Dabigatran, rivaroxaban and apixaban for extended venous thromboembolism treatment: network meta-analysis.
Bibliographic record
Abstract
AIM: Many new oral anticoagulants (NOACs; dabigatran, rivaroxaban, and apixaban) are currently available to treat thromboembolic disease. There are no head-to-head trials comparing these agents. To assess the efficacy and safety of NOACs for prevention of recurrent venous thromboembolism (VTE), we performed a network meta-analysis. METHODS: Medline, Embase, and the Cochrane-controlled trial register were searched, without language restriction, to identify trials. Studies were evaluated according to a priori inclusion criteria and appraised using established internal validity criteria. Adjusted indirect comparisons between agents were performed using well-established methods. RESULTS: Three trials meeting inclusion criteria were identified. Direct comparison between apixaban 2.5 mg twice daily (BID) versus apixaban 5 mg BID showed no difference for any outcome. Clinically relevant non-major bleeding occurred less with both apixaban 2.5 mg BID (OR 0.23, 95% CI 0.08-0.62, P=0.004) and apixaban 5 mg BID [OR 0.31, 95% CI 0.11-0.82, P=0.019] compared to rivaroxaban 20 mg daily. Apixaban 2.5 mg BID showed less clinically relevant non-major bleeding than dabigatran 150 mg BID [OR 0.4, 95% CI 0.16-0.9, P=0.04], but not apixaban 5 mg BID. There were no differences between rivaroxaban 20 mg daily and dabigatran 150 mg BID. No differences in risk for recurrent VTE, major bleeding, or mortality were observed for any comparison between any pair of NOACs. CONCLUSION: There were no significant differences in risk for recurrent VTE, major bleeding, or all-cause mortality between the NOACs. However, apixaban 2.5 mg BID was associated with less clinically significant non-major bleeding than either rivaroxaban 20 mg daily or dabigatran 150 mg BID.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.048 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".