Aspirin versus low-molecular-weight heparin for venous thromboembolism prophylaxis in orthopaedic trauma patients: A patient-centered randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Emerging evidence suggests aspirin may be an effective venous thromboembolism (VTE) prophylaxis for orthopaedic trauma patients, with fewer bleeding complications. We used a patient-centered weighted composite outcome to globally evaluate aspirin versus low-molecular-weight heparin (LMWH) for VTE prevention in fracture patients. METHODS: We conducted an open-label randomized clinical trial of adult patients admitted to an academic trauma center with an operative extremity fracture, or a pelvis or acetabular fracture. Patients were randomized to receive LMWH (enoxaparin 30-mg) twice daily (n = 164) or aspirin 81-mg twice daily (n = 165). The primary outcome was a composite endpoint of bleeding complications, deep surgical site infection, deep vein thrombosis, pulmonary embolism, and death within 90 days of injury. A Global Rank test and weighted time to event analysis were used to determine the probability of treatment superiority for LMWH, given a 9% patient preference margin for oral administration over skin injections. RESULTS: Overall, 18 different combinations of outcomes were experienced by patients in the study. Ninety-nine patients in the aspirin group (59.9%) and 98 patients in the LMWH group (59.4%) were event-free within 90 days of injury. Using a Global Rank test, the LMWH had a 50.4% (95% CI, 47.7-53.2%, p = 0.73) probability of treatment superiority over aspirin. In the time to event analysis, LMWH had a 60.5% probability of treatment superiority over aspirin with considerable uncertainty (95% CI, 24.3-88.0%, p = 0.59). CONCLUSION: The findings of the Global Rank test suggest no evidence of superiority between LMWH or aspirin for VTE prevention in fracture patients. LMWH demonstrated a 60.5% VTE prevention benefit in the weighted time to event analysis. However, this difference did not reach statistical significance and was similar to the elicited patient preferences for aspirin.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".