Medical Therapy v. PCI in Stable Coronary Artery Disease
Bibliographic record
Abstract
BACKGROUND: Percutaneous coronary intervention (PCI) with either drug-eluting stents (DES) or bare metal stents (BMS) reduces angina and repeat procedures compared with optimal medical therapy alone. It remains unclear if these benefits are sufficient to offset their increased costs and small increase in adverse events. OBJECTIVE: Cost utility analysis of initial medical therapy v. PCI with either BMS or DES. DESIGN: . Markov cohort decision model. Data Sources. Propensity-matched observational data from Ontario, Canada, for baseline event rates. Effectiveness and utility data obtained from the published literature, with costs from the Ontario Case Costing Initiative. TARGET POPULATION: Patients with stable coronary artery disease, confirmed after angiography, stratified by risk of restenosis based on diabetic status, lesion size, and lesion length. Time Horizon. Lifetime. Perspective. Ontario Ministry of Health and Long Term Care. Interventions. Optimal medical therapy, PCI with BMS or DES. OUTCOME MEASURES: Lifetime costs, quality-adjusted life years (QALYs), and the incremental cost-effectiveness ratio (ICER). RESULTS: of Base Case Analysis. In the overall population, medical therapy had the lowest lifetime costs at $22,952 v. $25,081 and $25,536 for BMS and DES, respectively. Medical therapy had a quality-adjusted life expectancy of 10.1 v. 10.26 QALYs for BMS, producing an ICER of $13,271/QALY. The DES strategy had a quality-adjusted life expectancy of only 10.20 QALYs and was dominated by the BMS strategy. This ranking was consistent in all groups stratified by restenosis risk, except diabetic patients with long lesions in small arteries, in whom DES was cost-effective compared with medical therapy (ICER of $18,826/QALY). Limitations. There is the possibility of residual unobserved confounding. CONCLUSIONS: In patients with stable coronary artery disease, an initial BMS strategy is cost-effective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.074 | 0.001 |
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".