Expert Consensus on Ivabradine-based Therapy for Heart Rate Managementin Chronic Coronary Syndrome and Heart Failure with Reduced EjectionFraction in India
Bibliographic record
Abstract
Heart rate is an important indicator of health and disease and the modulation of heart rate can help to improve cardiovascular outcomes. Besides β-blockers, Ivabradine is a wellestablished heart rate modulating drug that reduces heart rate without any hemodynamic effects. This consensus document was developed with the help of expert opinions from cardiologists across India on effective heart rate management in routine clinical practice and choosing an appropriate Ivabradine-based therapy considering the available scientific data and guideline recommendations. Based on the discussion during the meetings, increased heart rate was recognized as a significant predictor of adverse cardiovascular outcomes among patients with chronic coronary syndromes and heart failure with reduced ejection fraction making heart rate modulation important in these subsets. Ivabradine is indicated in the management of chronic coronary syndromes and heart failure with reduced ejection fraction for patients in whom heart rate targets cannot be achieved despite guideline-directed β-blocker dosing or having contraindication/intolerance to β-blockers. A prolonged release once-daily dosage of Ivabradine can be considered in patients already stabilized on Ivabradine twice-daily. Ivabradine/β-blocker fixed-dose combination can also be considered to reduce pill burden. Two consensus algorithms have been developed for further guidance on the appropriate usage of Ivabradine-based therapies. Ivabradine and β-blockers can provide more pronounced clinical improvement in most chronic coronary syndromes and heart failure with reduced ejection fraction patients with a fixed-dose combination providing an opportunity to improve adherence.
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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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".