Ivabradine: the evidence of its therapeutic impact in angina.
Bibliographic record
Abstract
INTRODUCTION: Stable angina pectoris (SAP) is a widely prevalent disease affecting 30 000 to 40 000 per million people in Europe and the US. SAP is associated with reductions in quality of life and ability to work, and increased use of healthcare resources. Ivabradine is a drug with a unique therapeutic target, the I(f) current of the sinus node, developed for the treatment of cardiovascular diseases including SAP. It has an exclusive heart rate reducing effect, without any negative effect on left ventricular function or coronary vasodilatation. AIMS: The aim of this paper is to review the evidence concerning the use of ivabradine in the treatment of SAP. EVIDENCE REVIEW: Ivabradine is an effective antianginal and antiischemic drug, not inferior to the beta blocker atenolol and the calcium channel antagonist (CCA) amlodipine. It decreases the frequency of angina attacks and increases the time to anginal symptoms during exercise. Because of its exclusive chronotropic effect, ivabradine is not associated with the typical adverse reactions associated with beta blockers or other antianginal drugs. CLINICAL VALUE: Clinical evidence shows that ivabradine is a very good antiischemic and antianginal agent, being as effective as beta blockade and CCA therapy in controlling myocardial ischemia and symptoms of stable angina. Ongoing studies will determine the potential of ivabradine to improve morbidity and mortality in coronary artery disease and heart failure.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".