Perioperative adverse events in adult patients with obstructive sleep apnea undergoing ambulatory surgery: An updated systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: The suitability of ambulatory surgery for patients with obstructive sleep apnea (OSA) remains controversial. This systematic review and meta-analysis aimed to evaluate the odds of perioperative adverse events in patients with OSA undergoing ambulatory surgery, compared to patients without OSA. METHODS: Four electronic databases were searched for studies published between January 1, 2011 and July 11, 2023. The inclusion criteria were: adult patients with diagnosed or high-risk of OSA undergoing ambulatory surgery; perioperative adverse events; control group included; general and/or regional anesthesia; and publication on/after February 1, 2011. We calculated effect sizes as odds ratios using a random effects model, and additional sensitivity analyses were conducted. RESULTS: :41%, P < 0.00001, 6 studies, n = 132,473). Three studies reported that OSA was strongly associated with prolonged post anesthesia care unit (PACU) length of stay (LOS), while one study reported that the association was not statistically significant. In addition, four studies reported that OSA was associated with postoperative respiratory depression/hypoxia, with one large study on shoulder arthroscopy reporting an almost 5-fold increased odds of pulmonary compromise, 5-fold of myocardial infarction, 3-fold of acute renal failure, and 5-fold of intensive care unit (ICU) admission. CONCLUSIONS: Ambulatory surgical patients with OSA had almost two-fold higher odds of same-day admission compared to non-OSA patients. Multiple large studies also reported an association of OSA with prolonged PACU LOS, respiratory complications, and/or ICU admission. Clinicians should screen preoperatively for OSA, optimize comorbidities, adhere to clinical algorithm-based management perioperatively, and maintain a high degree of vigilance in the postoperative period.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".