Association Between Atrial Fibrillation and Central Sleep Apnea
Bibliographic record
Abstract
BACKGROUND: We previously described an association between atrial fibrillation and central sleep apnea in a group of patients with congestive heart failure. We hypothesized that the prevalence of atrial fibrillation might also be increased in patients with central sleep apnea in the absence of other cardiac disease. METHODS AND RESULTS: We compared the prevalence of atrial fibrillation in a series of 60 consecutive patients with idiopathic central sleep apnea (apnea-hypopnea index > 10 events per hour, > 50% central events) with that in 60 patients with obstructive sleep apnea (apnea-hypopnea index > 10, > 50% obstructive events) and 60 patients without sleep apnea (apnea-hypopnea index < 10), matched for age, sex, and body mass index. Subjects with a history of congestive heart failure, coronary artery disease, or stroke were excluded from the study. The prevalence of atrial fibrillation among patients with idiopathic central sleep apnea was found to be significantly higher than the prevalence among patients with obstructive sleep apnea or no sleep apnea (27%, 1.7%, and 3.3%, respectively, P < .001). However, hypertension was most common and oxygen desaturation most extreme among patients with obstructive sleep apnea. CONCLUSIONS: We conclude that there is a markedly increased prevalence of atrial fibrillation among patients with idiopathic central sleep apnea in the absence of congestive heart failure. Moreover, the high prevalence of atrial fibrillation among patients with idiopathic central sleep apnea is not explainable by the presence of hypertension or nocturnal oxygen desaturation, since both of these were more strongly associated with obstructive sleep apnea.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".