The prevalence of obstructive sleep apnea in patients with atrial fibrillation
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnea (OSA) is a systemic disorder associated with significant cardiovascular complications. OSA may play a role in the initiation and worsening of atrial fibrillation (AF). This study aimed to determine the prevalence and clinical predictors of OSA in patients with AF. HYPOTHESIS: OSA is underdiagnosed in a large number of patients with AF and may not be predicted by conventional clinical indices. METHODS: Consecutive nonselected patients with AF were recruited from different arrhythmia clinics in Toronto, Ontario, Canada. Patients with previous diagnosis and/or treatment of OSA were excluded. Patients underwent 2 consecutive nights of ambulatory sleep testing with full electroencephalogram recording. OSA was defined as an Apnea-Hypopnea Index (AHI) score ≥ 5 per hour of sleep. RESULTS: 123 patients with AF were recruited, with 100 patients included in the final analysis. OSA was detected in 85% of these patients. 27% of patients with normal overall AHI had an increased AHI during rapid eye movement sleep. Only age and male sex were independent predictors of the presence of OSA in these patients. CONCLUSIONS: OSA is common and often undetected in patients with AF, especially in nonobese and/or female patients. Patients may have a normal overall AHI but an abnormal AHI during rapid eye movement sleep. The clinical relevance and therapeutic implications in this subgroup should be further investigated. The clinical features of OSA are not reliable predictors of OSA in patients with AF. A low threshold for detection of OSA, with sleep studies, in these patients may be merited.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".