Cost-Effectiveness of Carotid Endarterectomy vs. Carotid Stenting: a Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Carotid artery stenting (CAS) and carotid endarterectomy (CEA) are gold-standard treatments of carotid artery stenosis. This study aims to identify the cost-effectiveness of CEA vs CAS. METHODS: Studies were screened through PubMed, MEDLINE, and Embase using PRISMA guidelines, and required ≥ 20 participants who were ≥ 16 years, alongside costs at 1-year postoperatively. The Shapiro-Wilk test, independent sample t-tests, ANOVA, and Spearman's R were used, with costs adjusted to 2024. A random-effects model was used to compare cost-effectiveness. Bias assessment was according to the Cochrane Risk of Bias 2.0 tool and the Newcastle-Ottawa Scale. RESULTS: 7 studies were included, with a sample of 6493 participants (3418 M, 3075 F). 2932 and 3511 participants underwent CEA and CAS respectively. CEA reported a significantly longer mean length of procedure (191.92 vs. 77.5 min, p < 0.0001) and length of stay (3.13 vs. 2.60 days, p < 0.0001) vs. CAS. The mean adjusted cost of CEA and CAS were $18156.60 (6466) and $17711.01 (5511) respectively. Studies reported lower risks of stroke (2.12% vs. 3.65%, p < 0.001), higher risks of myocardial infarctions (1.70% vs. 1.42%, p < 0.01), and higher risks of other complications for CEA vs. CAS respectively. The expected 1-year cost of CEA was marginally lower than CAS ($21264.03 vs. $21433.14, p < 0.05). The cost-effectiveness of CEA was marginally better than CAS (ratio = 1.019, 95% CI [1.017, 1.020)]. CONCLUSIONS: CEA provides marginally improved cost-effectiveness over CAS, providing long-term cost benefits to centers with large surgical volumes. However, shorter procedural times and inpatient stays with CAS may improve overall productivity. Cost should hence not be a deciding factor when choosing between CEA and CAS.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.001 | 0.002 |
| 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 teacher head, 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".