Rivaroxaban and Aspirin in Peripheral Vascular Disease: a Review of Implementation Strategies and Management of Common Clinical Scenarios
Bibliographic record
Abstract
PURPOSE OF REVIEW: Peripheral artery disease (PAD) affects an estimated 200 million people worldwide and is associated with significant cardiovascular morbidity and mortality. Cardiovascular risk is further increased among individuals with polyvascular disease, where either cerebrovascular or coronary artery disease is present in addition to PAD. In this review, we present common clinical scenarios encountered when managing patients with PAD and provide an evidence-based approach to prescribing optimal antithrombotics in this population. RECENT FINDINGS: The COMPASS trial recently demonstrated that rivaroxaban 2.5 mg BID + ASA daily significantly reduces major adverse cardiac and limb events in patients with PAD. Despite these advances, morbidity following MALE events remains high. With widespread approval by federal health regulators, the COMPASS regimen should be strongly considered in PAD patients who do not have a high bleeding risk. Implementing the COMPASS regimen in patients with PAD, along with other vascular risk reduction strategies, will have a substantial impact on reducing atherothromboembolic risk in patients with established vascular disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".