleep disruption during ICU stay. We assessed study quality using Newcastle-Ottawa Scale or Cochrane Risk of Bias tool. DATA EXTRACTION: We abstracted all data independently and in duplicate. Potential ICU sleep disruption risk factors were categorized into three categories based on how data were reported: 1) patient-reported reasons for sleep disruption, 2) patient-reported ratings of potential factors affecting sleep quality, and 3) studies reporting a statistical or temporal association between potential risk factors and disrupted sleep. DATA SYNTHESIS: Of 5,148 citations, we included 62 studies. Pain, discomfort, anxiety/fear, noise, light, and ICU care-related activities are the most common and widely studied patient-reported factors causing sleep disruption. Patients rated noise and light as the most sleep-disruptive factors. Higher number of comorbidities, poor home sleep quality, home sleep aid use, and delirium were factors associated with sleep disruption identified in available studies. CONCLUSIONS: This systematic review summarizes all premorbid, illness-related, and ICU-related factors associated with sleep disruption in the ICU. These findings will inform sleep promotion efforts in the ICU and guide further research in this field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.573 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".