Antithrombotics in stable peripheral artery disease
Bibliographic record
Abstract
Patients with peripheral artery disease (PAD) are at high risk for ischemic cardiovascular complications. While single antiplatelet therapy (SAPT), predominantly aspirin, has long been the standard antithrombotic treatment in stable PAD, there have now been greater than 40,000 PAD patients randomized to varying antiplatelet and/or anticoagulant regimens. In this review, we provide a summary of the current evidence for antithrombotics in stable PAD, focusing on the rates of major adverse cardiovascular events (MACE), major adverse limb events (MALE), and major bleeding. SAPT has a limited role in the treatment of asymptomatic PAD, particularly in the absence of concomitant coronary artery disease. In symptomatic PAD, SAPT is effective in preventing MACE, though treatment with a thienopyridine appears marginally superior to aspirin. Dual antiplatelet therapy (DAPT) suggests benefit over SAPT in reducing MACE and MALE, though studies to date are not conclusive and/or are associated with excess major bleeding. Combining moderate to high intensity vitamin K antagonists with antiplatelet therapy does not reduce MACE or MALE and increases life-threatening bleeding. Rivaroxaban 2.5 mg BID in addition to aspirin reduces the incidence of both MACE and MALE as compared to aspirin alone, without increasing life-threatening bleeding. This regimen is associated with a reduced severity of MALE when it does occur. Comparisons across antithrombotic trials in PAD are challenging given the heterogeneity of patient populations and the differing assessment of outcomes. The vascular medicine practitioner can reduce ischemic cardiac and limb events, as well as minimize life-threatening bleeding, by choosing the optimal antithrombotic regimen in their PAD patients.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".