Abstract 12361: Efficacy and Safety of NOACs vs. Warfarin Across the Continuous Range of Body Mass Index and Body Weight: Insights From COMBINE-AF
Bibliographic record
Abstract
Introduction: The efficacy and safety of non-vitamin K oral anticoagulants (NOACs) in patients with atrial fibrillation (AF) at the extremes of body mass index (BMI) and body weight (BW) remains uncertain, leading to concerns regarding use in these populations across clinical practice guidelines. Methods: This analysis of the COMBINE-AF database pools individual patient-level data from the 4 pivotal RCTs of NOAC vs. warfarin in AF: RE-LY, ROCKET-AF, ARISTOTLE, and ENGAGE AF-TIMI 48. Pts randomized to low-dose NOACs not globally approved for clinical use were excluded. The primary efficacy and safety outcome was stroke/systemic embolic event (S/SEE) and major bleeding, respectively, with intracranial hemorrhage (ICH) being a secondary outcome. Outcomes were assessed across BMI and BW using a Cox model stratified by trial, with interaction testing for NOAC vs. warfarin. Restricted cubic splines were used to display the hazard ratio of NOAC vs. warfarin for each outcome across BMI. Results: For 58,464 pts, the median BMI was 28 (25 th -75 th %ile: 25-32) kg/m 2 , with the top 5% (n=2,924) having a BMI ≥ 40 kg/m 2 . For patients randomized to warfarin, the risk of each outcome was lower with increasing BMI (HR per 5 kg/m 2 increase: S/SEE 0.79 [95% CI 0.75-0.84]; major bleeding 0.91 [95% CI 0.87-0.95]; ICH 0.72 [95% CI 0.66-0.80]; p<0.01 for each). There was no significant treatment interaction for NOAC vs. warfarin by BMI for S/SEE (p-interaction = 0.71; Fig 1A ), major bleeding (p-interaction = 0.15; Fig 1B ), or ICH (p-interaction = 0.84; Fig 1C ), such that there was consistent reduction in S/SEE and ICH ( Fig 1A and 1C, respectively ) across the range of BMI with NOAC vs. warfarin. Similar results were seen for each outcome when assessed by BW (median [25 th -75 th %ile]: 81 [70-94] kg; 5 th -95 th %ile: 55-119 kg). Conclusions: In this pooled analysis of the pivotal AF trials, use of NOAC was associated with a consistent reduction in S/SEE and ICH compared with warfarin across the range of BMI and BW.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".