The ‘obesity paradox’ in atrial fibrillation: observations from the ARISTOTLE (Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation) trial
Bibliographic record
Abstract
AIMS: The prognostic implication of adiposity on clinical outcomes in atrial fibrillation (AF) patients treated with oral anticoagulation is unclear. METHODS AND RESULTS: ). Waist circumference (WC) was defined as high if >102 cm for men and >88 cm in women. Outcomes were stroke or systemic embolism, a composite endpoint (stroke, systemic embolism, myocardial infarction, or all-cause mortality), all-cause mortality, and major bleeding. Cox models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) across categories of BMI and WC adjusting for established risk factors and treatment allocation. At baseline, 4052 (22.6%) patients had a normal BMI, 6702 (37.4%) were overweight, and 7159 (40.0%) were obese. In multivariable analyses, higher BMI was associated with a lower risk of all-cause mortality [overweight: HR 0.67 (95% CI 0.59-0.78); obese: HR 0.63 (95% CI 0.54-0.74), P < 0.0001] and the composite endpoint [overweight: HR 0.74 (95% CI 0.65-0.84); obese: HR 0.68 (95% CI 0.60-0.78), P < 0.0001] compared with normal BMI. In women, high WC was associated with a 31% lower risk of all-cause mortality (P = 0.001), 27% lower risk of the composite endpoint (P = 0.001), and 28% lower risk of stroke or systemic embolism (P = 0.048) but not in men. There was no significant association between adiposity and major bleeding. CONCLUSION: In patients with AF treated with oral anticoagulants, higher BMI and WC are associated with a more favourable prognosis.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".