From coronary artery disease to heart failure: potential benefits of ivabradine
Bibliographic record
Abstract
In addition to the beneficial effects of heart rate reduction for the prevention of angina, a lower heart rate is also associated with a more favourable prognosis in patients with coronary artery disease (CAD). A high resting heart rate is a strong predictor for cardiovascular mortality and morbidity in patients with CAD. Patients with resting heart rate above 77 bpm are also prone to more re-hospitalizations for cardiovascular reasons, independently of major risk factors compared with patients with lower resting heart rates. These issues are clinically important because they support the relevance of testing the effect of lowering heart rate to reduce cardiovascular mortality and morbidity. The value of ivabradine for reduction in hard cardiovascular events in patients with ischaemic heart disease is presently being tested in the ongoing large-scale BEAUTIFUL (morBidity–mortality EvAlUaTion of the If inhibitor ivabradine in patients with coronary disease and left ventricULar dysfunction) study. Also, the prognostic value of heart rate in patients with heart failure and the lack of intrinsic negative inotropic effects of ivabradine have prompted its evaluation in addition to modern multifaceted therapy of heart failure in the Systolic Heart failure treatment with If inhibitor ivabradine Trial (SHIFT). These large-scale clinical trials will help to determine whether the spectrum of patients benefiting from a pure heart rate-reducing agent, such as ivabradine, goes beyond those with angina and whether the clinical benefits are much greater than prevention of angina and extend to reduction in cardiovascular mortality and morbidity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.007 | 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".