Eligibility and Implementation of Rivaroxaban for Secondary Prevention of Atherothrombosis in Clinical Practice—Insights From the CANHEART Study
Bibliographic record
Abstract
Background The COMPASS (Cardiovascular Outcomes for People Using Anticoagulation Strategies) trial decreased major adverse cardiovascular events with very low‐dose rivaroxaban and aspirin in patients with coronary artery disease and peripheral artery disease. We examined the eligibility and potential real‐world impact of this strategy on the COMPASS‐eligible population. Methods and Results COMPASS eligibility criteria were applied to the CANHEART (Cardiovascular Health in Ambulatory Care Research Team) registry, a population‐based cohort of Ontario adults. We compared 5‐year major adverse cardiovascular events and major bleeding rates stratified by COMPASS eligibility and by clinical risk factors. We applied COMPASS trial rivaroxaban/aspirin arm hazard ratios to estimate the potential impact on the COMPASS‐eligible cohort. Among 362 797 patients with coronary artery disease or peripheral artery disease, 38% were deemed eligible, 47% ineligible, and 15% indeterminate. Among eligible patients, a greater number of risk factors was associated with higher rates of cardiovascular outcomes, whereas bleeding rates increased minimally. Over 5 years, applying COMPASS treatment effects to eligible patients resulted in a 2.4% absolute risk reduction of major adverse cardiovascular events and a number needed to treat of 42, and a 1.3% absolute risk increase of major bleeding and number needed to harm (NNH) of 77. Those with at least 2 risk factors had a 3.0% absolute risk reduction of major adverse cardiovascular events (number needed to treat =34) and a 1.6% absolute risk increase of major bleeding (number needed to harm =61). Conclusions Implementation of very‐low‐dose rivaroxaban therapy would potentially impact ≈ $$ \approx $$ 2 in 5 patients with atherosclerotic disease in Ontario. Eligible individuals with ≥ $$ \ge $$ 2 comorbidities represent a high‐risk subgroup that may derive the greatest benefit‐to‐risk ratio. Selection of patients with high‐risk predisposing factors appears appropriate in routine practice.
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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".