Cost‐Effectiveness of Paclitaxel‐Coated Balloon Angioplasty in Patients With Drug‐Eluting Stent Restenosis
Bibliographic record
Abstract
BACKGROUND: The economic impact of drug-eluting stent (DES) in-stent restenosis (ISR) is substantial, highlighting the need for cost-effective treatment strategies. HYPOTHESIS: Compared to plain old balloon angioplasty (POBA) or repeat DES implantation, drug-coated balloon (DCB) angioplasty is a cost-effective therapy for DES-ISR. METHODS: A Markov state-transition model was used to compare DCB angioplasty with POBA and repeat DES implantation. Model input parameters were obtained from the literature, and the cost analysis was conducted from a German healthcare payer's perspective. Extensive sensitivity analyses were performed. RESULTS: Initial procedure costs amounted to €3488 for DCB angioplasty and to €2782 for POBA. Over a 6-month time horizon, the DCB strategy was less costly (€4028 vs €4169) and more effective in terms of life-years (LYs) gained (0.497 versus 0.489) than POBA. The DES strategy incurred initial costs of €3167 and resulted in 0.494 LYs gained, at total costs of €4101 after a 6-month follow-up. Thus, DCB angioplasty was the least costly and most effective strategy. Base-case results were influenced mostly by initial procedure costs, target lesion revascularization rates, and the costs of dual antiplatelet therapy. CONCLUSIONS: DCB angioplasty is a cost-effective treatment option for coronary DES-ISR. The higher initial costs of the DCB strategy compared to POBA or repeat DES implantation are offset by later cost savings.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".