Effects of Angiotensin-Converting Enzyme Inhibition in Low-Risk Patients Early After Coronary Artery Bypass Surgery
Bibliographic record
Abstract
BACKGROUND: Early after coronary artery bypass surgery (CABG), activation of numerous neurohumoral and endogenous vasodilator systems occurs that could be influenced favorably by angiotensin-converting enzyme inhibitors. METHODS AND RESULTS: The Ischemia Management with Accupril post-bypass Graft via Inhibition of the coNverting Enzyme (IMAGINE) trial tested whether early initiation (< or = 7 days) of an angiotensin-converting enzyme inhibitor after CABG reduced cardiovascular events in stable patients with left ventricular ejection fraction > or = 40%. The trial was a double-blind, placebo-controlled study of 2553 patients randomly assigned to quinapril, target dose 40 mg/d, or placebo, who were followed up to a maximum of 43 months. The mean (SD) age was 61 (10) years. The incidence of the primary composite end point (cardiovascular death, resuscitated cardiac arrest, nonfatal myocardial infarction, coronary revascularization, unstable angina or heart failure requiring hospitalization, documented angina, and stroke) was 13.7% in the quinapril group and 12.2% in the placebo group (hazard ratio 1.15, 95% confidence interval 0.92 to 1.42, P=0.212) over a median follow-up of 2.95 years. The incidence of the primary composite end point increased significantly in the first 3 months after CABG in the quinapril group (hazard ratio 1.52, 95% confidence interval 1.03 to 2.26, P=0.0356). Adverse events also increased in the quinapril group, particularly during the first 3 months after CABG. CONCLUSIONS: In patients at low risk of cardiovascular events after CABG, routine early initiation of angiotensin-converting enzyme inhibitor therapy does not appear to improve clinical outcome up to 3 years after CABG; however, it increases the incidence of adverse events, particularly early after CABG. Thus, early after CABG, initiation of angiotensin-converting enzyme inhibitor therapy should be individualized and continually reassessed over time according to risk.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".