Associations of Epicardial, Abdominal, and Overall Adiposity With Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: Although adiposity is increasingly recognized as a risk factor for atrial fibrillation (AF), the importance of epicardial fat compared with other adipose tissue depots remains uncertain. We sought to characterize and compare the associations of AF with epicardial fat and measures of abdominal and overall adiposity. METHODS AND RESULTS: We conducted a meta-analysis of 63 observational studies including 352 275 individuals, comparing AF risk for 1-SD increases in epicardial fat, waist circumference, waist/hip ratio, and body mass index. A 1-SD higher epicardial fat volume was associated with a 2.6-fold higher odds of AF (odds ratio, 2.61; 95% confidence interval [CI], 1.89-3.60), 2.1-fold higher odds of paroxysmal AF (odds ratio, 2.14; 95% CI, 1.45-3.16) and, 5.4-fold higher odds of persistent AF (odds ratio, 5.43; 95% CI, 3.24-9.12) compared with sinus rhythm. Likewise, a 1-SD higher epicardial fat volume was associated with 2.2-fold higher odds of persistent compared with paroxysmal AF (odds ratio, 2.19; 95% CI, 1.66-2.88). Similar associations existed for postablation, postoperative, and postcardioversion AF. In contrast, associations of abdominal and overall adiposity with AF were less extreme, with relative risks per 1-SD higher values of 1.32 (95% CI, 1.25-1.41) for waist circumference, 1.11 (95% CI, 1.08-1.14) for waist/hip ratio, and 1.22 (95% CI, 1.17-1.27) for body mass index. CONCLUSIONS: Strong and graded associations were observed between increasing epicardial fat and AF. Moreover, the strength of associations of AF with epicardial fat is greater than for measures of abdominal or overall adiposity. Further studies are needed to assess the mechanisms and clinical relevance of epicardial fat.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".