Obstructive sleep apnea is common among patients referred for coronary artery bypass grafting and can be diagnosed by portable monitoring
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnea (OSA) is common among patients with coronary artery disease. However, OSA remains largely under recognized. The lack of clinical suspicion and difficulties to access full polysomnography (PSG) are limiting factors. The aim of this study was to evaluate, among patients referred to coronary artery bypass grafting (CABG): (i) the prevalence of OSA, (ii) the association of OSA with clinical symptoms, (iii) the performance of overnight unattended portable monitoring (PM) as an alternative method for the diagnosis of OSA. METHODS: Consecutive patients referred for CABG were evaluated by standard physical evaluation and validated questionnaires (Berlin questionnaire and Epworth Sleepiness Scale) and underwent full PSG and PM (Stardust II). RESULTS: We studied 70 consecutive patients (76% men), age 58±7 years (mean±SD), BMI [median (interquartile range)] 27.6 kg/m (25.8-31.1). The prevalence of OSA (full PSG) using an apnea-hypopnea index of at least 5 events/h was 87%. Commonly used clinical traits for the screening of OSA such as the Epworth Sleepiness Scale and neck circumference had low sensitivities to detect OSA. In contrast, the Berlin questionnaire showed a good sensitivity (72%) to detect OSA. PM showed good sensitivity (92%) and specificity (67%) for the diagnosis of OSA. CONCLUSION: OSA is strikingly common among patients referred for CABG. The Berlin questionnaire, but not symptom of excessive daytime sleepiness is a useful tool to screen OSA. PM is useful for the diagnosis of OSA and therefore is an attractive tool for widespread use among patients with coronary artery disease.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.003 | 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".