Comparative Effectiveness and Safety of Direct Oral Anticoagulants vs Warfarin Among Obese Patients With Atrial Fibrillation
Bibliographic record
Abstract
Background: Obese patients are underrepresented in clinical trials assessing the comparative effectiveness and safety of use of direct oral anticoagulants vs use in atrial fibrillation (AF) patients. Methods: Using data from Quebec provincial administrative databases, for the years2010-2017, we created a retrospective cohort of patients with inpatient or outpatient coding for AF and obesity who were newly prescribed an oral anticoagulant. The primary safety outcome was a composite of intracranial, gastrointestinal, and major bleeding from other sites, and the primary effectiveness outcome was a composite of ischemic stroke, systemic embolism, acute myocardial infarction, and death in the first year after oral anticoagulant initiation. Treatment groups were compared using inverse-probability-of-treatment-weighting Cox proportional-hazards models. Results: A total of 2263 patients were included, of whom 1253, 403, and 539 filled a warfarin, standard-dose rivaroxaban, and standard-dose apixaban prescription, respectively. Standard-dose rivaroxaban was associated with a similar composite safety (hazard ratio [HR] 0.91; 95% confidence interval [CI] 0.44-1.91) and composite effectiveness risk (HR 1.42; 95% CI 0.99-2.04) compared to warfarin, whereas standard-dose apixaban was associated with a lower composite safety (HR 0.40; 95% CI 0.16-0.98) and similar composite effectiveness risk (HR 0.96; 95% CI 0.67-1.39). Conclusion: Use of direct oral anticoagulants in obese AF patients was associated with a similar effectiveness and safety profile to that of warfarin use.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".