Dual pathway inhibition in patients with atherosclerosis with and without heart failure: insights from the XATOA Registry
Bibliographic record
Abstract
Abstract Introduction Patients with atherosclerotic cardiovascular disease (ASCVD) are at a high-risk of experiencing a major adverse cardiovascular event, with 1 in 10 individuals experiencing an event within four years (1). To address this risk of secondary cardiovascular events, there have been renewed efforts to enhance secondary prevention therapies through the application of guideline-directed medical therapy. One secondary prevention strategy is the use of dual pathway inhibition (DPI) therapy with aspirin and vascular-dose rivaroxaban (2.5mg twice daily), which simultaneously targets both the platelet activation and thrombin generation pathways. Patients with concomitant ASCVD and heart failure (HF) are a subgroup with a higher risk for ischemic events, but have not been adequately represented in recent clinical trials. Purpose To explore the risks and benefits of DPI therapy in a generalizable population of patients with concomitant ASCVD and HF. Methods The Xarelto plus Acetylsalicylic acid Treatment patterns and Outcomes in patients with Atherosclerosis (XATOA) registry is a prospective, multicentre registry of patients with either coronary artery or peripheral artery disease that were initiated on DPI (2). The primary endpoint was a composite of cardiovascular death, myocardial infarction or stroke and the safety outcome was major bleeding. Multivariable logistic regression was performed to assess the association of HF status and ejection fraction (EF) on the outcomes of interest. Results Of 5532 participants, 4022 (72.7%) had documentation of HF status. Of those 873 (21.5%) had a history of heart failure (EF >40% - 461; EF ≤40% - 181, EF unknown – 231). Over a median follow-up of 465 days (IQR – 372-576), the primary outcome occurred in 4.9% of participants with HF compared to 2.4% in those without HF (aHR 1.57 95% CI 1.02-2.41). The safety outcome was similar in patients with and without HF (0.9% versus 1.11%; aHR 0.7 95% CI 0.31-1.67). Among patients with HF, those with an EF of ≤40% demonstrated a non-significant trend towards higher rates of adverse events including MACE (8.8% versus 3.5%; aHR 1.38; 95% CI 0.59-3.22) compared to those with an EF of > 40%. Conclusion In a generalizable cohort of patients with atherosclerotic disease and HF, the use of DPI is associated with similar outcomes to those observed in recent randomised controlled clinical trials.Table 1 - Demographics by HF statusFigure 1 - MACE by HF status
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".