The design of venous thromboembolism prophylaxis trials: Fondaparinux is definitely more effective than enoxaparin in orthopaedic surgery
Bibliographic record
Abstract
The fondaparinux trials in venous thromboembolism (VTE) prevention after orthopaedic surgery have been subject to methodological criticisms recently summarised in this journal. These criticisms merit comments and corrections. Fondaparinux reduced the risk of VTE and of proximal deep-vein thrombosis by more than 55% compared with enoxaparin, based on the efficacy endpoint that supported the registration and use of low-molecular-weight heparins (LMWH) in all their prophylactic indications, an endpoint endorsed by international consensus statements and health authorities. Fondaparinux is the only antithrombotic agent that significantly reduced the rate of symptomatic VTE in a single orthopaedic surgery trial that was powered to detect this effect. In contrast to the paucity of data available on LMWH, the relationship between the timing of first administration and efficacy and safety has been well documented for fondaparinux. Fondaparinux used according to its approved regimen provides a simple, easy-to-use, effective and safe post-operative regimen for all orthopaedic surgery patients.
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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 | 0.100 | 0.228 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".