Efficacy of <i>I</i><sub>f</sub> Inhibition with Ivabradine in Different Subpopulations with Stable Angina Pectoris
Bibliographic record
Abstract
OBJECTIVES: The antianginal and anti-ischemic efficacy of ivabradine has been demonstrated in large-scale trials. Pooling trial data allowed for subpopulation analyses of ivabradine's antianginal efficacy. METHODS: Data on the frequency of angina attacks, short-acting nitrate consumption, and heart rate were pooled from 5 randomized trials in patients with stable angina pectoris receiving 5, 7.5, or 10 mg of ivabradine b.i.d. for 3 or 4 months. The subpopulations were defined according to age, sex, disease characteristics, and comorbidities (severity of angina, history of myocardial infarction, cerebrovascular disease, revascularization status, diabetes, asthma/chronic obstructive pulmonary disease, or peripheral vascular disease). RESULTS: Efficacy data were available for 2,425 patients (full analysis set), in whom ivabradine reduced the frequency of diary-based angina attacks by 59.4% and nitrate consumption by 53.7%. All subpopulations experienced 51-70% reductions in the frequency of angina attacks, with similar reductions for the other parameters studied. Ivabradine's efficacy was maintained in the presence of different comorbidities. In the safety set, ivabradine reduced heart rate by 14.5%. Ivabradine had a good safety and tolerability profile in all the subpopulations assessed. CONCLUSIONS: The antianginal efficacy of ivabradine was consistent across all the subpopulations analyzed, independent of the severity of angina and the presence of a comorbidity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".