P2298High body mass index and outcomes of dual antithrombotic therapy with dabigatran and a P2Y12 inhibitor in patients with atrial fibrillation undergoing PCI: Results from RE-DUAL PCI
Bibliographic record
Abstract
Background: There is a general lack of knowledge about efficacy or safety of the non-vitamin K antagonist oral anticoagulants (NOACs) in patients with extremes of body weight or body mass index (BMI, including patients with either BMI ≤25 or ≥35), which can impact drug levels, and such information could be of even greater relevance when a NOAC is combined with an antiplatelet agent. The RE-DUAL PCI trial (NCT02164864) evaluated the safety and efficacy of a dual antithrombotic therapy regimen using dabigatran and a P2Y12 inhibitor, and compared this with a classical “triple therapy” with warfarin, aspirin and clopidogrel. Purpose: We sought to assess whether BMI could impact outcomes in the setting of the study. Methods: The RE-DUAL PCI trial randomized 2725 patients with nonvalvular atrial fibrillation (AF) who had undergone percutaneous coronary intervention (PCI) to triple therapy with warfarin, clopidogrel or ticagrelor, and aspirin for 1 to 3 months, or to dabigatran dual therapy with either 110 mg or 150 mg twice daily (BID), each with either clopidogrel or ticagrelor. We report the rates of first ISTH major or clinically relevant non-major bleeding events, and the composite end point of death, myocardial infarction, stroke, systemic embolism or unplanned revascularization, as a function of baseline BMI, dividing the population into 4 subgroups of BMI (all in kg/m2 body surface area): normal/underweight (<25), overweight (25-<30), class I obese (30-<35) and >class I obese (≥35).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".