Extended anticoagulation for unprovoked venous thromboembolism
Bibliographic record
Abstract
After completing anticoagulation therapy for acute venous thromboembolism (VTE), patients with unprovoked VTE are at increased risk of recurrent thrombotic events. Recent studies suggest a risk of nearly 10% in the first year after stopping anticoagulants and 30% at 8 years. Therefore, it is important to consider extended anticoagulation for secondary prevention in these high-risk patients. While several oral anticoagulants are available for this purpose, there is limited information available regarding the optimal agent to minimize bleeding risks and maximize efficacy at VTE prevention. This review article summarizes the evidence available for Vitamin-K antagonists (VKAs) and direct oral anticoagulants (DOACs) for extended treatment of VTE. We also introduce the COVET trial, the first head-to-head comparison of VKAs to DOACs, rivaroxaban and apixaban, for extended management of unprovoked VTE.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".