Enoxaparin Versus Dabigatran or Rivaroxaban for Thromboprophylaxis After Hip or Knee Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Dabigatran and rivaroxaban are novel oral anticoagulants approved for prevention of venous thromboembolism after hip or knee arthroplasty. However, information assessing clinically important efficacy and bleeding outcomes of these 2 new agents versus low-molecular-weight heparin (enoxaparin) is lacking. METHODS AND RESULTS: We separately pooled efficacy and safety data from 6 phase III randomized trials (18 405 participants) comparing equivalent durations of treatment with enoxaparin (40 mg once daily [od] or 30 mg twice daily) versus dabigatran (220 mg od) or versus rivaroxaban (10 mg od) after hip or knee arthroplasty. Odds ratios (OR) for individual outcomes were calculated for each trial and were pooled using the Mantel-Haenszel method. Compared with dabigatran, enoxaparin had a similar risk of symptomatic venous thromboembolism plus all-cause mortality (0.9% versus 1.1%; OR, 0.76; 95% confidence interval [CI], 0.44 to 1.31; I²=76%) and bleeding (5.0% versus 5.6%; OR, 0.90; 95% CI, 0.71 to 1.15; I²=0%). Compared with rivaroxaban, enoxaparin had a 2-fold higher risk of symptomatic venous thromboembolism plus all-cause mortality (1.2% versus 0.6%; OR, 2.04; 95% CI, 1.32 to 3.17; P<0.001; number needed to treat, 167; I²=0%) but demonstrated a significant lower risk of bleeding (2.5% versus 3.1%; OR, 0.79; 95% CI, 0.62 to 0.99; P=0.049; number needed to harm, 167; I²=0%). CONCLUSIONS: In patients undergoing hip or knee arthroplasty, enoxaparin and dabigatran showed similar rates of efficacy and bleeding. Enoxaparin was less effective than rivaroxaban but had a lower risk of bleeding. These results may have important implications for the choice of prophylactic agent in major joint arthroplasty.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".