Undiagnosed Obstructive Sleep Apnea and Postoperative Outcomes: A Prospective Observational Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The prevalence of undiagnosed obstructive sleep apnea (OSA) during preoperative evaluation and the best method to screen OSA and its association with postoperative complications remain unclear. OBJECTIVES: To determine the prevalence of undiagnosed OSA in preoperative Indian patients undergoing noncardiac surgery, to compare the diagnostic accuracy of the STOP-BANG questionnaire to a preoperative level III sleep study, and to assess the association of OSA with postoperative complications. METHODS: A prospective cohort of 245 consecutive adults with ≥2 risk factors for OSA who underwent noncardiac surgery between July 2011 and February 2013 were studied. The STOP-BANG questionnaire was administered to all patients, and 182/245 (74.2%) patients underwent a preoperative level III sleep study. Patients were followed for postoperative complications in hospital and contacted at 30 days after surgery. RESULTS: 70/182 (38.5%) obtained a new diagnosis of OSA, including 11/182 (6%) with moderate to severe OSA (apnea-hypopnea index ≥15/h). On logistic regression analyses, the presence of OSA was independently associated with postoperative oxygen desaturation (OR 5.96, 95% CI 2.35-15.1, p < 0.01), a postoperative complication within 7 days (OR 3.63, 95% CI 1.77-7.45, p < 0.01) and within 30 days (OR 3.5, 95% CI 1.74-7.1, p < 0.01). The STOP-BANG questionnaire did not identify 12/70 (17%) of the patients diagnosed with OSA and classified 28% of the cohort as OSA when the level III sleep study was negative. CONCLUSIONS: Unrecognized OSA is common in preoperative patients and is independently associated with postoperative complications. The STOP-BANG questionnaire had a lower performance in the diagnosis of OSA in a South Indian population than the level III sleep study.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it