Perioperative adverse events in patients with obstructive sleep apnea undergoing ambulatory ENT surgery: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Patients with obstructive sleep apnea (OSA) may be at increased risk for adverse events during ambulatory otorhinolaryngologic (ear, nose, and throat, [ENT]) surgery. There remains a gap in the literature quantifying these risks. This systematic review and meta-analysis aimed to evaluate the incidence of perioperative complications among patients with OSA undergoing ambulatory ENT surgeries. METHODS: We systematically searched five databases from inception until February 2024 for studies on adult OSA patients undergoing ambulatory ENT surgeries. Primary outcomes included rates of composite adverse events, same-day admissions, emergency department (ED) visits, and readmissions. Meta-analysis, sensitivity analyses, and meta-regression were performed. RESULTS: Sixteen studies (5453 patients) were included. The pooled incidence of composite adverse events was 10 % (95 % CI 7-14 %), with 12 % requiring same-day admission, 7 % presenting to the ED, and a 3 % readmission rate. Adverse events were mostly bleeding, pain, and dehydration. Expansion sphincter pharyngoplasty and other combined/multi-level procedures were generally associated with the most complications. CONCLUSION: Our findings suggest that ENT procedures may be safely performed in ambulatory settings in appropriately selected patients with OSA. Improved patient selection and perioperative management may reduce complications, and careful risk stratification remains essential, particularly for combined/multi-level airway surgeries.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.030 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".