Multicenter evaluation of a self-expanding carotid stent system with distal protection in the treatment of carotid stenosis.
Bibliographic record
Abstract
PURPOSE: Carotid artery stent placement may be limited by the embolization of atheromatous material. We evaluated the safety and feasibility of the Medtronic Self-Expanding Carotid Stent (Exponent) in combination with the Medtronic Interceptor Carotid Filter System for the treatment of carotid stenosis among patients at high risk for carotid endarterectomy. METHODS: Patients at high risk for carotid endarterectomy but amenable to percutaneous treatment with stent placement were enrolled. Clinical follow-up was performed at 30 days and 6 and 12 months postprocedure. The National Institutes of Health Stroke Scale was assessed before and within 3 days postprocedure and at 30 days and 6 months postprocedure. Angiography was performed pre- and postprocedure, and carotid duplex scans were performed at baseline and at 30 days and 6 months. RESULTS: Fifty-two carotid procedures were performed in 51 patients (mean age, 69 years; 84% of patients were men). The major adverse event (MAE) rate (death, stroke, and myocardial infarction [MI]) at 30 days was 5.9%: 2 strokes and a single death from periprocedural MI. MAE rates after 6 and 12 months were 5.9% and 11.8%, respectively. The delivery success rate was 94.2% (49/52) for the Interceptor Filter System and 95.9% (47/49) for the Exponent Stent. The mean diameter stenosis of the target lesion was reduced from 62.4% preprocedure to 21.2% postprocedure. CONCLUSION: High delivery success rates were achieved with a low rate of MAE (death, stroke, or MI) in a high-risk population. Treatment of carotid artery disease with the Exponent Carotid Stent combined with distal protection from the Interceptor Filter System is effective and safe.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".