Safety and Efficacy of Ivabradine in the Management of Stable Angina Pectoris
Bibliographic record
Abstract
The first selective Ifcurrent inhibitor, ivabradine, lowers heart rate (HR) at rest and during exercise with no vasomotor, negative inotropic, or negative lusitropic effects. Given that elevated resting HR is a key factor in the onset of myocardial ischemia and a strong independent predictor of cardiovascular outcomes, ivabradine provides new therapeutic prospects in coronary artery disease (CAD). Its selective HR-lowering action has proven anti-ischemic and anti-anginal efficacy, and ivabradine is currently indicated for the symptomatic treatment of stable angina pectoris. Ivabradine can also be safely combined with other anti-anginal agents, and addition of ivabradine to beta-blocker therapy further improves anti-ischemic efficacy and exercise capacity of patients with stable angina. The recent BEAUTIFUL trial demonstrated that although the primary endpoint was not met in the overall population, addition of ivabradine on top of standard preventive treatments significantly reduced the risk of coronary events in stable CAD patients with left ventricular systolic dysfunction among the subgroup of patients with a resting HR ≥ 70 bpm. This is in accordance with pre-clinical data showing that long-term HR reduction improves endothelial function and reduces the progression of atherosclerosis. A significant proportion of patients with stable angina have elevated resting HR and ivabradine should therefore be considered as an important therapy in these cases. In combination with other standard treatments, ivabradine can improve angina and could potentially improve coronary outcomes. Ongoing and future clinical studies will evaluate the presence and magnitude of the cardioprotective benefits of HR lowering with ivabradine in patients with cardiovascular diseases.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".