Effect of fondaparinux 2.5 mg once daily on mortality: a meta-analysis of phase III randomized trials of venous thromboembolism prevention
Bibliographic record
Abstract
Aims: Fondaparinux significantly reduces death in patients with acute coronary syndromes. The effect of fondaparinux on mortality when used for prevention of venous thromboembolism is unknown. We performed a meta-analysis to examine the effect of fondaparinux 2.5 mg once daily on mortality in phase III randomized trials of venous thromboembolism prevention. Methods and results: Eight trials involving 13 085 patients undergoing major orthopaedic or abdominal surgery or medical patients were included. In five trials, fondaparinux was compared with low-molecular-weight heparin (LMWH); in three trials, the comparator was placebo. The primary efficacy outcome was all-cause mortality up to day 30. The incidence of death was 1.6% (105/6538) in patients treated with fondaparinux compared with 2.1% (134/6547) in patients treated with placebo or LMWH [odds ratio (OR) 0.79; 95% confidence interval (CI) 0.60 to 1.01, P ¼ 0.058; P for heterogeneity ¼ 0.58]. Results were consistent irrespective of whether the comparator was placebo (2.0 vs. 2.6%, OR 0.77; 95% CI: 0.46–1.26) or LMWH (1.5 vs. 1.9%, OR 0.78; 95% CI: 0.58–1.06). Conclusion: The one-fifth reduction in mortality with fondaparinux suggested in randomized trials of venous thromboembolism prevention is not statistically significant, but is externally consistent with the reduction in mortality observed in registry studies and in randomized trials of fondaparinux in patients with acute coronary syndromes.
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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 | 0.019 | 0.030 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.049 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".