Role of Ivabradine in the Treatment of Patients With Cardiovascular Disease
Bibliographic record
Abstract
OBJECTIVE: To review the role of heart rate in myocardial ischemia and heart failure with reduced ejection fraction (HFrEF) as well as ivabradine's pharmacology and pharmacokinetics, clinical trials, and place in therapy. DATA SOURCES: We conducted MEDLINE searches from 1980 to October 2015 using the terms heart failure, HFrEF, angina, f-channel inhibitor, and ivabradine, with forward and backward citation tracking. STUDY SELECTION AND DATA EXTRACTION: English-language trials assessing ivabradine were obtained. Studies and narrative reviews of the topic areas were incorporated if they provided relevant data to inform the practicing clinician. DATA SYNTHESIS: In the SIGNIFY (Study Assessing the Morbidity-Mortality Benefits of the If Inhibitor Ivabradine in Patients with Coronary Artery Disease) trial, there was no difference in the primary composite end point of cardiovascular (CV) mortality or nonfatal myocardial infarction with ivabradine use in patients with stable coronary artery disease (CAD) versus placebo (P = 0.20). In the subgroup with Canadian Cardiovascular Society angina class ≥II, there was an 18% increase in the primary end point with ivabradine versus placebo (P = 0.02). In HFrEF patients, ivabradine reduced CV mortality or heart failure hospitalizations versus placebo, as seen in the SHIFT (Systolic Heart failure treatment with the If inhibitor ivabradine Trial; P < 0.05). CONCLUSIONS: The SIGNIFY trial negated much of the enthusiasm for using ivabradine in CAD. Ivabradine is a promising therapy in HFrEF based on the results of the SHIFT, but it is an adjunctive therapy, not a substitute for drugs with proven mortality benefits.
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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 | 0.004 | 0.014 |
| 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) | 0.003 | 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".