Insomnia is Associated with Depression and Anxiety in Patients Undergoing Noncardiac Surgery
Bibliographic record
Abstract
Abstract BackgroundTo investigate the difference of demographic, health status and clinical characteristics of patients with or without insomnia postoperatively, and to identify the potential risk factors of insomnia.Methods299 patients undergoing surgery were included. Patients were divided into group A (insomnia, N = 78) and group B (without insomnia, N = 221). Insomnia Severity Index (ISI), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder (GAD-7), and Montreal cognitive assessment (MoCA) were applied to all patients preoperatively. Visual Analogue Scale (VAS) was assessed preoperatively, and at the end of the surgery, one day after surgery, two days after surgery and three days after surgery. The PHQ-9, the GAD-7 and the ISI were reassessed three days after surgery. Information on sociodemographic variables and demographic data were collected.ResultsAmong the two groups, the average points patients got in the ISI, PHQ-9 and the GAD-7 in group A were also significantly higher than those in group B. The VAS score 3 days after surgery was significantly higher in group A. The PHQ-9 and the GAD-7 3 days after surgery showed significantly higher depression and anxiety scores in group A. Logistic regression showed ISI (P < 0.001, 95%CI = 1.218-1.500), the GAD-7 (P = 0.01, 95%CI = 0.712–0.954) preoperatively and the PHQ-9 postoperatively (P < 0.001, 95%CI = 1.226–1.555) were risk factors of insomnia.ConclusionsInsomnia is common in patients, which worsen after surgery. The present study suggests that depression and anxiety are risk factors of poor sleep quality after surgery. There is a need for further research and strategies for depression and anxiety management to achieve better sleep and significant health benefits in these patients.Trial registration: clinical trial, NCT04027751. Registered 22 July 2019, https://clinicaltrials.gov/ct2/show/NCT04027751?cond=NCT04027751&cntry=CN&draw=2&rank=1.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".