Efficacy and safety of low-dose rivaroxaban on top of aspirin in patients with polypharmacy and multimorbidity: an analysis from the COMPASS trial
Bibliographic record
Abstract
Abstract Background In patients with coronary or peripheral artery disease, intensified antithrombotic therapy with aspirin plus low dose rivaroxaban reduced cardiovascular outcomes compared with aspirin alone. Polypharmacy and multimorbidity are frequent in patients with vascular disease and are often perceived as barriers to more intensive pharmacotherapy by both patients and physicians. Purpose To report cardiovascular outcomes and the efficacy, safety, and net benefit of low dose rivaroxaban plus aspirin in patients with stable vascular disease by the number of concomitant cardiovascular drugs and by the number of comorbidities. Methods We reported ischemic events (cardiovascular death, stroke, or MI), major bleeding (ISTH modified criteria), and a prespecified net clinical outcome in participants from the randomised, double-blind COMPASS study by number of cardiovascular medications (0–2, 3, 4, 5–7) and by number of concomitant medical conditions. We compared rates and hazard ratios of patients treated with rivaroxaban plus aspirin vs aspirin alone by category of number of medications and concomitant conditions and tested for interaction between polypharmacy and multimorbidity and antithrombotic regimen. Results Although patients with polypharmacy and multimorbidity have a higher risk of cardiovascular events (Figure) those who required many cardiovascular drugs derived the largest absolute reduction in the net clinical outcome when adding rivaroxaban on top of aspirin. The relative efficacy, safety, and net clinical benefit of adding low-dose rivaroxaban to aspirin in patients with stable vascular diseases were not affected by the number of cardiovascular drugs or by the number of comorbidities. Multimorbidity, but not polypharmacy, was related with a higher risk of major bleeding. Conclusion Addition of low-dose rivaroxaban conveyed a benefit irrespective of the number of concomitant drugs or comorbid conditions. Multiple comorbidities and/or polypharmacy should not dissuade the addition of low-dose rivaroxaban to aspirin in otherwise eligible patients. Figure 1 Funding Acknowledgement Type of funding source: Private company. Main funding source(s): The COMPASS trial was funded by Bayer AG.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".