Association of type of oral anticoagulation with risk of bleeding in 45,114 patients with venous thromboembolism during initial and extended treatment—A nationwide register‐based study
Bibliographic record
Abstract
BACKGROUND: Safety data for different anticoagulant medications in venous thromboembolism (VTE) are scarce, in particular for extended treatment. OBJECTIVES: To compare major bleeding rates depending on the choice of anticoagulation during initial (first 6 months) and extended treatment (6 months up to 5 years). METHODS: A nationwide register-based study including cancer-free patients with a first-time VTE between 2014 and 2020. Cox proportional hazards models were used to compare bleeding rates. RESULTS: We included 6558 patients on warfarin, 18,196 on rivaroxaban, and 19,498 on apixaban. At 6 months, 4750 (72.4%) remained on warfarin, 11,366 (62.5%) on rivaroxaban, and 11,940 (61.2%) on apixaban. During initial treatment, major bleeding rates were 3.86 (95% CI 3.14-4.58), 2.93 (2.55-3.31), and 1.95 (1.65-2.25) per 100 patient-years for warfarin, rivaroxaban, and apixaban, respectively, yielding adjusted hazard ratios (aHRs) of 0.89 (95% CI 0.71-1.12) for rivaroxaban versus warfarin, 0.55 (0.43-0.71) for apixaban versus warfarin, and 0.62 (0.50-0.76) for apixaban versus rivaroxaban. During extended treatment, major bleeding rates were 1.55 (1.19-1.91), 1.05 (0.85-1.26), and 0.96 (0.78-1.15) per 100 patient-years for warfarin, rivaroxaban, and apixaban, respectively, with aHRs of 0.72 (0.53-0.99) for rivaroxaban versus warfarin, 0.60 (0.44-0.82) for apixaban versus warfarin, and 0.85 (0.64-1.12) for apixaban versus rivaroxaban. Previous bleeding and increasing age were risk factors for bleeding both during initial and extended treatment. CONCLUSION: Apixaban had a lower bleeding risk than warfarin or rivaroxaban during initial treatment. During extended treatment, bleeding risk was similar for apixaban and rivaroxaban, and higher with warfarin.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".