Assessment of Obstructive Sleep Apnea Among Patients With Chronic Obstructive Pulmonary Disease in Primary Care
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Bibliographic record
Abstract
Study Objectives: Observational studies link untreated obstructive sleep apnea (OSA) with adverse outcomes in chronic obstructive pulmonary disease (COPD). The first step in addressing OSA is a clinical assessment. However, given competing demands and a lack of high-quality evidence, it is unclear how often such assessments occur. We explored the documentation of OSA assessment among patients with COPD in primary care, and the patient and provider characteristics associated with these assessments. Methods: We conducted a cross-sectional study of patients with clinically diagnosed COPD at 2 primary care practices. We abstracted charts to determine whether providers assessed OSA, defined as documentation of symptoms, treatment, or a referral to sleep medicine. We performed multivariable mixed-effects logistic regression to assess the associations of patient and provider characteristics with OSA assessment. Results: Among 641 patients with clinically diagnosed COPD, 146 (23%) had OSA assessed over a 1-year period. Positive associations with OSA assessment included body mass index ≥ 30 (odds ratio [OR] 3.5, 95% confidence interval [CI] 1.8-7.0), pulmonary subspecialist visits (OR 3.9, 95%CI 2.4-6.3), and a prior sleep study demonstrating OSA documented within the electronic medical record (OR 18.0, 95%CI 9.0-35.8). Notably, patients identifying as Black were less likely to have OSA assessed than those identifying as White (OR 0.5, 95%CI 0.2-0.9). Conclusions: Providers document an assessment of OSA among a quarter of patients with COPD. Our findings highlight the importance of future work to rigorously test the impact of assessment on important health outcomes. Our findings also reinforce that additional strategies are needed to improve the equitable delivery of care.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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