Temporal Trends in the Use and Comparative Effectiveness of Direct Oral Anticoagulant Agents Versus Warfarin for Nonvalvular Atrial Fibrillation: A Canadian Population‐Based Study
Bibliographic record
Abstract
BACKGROUND: Direct oral anticoagulants (DOACs) are noninferior to warfarin for stroke prevention in atrial fibrillation (AF). We aimed to determine the population risk of stroke and death in incident AF, stratified by anticoagulation status and type, and the temporal trends of oral anticoagulation practice in the post-DOAC approval period. METHODS AND RESULTS: We conducted a population-based cohort study of incident nonvalvular AF cases using administrative health data in Alberta, Canada. We used Cox proportional hazards modeling with anticoagulation status as a time-varying exposure and adjusted for age (continuous), sex, congestive heart failure, hypertension, diabetes mellitus, prior transient ischemic attack or ischemic stroke, myocardial infarction, peripheral artery disease, and chronic kidney disease. Primary outcome was the composite of stroke and death. Among 34 965 patients with incident AF (56.0% male, median age 73 years), relative to warfarin, DOAC use was associated with decreased risk of all stroke and death (hazard ratio: 0.90; 95% confidence interval, 0.83-0.97) and decreased hemorrhagic stroke (hazard ratio: 0.60; 95% confidence interval, 0.40-0.91]) but a similar risk of ischemic stroke (hazard ratio: 1.12; 95% confidence interval, 0.94-1.34]). During this time period, DOAC use increased rapidly, surpassing warfarin, but the total oral anticoagulation use in the population remained stable, even in the subgroup with the highest thromboembolic risk. CONCLUSIONS: In a real-world population-based study of patients with incident AF, anticoagulation with DOACs was associated with decreased risk of stroke and death compared with warfarin. Despite a rapid uptake of DOACs in clinical practice, the total proportion of AF patients on anticoagulation has remained stable, even in high-risk patients.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 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".