Rivaroxaban compared with standard thromboprophylaxis after major orthopaedic surgery: co‐medication interactions
Bibliographic record
Abstract
AIM: The aim of the present study was to analyse concomitant drug use and its association with outcome in patients (N = 17 701) receiving rivaroxaban or standard of care (SOC) for the prevention of venous thromboembolism after major orthopaedic surgery in the non-interventional, phase IV XAMOS (Xarelto® in the prophylaxis of post-surgical venous thromboembolism after elective major orthopaedic surgery of hip or knee) study. METHODS: Concomitant drug use was at the discretion of the treating physician. Prespecified co-medications of interest were cytochrome P450 (CYP) 3A4/P-glycoprotein inhibitors/inducers, platelet aggregation inhibitors (PAIs) and nonsteroidal anti-inflammatory drugs (NSAIDs). Crude event incidences were compared between rivaroxaban and SOC groups. RESULTS: CYP3A4/P-glycoprotein inhibitor/inducer use was infrequent, in contrast to PAI (~7%) and NSAID (~52%) use. Rivaroxaban was associated with a lower incidence of overall symptomatic thromboembolic events compared with SOC, regardless of co-medication use. In both treatment groups, PAI users, with higher age and prevalence of cardiovascular co-morbidities, had similar higher (>7-fold) incidences of symptomatic arterial but not venous thromboembolic events compared with non-users. NSAID use had no influence on thromboembolic events. However, odds ratios (ORs) for major bleeding events (European Medicines Agency definition) were higher in NSAID users compared with non-users in rivaroxaban [OR = 1.50; 95% confidence interval (CI) 1.06, 2.13] and SOC (OR = 1.70; CI 1.16, 2.49) groups. In PAI users, ORs for major bleeding events were no different from those of non-users in both the rivaroxaban (OR = 1.49; CI 0.84, 2.65) and SOC (OR = 1.46; CI 0.82, 2.62) groups. CONCLUSIONS: Use of NSAIDs in XAMOS was frequent and associated with a higher frequency of bleeding events in patients receiving rivaroxaban or SOC, although the benefit-risk profile of rivaroxaban compared with SOC was maintained.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".