Dabigatran and Warfarin in Vitamin K Antagonist–Naive and –Experienced Cohorts With Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND: The comparison of anticoagulants dabigatran and warfarin might be most equitable in vitamin K antagonist (VKA)-naive patients. METHODS AND RESULTS: Warfarin and 2 doses of dabigatran-110 mg BID (D110) and 150 mg BID (D150)-were compared in a balanced population of VKA-naive (≤62 days of lifetime VKA exposure, with 33% never prescribed a VKA) and VKA-experienced patients with atrial fibrillation (n=18 113). For VKA-naive and -experienced patients assigned warfarin, the time in therapeutic range (international normalized ratio 2.0 to 3.0) was 62% and 67%, respectively, and 61% and 66% for those never and ever prescribed a VKA. In VKA-naive patients, stroke and systemic embolism rates were 1.57%, 1.07%, and 1.69% per year for D110, D150, and warfarin, respectively. D110 was similar to warfarin (P=0.65); D150 was superior (P=0.005). Major bleeding rates were 3.11%, 3.34%, and 3.57% per year, respectively. D110 and D150 were similar to warfarin (P=0.19 and P=0.55). Intracranial bleeding rates were 0.19%, 0.33%, and 0.73% per year, respectively. D110 and D150 were lower than warfarin (P<0.001 and P=0.005). In VKA-experienced patients, stroke and systemic embolism rates were 1.51%, 1.15%, and 1.74% per year for D110, D150, and warfarin, respectively. D110 was similar to warfarin (P=0.32); D150 was superior (P=0.007). Major bleeding rates were 2.66%, 3.30%, and 3.57% per year, respectively. D110 was lower than warfarin (P=0.003); D150 was similar (P=0.41). Intracranial bleeding rates were 0.26%, 0.32%, and 0.79% per year, respectively. D110 and D150 were lower than warfarin (P<0.001 for both). Results were similar for patients never on a VKA. CONCLUSIONS: Previous VKA exposure does not influence the benefits of dabigatran at either dose compared with warfarin. CLINICAL TRIAL REGISTRATION: http://www.clinicaltrials.gov. Unique identifier: NCT00262600.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".