Meta-Analysis of Randomized Controlled Trials Comparing the Long-Term Outcomes of Carotid Artery Stenting Versus Endarterectomy
Bibliographic record
Abstract
BACKGROUND: Stenting is an endovascular alternative to endarterectomy for the management of carotid stenosis, but its long-term safety and efficacy relative to endarterectomy remain unclear. Our objective was to compare the safety and efficacy of stenting with those of endarterectomy, with a particular focus on long-term outcomes, via meta-analysis of randomized controlled trials (RCTs). METHODS AND RESULTS: We systematically searched PubMed, EMBASE, MEDLINE, and the Cochrane Library for RCTs with ≥50 patients that compared stenting with endarterectomy in patients with carotid stenosis. Periprocedural and long-term outcomes were assessed, with data pooled across RCTs using random-effects models. Eight RCTs were included in our meta-analysis (n=7091), with follow-up ranging from 2.0 to 10.0 years. When compared with endarterectomy, stenting was associated with an increased risk of periprocedural stroke (relative risk, 1.49, 95% confidence interval [CI], 1.11 to 2.01; risk difference, 1.7%; 95% CI, 0.3 to 3.0) but a decreased risk of periprocedural myocardial infarction (relative risk, 0.47; 95% CI, 0.29 to 0.78; risk difference, -0.4%; 95% CI, -0.8% to 0.1%). During long-term follow-up, stenting was associated with an increased risk of stroke (relative risk, 1.36; 95% CI, 1.16 to 1.61) and a composite end point of ipsilateral stroke, periprocedural stroke, or periprocedural death (relative risk, 1.45; 95% CI, 1.20 to 1.75). CONCLUSIONS: Although stenting has more favorable periprocedural outcomes with respect to myocardial infarction, the observed increased risk of stroke and death throughout follow-up with stenting suggests that endarterectomy remains the treatment of choice for carotid stenosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.072 | 0.118 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".