Cost-Effectiveness of Coronary Artery Bypass Surgery Versus Medicine in Ischemic Cardiomyopathy: The STICH Randomized Clinical Trial
Bibliographic record
Abstract
BACKGROUND: The STICH Randomized Clinical Trial (Surgical Treatment for Ischemic Heart Failure) demonstrated that coronary artery bypass grafting (CABG) reduced all-cause mortality rates out to 10 years compared with medical therapy alone (MED) in patients with ischemic cardiomyopathy and reduced left ventricular function (ejection fraction ≤35%). We examined the economic implications of these results. METHODS: We used a decision-analytic patient-level simulation model to estimate the lifetime costs and benefits of CABG and MED using patient-level resource use and clinical data collected in the STICH trial. Patient-level costs were calculated by applying externally derived US cost weights to resource use counts during trial follow-up. A 3% discount rate was applied to both future costs and benefits. The primary outcome was the incremental cost-effectiveness ratio assessed from the US health care sector perspective. RESULTS: For the CABG arm, we estimated 6.53 quality-adjusted life-years (95% CI, 5.70-7.53) and a lifetime cost of $140 059 (95% CI, $106 401 to $180 992). For the MED arm, the corresponding estimates were 5.52 (95% CI, 5.06-6.09) quality-adjusted life-years and $74 894 lifetime cost (95% CI, $58 372 to $93 541). The incremental cost-effectiveness ratio for CABG compared with MED was $63 989 per quality-adjusted life-year gained. At a societal willingness-to-pay threshold of $100 000 per quality-adjusted life-year gained, CABG was found to be economically favorable compared with MED in 87% of microsimulations. CONCLUSIONS: In the STICH trial, in patients with ischemic cardiomyopathy and reduced left ventricular function, CABG was economically attractive relative to MED at current benchmarks for value in the United States. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT00023595.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".