Management of Patients with Asymptomatic and Symptomatic Carotid Artery Disease: Update on Anti-Thrombotic Therapy
Bibliographic record
Abstract
The most common causes of ischaemic stroke are represented by carotid artery atherosclerotic disease (CAAD) and atrial fibrillation. While oral anticoagulants substantially reduce the incidence of thromboembolic stroke (< 1%/year), the rate of ischaemic stroke and other cardiovascular disease events in patients with CAAD remains high, ranging from 8.4 to 18.1 events per 100 patient-years. Similar to any other atherosclerotic disease, anti-thrombotic therapies are proposed for CAAD to reduce stroke and other cardiovascular events. The 2017 European Society of Cardiology (ESC)/European Society for Vascular Surgery (ESVS) guidelines recommend for patients with asymptomatic CAAD ≥60% the use of aspirin 75 to 100 mg once daily or clopidogrel 75 mg once daily at the exception of patient at very high bleeding risk. For patients with symptomatic CAAD ≥50%, the use of aspirin 75 to 100 mg once daily or clopidogrel 75 mg once daily is recommended. New perspectives for anti-thrombotic therapy for the treatment of patients with CAAD come from the novel dual pathway strategy combining a low-dose anticoagulant (i.e. rivaroxaban) and aspirin that may help reduce long-term ischaemic complications in patients with CAAD. This review summarizes current evidence and recommendations for the anti-thrombotic management of patients with symptomatic or asymptomatic CAAD or those undergoing carotid revascularization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".