Association of STOP-Bang Questionnaire as a Screening Tool for Sleep Apnea and Postoperative Complications: A Systematic Review and Bayesian Meta-analysis of Prospective and Retrospective Cohort Studies
Bibliographic record
Abstract
BACKGROUND: The risk of postoperative complications increases with undiagnosed obstructive sleep apnea (OSA). The high-risk OSA (HR-OSA) patients can be easily identified using the STOP-Bang screening tool. The aim of this systematic review and meta-analysis is to determine the association of postoperative complications in patients screened as HR-OSA versus low-risk OSA (LR-OSA). METHODS: The following data bases were searched from January 1, 2008, to October 31, 2016, to identify the eligible articles: Cochrane Central Register of Controlled Trials, MEDLINE, PubMed, Cochrane Databases of Systematic Reviews, Medline-in-Process & other nonindexed citations, Google Scholar, Embase, Web of Sciences and Scopus. The search included studies with adult surgical patients screened for OSA with STOP-Bang questionnaire that reported at least 1 cardiopulmonary or any other complication requiring intensive care unit admission as diagnosis of outcome. We used a Bayesian random-effects analysis to evaluate the existing evidence of STOP-Bang in relation to OSA and to assess the association of postoperative complications with the identified HR-OSA patients by study design and methodologies. RESULTS: This systematic review and meta-analysis was conducted using 10 cohort studies: 23,609 patients (HR-OSA, 7877; LR-OSA, 15,732). The pooled odds of perioperative complications were higher in the HR-OSA versus LR-OSA patients (odds ratio 3.93, 95% credible interval, 1.85-7.77, P= .003; 6.86% vs 4.62%). The length of hospital stay was longer in HR-OSA by 2 days when compared with LR-OSA (5.0 ± 4.2 vs 3.4 ± 2.8 days; mean difference 2.01; 95% credible interval, 0.77-3.24; P= .005). Meta-regression to adjust for baseline confounding factors and subgroup analysis did not materially change the results. CONCLUSIONS: This systematic review and meta-analysis suggests that HR-OSA is related with higher risk of postoperative adverse events and longer length of hospital stay when compared with LR-OSA patients. Our findings support the implementation of the STOP-Bang screening tool for perioperative risk stratification.
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How this classification was reachedexpand
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".