Rivaroxaban for extended thromboprophylaxis in acutely ill medical patients 75 years of age or older
Bibliographic record
Abstract
BACKGROUND: Although older patients are at increased risk for venous thromboembolism (VTE), thromboprophylaxis is underused because of bleeding concerns. The MARINER trial evaluated whether rivaroxaban reduced symptomatic postdischarge VTE in acutely ill medical patients. OBJECTIVES: We hypothesized that rivaroxaban would have a favorable benefit/risk profile in patients ≥75 years of age. METHODS: Patients were randomized in a double-blind manner at hospital discharge to rivaroxaban (10 mg/day for creatinine clearance ≥50 ml/min; 7.5 mg/day for ≥30-<50 ml/min) or placebo for 45 days. Using a Cox proportional hazard model including treatment as a covariate, we compared the risk of the primary efficacy outcome (symptomatic VTE plus VTE-related death in the intention-to-treat population) and safety outcome (International Society on Thrombosis and Haemostasis major bleeding in the safety population) in the prespecified subgroups of patients ≥ and <75 years of age. RESULTS: The primary event rate in patients ≥75 years of age was 2-fold higher than that in those <75 years. The incidence of the primary efficacy outcomes in both age groups was numerically lower with rivaroxaban than with placebo (≥75: 1.2% and 1.6%, HR 0.73, 95% CI 0.43-1.22; <75 0.6% and 0.8%, HR 0.78, 95% CI 0.46-1.32; interaction p-value for age group = .85). The incidence of major bleeding was low and similar in the two age and treatment groups (interaction p value for age group = .35). CONCLUSION: Symptomatic VTE and VTE-related death occur frequently in older patients with acute medical illness. The benefit/risk profile of rivaroxaban in patients ≥75 years of age appears consistent with that observed in the general population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".