Cost-effectiveness Analysis of Preoperative Screening Strategies for Obstructive Sleep Apnea among Patients Undergoing Elective Inpatient Surgery
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnea is underdiagnosed in surgical patients. The cost-effectiveness of obstructive sleep apnea screening is unknown. This study's objective was to evaluate the cost-effectiveness of preoperative obstructive sleep apnea screening (1) perioperatively and (2) including patients' remaining lifespans. METHODS: An individual-level Markov model was constructed to simulate the perioperative period and lifespan of patients undergoing inpatient elective surgery. Costs (2016 Canadian dollars) were calculated from the hospital perspective in a single-payer health system. Remaining model parameters were derived from a structured literature search. Candidate strategies included: (1) no screening; (2) STOP-Bang questionnaire alone; (3) STOP-Bang followed by polysomnography (STOP-Bang + polysomnography); and (4) STOP-Bang followed by portable monitor (STOP-Bang + portable monitor). Screen-positive patients (based on STOP-Bang cutoff of at least 3) received postoperative treatment modifications and expedited definitive testing. Effectiveness was expressed as quality-adjusted life month in the perioperative analyses and quality-adjusted life years in the lifetime analyses. The primary outcome was the incremental cost-effectiveness ratio. RESULTS: In perioperative and lifetime analyses, no screening was least costly and least effective. STOP-Bang + polysomnography was the most effective strategy and was more cost-effective than both STOP-Bang + portable monitor and STOP-Bang alone in both analyses. In perioperative analyses, STOP-Bang + polysomnography was not cost-effective compared to no screening at the $4,167/quality-adjusted life month threshold (incremental cost-effectiveness ratio $52,888/quality-adjusted life month). No screening was favored in more than 90% of iterations in probabilistic sensitivity analyses. In contrast, in lifetime analyses, STOP-Bang + polysomnography was favored compared to no screening at the $50,000/quality-adjusted life year threshold (incremental cost-effectiveness ratio $2,044/quality-adjusted life year). STOP-Bang + polysomnography was favored in most iterations at thresholds above $2,000/quality-adjusted life year in probabilistic sensitivity analyses. CONCLUSIONS: The cost-effectiveness of preoperative obstructive sleep apnea screening differs depending on time horizon. Preoperative screening with STOP-Bang followed by immediate confirmatory testing with polysomnography is cost-effective on the lifetime horizon but not the perioperative horizon. The integration of preoperative screening based on STOP-Bang and polysomnography is a cost-effective means of mitigating the long-term disease burden of obstructive sleep apnea.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".