β-blocker Therapy is Not Associated with Reductions in Angina or Cardiovascular Events After Coronary Artery Bypass Graft Surgery: Insights from the IMAGINE Trial
Bibliographic record
Abstract
PURPOSE: To evaluate whether β-blockers were associated with a reduction in cardiovascular events or angina after Coronary Artery Bypass Graft (CABG) surgery, in otherwise stable low-risk patients during a mid-term follow-up. METHODS: We performed a post-hoc analysis of the IMAGINE (Ischemia Management with Accupril post-bypass Graft via Inhibition of angiotensin coNverting Enzyme) trial, which tested the effect of Quinapril in 2553 hemodynamically stable patients with left ventricular ejection fraction (LVEF) >40 %, after scheduled CABG. The association between β-blocker therapy and the incidence of cardiovascular events (death, cardiac arrest, myocardial infarction, revascularizations, angina requiring hospitalization, stroke or hospitalization for heart failure) or angina that was documented to be due to underlying ischemia was tested with Cox regression and propensity adjusted analyses. RESULTS: In total, 1709 patients (76.5 %) were using a β-blocker. Patients had excellent control of risk factors; with mean systolic blood pressure being 121 ± 14 mmHg, mean LDL cholesterol of 2.8 mmol/l, 59% of patients received statins and 92% of patients received antiplatelet therapy. During a median follow-up of 33 months, β-blocker therapy was not associated with a reduction in cardiovascular events (hazard ratio 0.97; 95 % confidence interval 0.74-1.27), documented angina (hazard ratio 0.85; 95 % confidence interval 0.61-1.19) or any of the individual components of the combined endpoint. There were no relevant interactions for demographics, comorbidities or surgical characteristics. Propensity matched and time-dependent analyses revealed similar results. CONCLUSIONS: β-blocker therapy after CABG is not associated with reductions in angina or cardiovascular events in low-risk patients with preserved LVEF, and may not be systematically indicated in such patients.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| 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".