Factors Associated with Postoperative Exacerbation of Sleep-disordered Breathing
Bibliographic record
Abstract
INTRODUCTION: The knowledge on the mechanism of the postoperative exacerbation of sleep-disordered breathing may direct the perioperative management of patients with obstructive sleep apnea. The objective of this study is to investigate the factors associated with postoperative severity of sleep-disordered breathing. METHODS: After obtaining approvals from Institutional Review Boards, consenting patients underwent portable polysomnography preoperatively, and on postoperative nights 1 and 3 in hospital or at home. The primary outcomes were polysomnography parameters measuring the sleep-disordered breathing. They were treated as repeated measurement variables and analyzed for associated factors by mixed models. RESULTS: Three hundred seventy-six patients, 168 men and 208 women, completed polysomnography on preoperative and postoperative night 1. Age was 59 ± 12 yr (mean ± SD). Preoperative apnea-hypopnea index (AHI) was 12 (4, 26) (median [25th, 75th percentile]) events per hour. Thirty-five patients had minor surgeries, 292 intermediate surgeries, and 49 major surgeries, with 210 general anesthesia and 166 regional anesthesia. The 72-h opioid dose was 55 (14, 85) mg intravenous morphine-equivalent dose. Preoperative AHI, age, and 72-h opioid dose were associated with postoperative AHI. Preoperative central apnea index, male sex, and general anesthesia were associated with postoperative central apnea index. Slow wave sleep percentage was inversely associated with postoperative AHI and central apnea index. CONCLUSIONS: Patients with a higher preoperative AHI were predicted to have a higher postoperative AHI. Preoperative AHI, age, and 72-h opioid dose were positively associated with postoperative AHI. Preoperative central apnea, male sex, and general anesthesia were associated with postoperative central apnea index.
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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 | 0.000 |
| 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) | 0.003 | 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".