The prevalence of and risk factors for sleep disturbances: a systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract Background Determining the prevalence and risk factors related to sleep disturbance is beneficial for risk stratification, preventative interventions, and care planning. The objectives of this systematic review and meta‐analysis are to determine the prevalence and risk factors of sleep disturbances and their associated postoperative complications in surgical patients. Method A systematic search of the databases MEDLINE, MEDLINE ePubs Ahead of Print and In‐ process, Embase Classic+Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials from inception to February 23, 2022, was conducted. The inclusion criteria were: (1) adult patients undergoing a surgical procedure; (2) in‐patient population; (3) assessed for pre‐ and postoperative sleep disturbances using the Pittsburgh Sleep Quality Index (PSQI) and/or objective sleep assessment tools, and (4) English language articles. The pooled prevalence of sleep disturbances was calculated using inverse‐variance random‐effects model. The 95% confidence interval (CI) was calculated using normal approximation calculation. Sensitivity analysis was performed to determine the effect of each study on the meta‐analysis estimates. Result The systematic search resulted in 21,951 articles. Twelve studies involving 1,497 patients were included. The pooled prevalence of sleep disturbances at preoperative assessment was 60% (95% CI: 50%, 69%) (Figure). Risk factors for postoperative sleep disturbances were preexisting disturbed sleep and preoperative anxiety. Patients with postoperative delirium had a higher prevalence of pre‐ and postoperative sleep disturbances. Patients with postoperative delirium also had higher wake after sleep onset percentage (WASO%) in preoperative assessment using actigraphy. Conclusion The prevalence of preoperative sleep disturbances is high at 60%. In adult surgical patients undergoing inpatient surgery, preoperative sleep disturbance and anxiety were the two main risk factors for postoperative sleep disturbance. Surgical patients with postoperative delirium were associated with a higher prevalence of pre‐and postoperative sleep disturbances. Preventing sleep disturbances in surgical patients may be important for postoperative outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".