Selecting oral antithrombotic therapies in peripheral arterial disease: A guide for practitioners
Bibliographic record
Abstract
PURPOSE: The purpose of this review is to guide practitioners through the certainty, and uncertainty, that surrounds optimal management of antithrombotic therapies in patients with lower-extremity peripheral arterial disease. It also provides practitioners with a framework from which to apply these therapies safely and effectively to optimize patient outcomes. SUMMARY: Peripheral arterial disease is an underdiagnosed and undertreated disease entity. Chronic antithrombotic therapies play a pivotal role in the prevention of thrombotic events in patients with lower-extremity peripheral arterial disease. Whether antiplatelet therapy, oral anticoagulation, or a combination of antiplatelet and anticoagulant therapies is best suited to prevent major cardiovascular and limb events in this patient population has been a long-standing clinical question. There is a great deal of variability in real-world practice as to which agents and dose intensities are used chronically for this purpose. Recent major publications exploring the use of "dual-pathway inhibition" have helped clarify best antithrombotic practices in patients with symptomatic peripheral arterial disease, and these have had a major impact on recently updated guidelines in the US, Europe, and Canada. CONCLUSION: Pharmacists play an important role in reevaluating antithrombotic regimens for all patients with peripheral arterial disease, recognizing that recent landmark publications have led to substantial changes to international guidelines. Dual-pathway inhibition with combined low-dose rivaroxaban and low-dose aspirin therapy should be considered in all patients with symptomatic peripheral arterial disease.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.008 |
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".