Utility of Screening for Obstructive Sleep Apnea in Cardiac Rehabilitation
Bibliographic record
Abstract
PURPOSE: Obstructive sleep apnea (OSA) is prevalent in patients with cardiovascular disease and is often undiagnosed. The purpose of this study was to determine the utility of communicating OSA risk with the patients in a diabetes and cardiac rehabilitation program (CRP) and primary care physicians. METHODS: Following an OSA education session, 295 patients in diabetes and CRPs were screened for OSA and daytime sleepiness by STOP-BANG and Epworth Sleepiness Scale questionnaires. Letters were sent to patients at high risk or noncompliant with continuous positive airway pressure (CPAP) treatment and their physicians. Follow-up questionnaires were sent to patients 6 months later. RESULTS: Of the 295 patients screened, 16.6% (n = 49) had an OSA diagnosis and had been prescribed CPAP. A smaller proportion patients in the diabetes program than in the CRP had discontinued CPAP (22.2% vs 45.2%; P = .03) with discomfort being the greatest barrier. Three of the 7 patients (42.9%) who had contact with their physician resumed CPAP. Of the remaining 246 patients who scored high on ≥1 questionnaire (77.6%; n = 191) and returned the 6-month questionnaire (53.9%; n = 103), communication of risk assessment resulted in 49.5% (n = 51) of patients consulting with their physician. Of those, half were referred for polysomnography. All were diagnosed with OSA. CONCLUSION: More than three quarters of patients in diabetes and CRPs scored high on ≥1 questionnaire suggesting signs/symptoms of OSA. However, only 16.6% were prescribed CPAP and compliance to treatment was poor (63.3%). Education and communication of OSA risk with patients and physicians resulted in a de novo diagnosis in at least 1 of 10 patients screened and 16.7% restarted CPAP.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".