Abstract 10169: Do Beta-Blockers Confer Cardiovascular Protection in Patients With Stable Coronary Artery Disease in the Contemporary Era?
Bibliographic record
Abstract
Introduction: Previous studies have failed to show a cardioprotective benefit of beta-blockers in patients with stable coronary artery disease (CAD). These studies, however, were frequently limited by either small or heterogenous populations. We aimed to determine the association between beta-blocker therapy and long-term cardiovascular events in patients with angiographically-documented stable CAD. Methods: We identified all patients ≥ 66 years undergoing elective coronary angiography in Ontario, Canada from 2009 to 2019, who had significant coronary stenoses. Patients with heart failure or recent myocardial infarction (MI) were excluded. We used a new user design by defining beta-blocker use as ≥1 prescription claims in the 90 days preceding or after coronary angiography and excluded those with beta-blocker use in the previous year. The main outcome was a composite of all-cause mortality, hospitalization for heart failure or MI. Propensity score and inverse probability of treatment weighting were used to deal with confounding. Results: We included 28,039 patients (mean age: 73.0 ± 5.6y; 66.2% male), 12,695 (45.3%) were treated with beta-blockers. The 5-year rate of the primary outcome in the weighted cohort was 14.3% in the beta-blocker group and 16.1% in the no beta-blocker group (HR: 0.92; 95% CI: 0.86 to 0.98; p=0.006), which was primarily driven by reductions in MI (HR: 0.87; 95% CI: 0.77 to 0.99; p=0.031). No significant difference was observed regarding all-cause death (HR: 0.95; 95% CI: 0.88 to 1.02) and hospitalization for heart failure (HR: 0.93; 95% CI: 0.82 to 1.06). Findings were consistent across subgroups, including sex, age, diabetes, and previous revascularization (p-interaction > 0.1; Figure). Conclusions: In patients with angiographically-documented stable CAD without heart failure or a recent MI, beta-blockers were associated with a significant reduction in the composite of all-cause mortality, hospitalization for heart failure or MI.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".