When Is Carotid Angioplasty and Stenting the Cost-Effective Alternative for Revascularization of Symptomatic Carotid Stenosis? A Canadian Health System Perspective
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Carotid revascularization procedures can be complicated by stroke. Additional disability adds to the already high costs of the procedure. To weigh the cost and benefit, we estimated the cost-utility of carotid angioplasty and stenting compared with carotid endarterectomy among patients with symptomatic carotid stenosis, with special emphasis on scenario analyses that would yield carotid angioplasty and stenting as the cost-effective alternative relative to carotid endarterectomy. MATERIALS AND METHODS: A cost-utility analysis from the perspective of the health system payer was performed by using a Markov analytic model. Clinical estimates were based on a meta-analysis. The procedural costs were derived from a microcosting data base. The costs for hospitalization and rehabilitation of patients with stroke were based on a Canadian multicenter study. Utilities were based on a randomized controlled trial. RESULTS: In the base case analysis, carotid angioplasty and stenting were more expensive (incremental cost of $6107) and had a lower utility (-0.12 quality-adjusted life years) than carotid endarterectomy. The results are sensitive to changes in the risk of clinical events and the relative risk of death and stroke. Carotid angioplasty and stenting were more economically attractive among high-risk surgical patients. For carotid angioplasty and stenting to become the preferred option, their costs would need to fall from more than $7300 to $4350 or less and the risks of the periprocedural and annual minor strokes would have to be equivalent to that of carotid endarterectomy. CONCLUSIONS: In the base case analysis, carotid angioplasty and stenting were associated with higher costs and lower utility compared with carotid endarterectomy for patients with symptomatic carotid stenosis. Carotid angioplasty and stenting were cost-effective for patients with high surgical risk.
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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 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".