Longitudinal changes in positive airway pressure device use after metabolic surgery: a 3-year matched cohort study of National Claims Data
Bibliographic record
Abstract
BACKGROUND: Metabolic surgery (MS) is the most durable treatment of obesity and can treat obstructive sleep apnea (OSA). OBJECTIVES: To compare trajectories of positive airway pressure (PAP) device use between individuals who had MS and similar individuals who did not have MS (non-MS). SETTING: Merative MarketScan Research Databases - a US-based commercial claims database. METHODS: Those who underwent MS were matched 1:1 with nonoperative controls on baseline demographic and health characteristics. PAP use trajectories were examined in the 3years after the index dates and stratified by baseline PAP use. RESULTS: A total of 8772 adults who had MS were matched with 8772 adults who did not have MS; in both groups, 17.3% had baseline PAP claims. Among individuals who had baseline PAP claims, those who had MS had significantly higher rates of PAP use cessation (58.9% versus 27.1%; P value < .01). Among individuals who were not using a PAP at baseline, PAP initiation was higher among those who did not have MS than those who had MS (10.8% versus 2.6%; P value < .01). CONCLUSIONS: MS was associated with discontinuation of PAP use and decreased initiation of PAP use among individuals who were not using these devices, suggesting that MS leads to symptomatic and preventive treatment for OSA.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".