Ivabradine: pre-clinical and clinical evidence in the setting of ventricular arrhythmias.
Bibliographic record
Abstract
BACKGROUND: ) specific inhibitor, is responsible for the sinoatrial node's spontaneous depolarization. According to current guidelines, it is indicated in specific heart failure populations and as a second-line treatment option to improve angina in chronic coronary syndromes. REVIEW OF LITERATURE: The role of ivabradine in the setting of ventricular arrhythmias has been studied in both experimental and clinical studies. Specifically, experimental studies have examined the role of ivabradine in acute myocardial ischemia, reperfusion, digitalis-induced ventricular arrhythmias, and catecholaminergic polymorphic ventricular tachycardia showing promising results. In addition, clinical studies have shown a beneficial role of ivabradine in reducing ventricular arrhythmias. Ivabradine reduced premature ventricular contractions in combination with beta-blockers in dilated cardiomyopathy patients. Similarly, in catecholaminergic polymorphic ventricular tachycardia, ivabradine reduced dobutamine-induced premature ventricular complexes and improved ventricular arrhythmias burden. On the other hand, current data show no beneficial role of ivabradine in reducing ventricular arrhythmias in myocardial ischemia. CONCLUSIONS: Randomized clinical trials are needed to elucidate the role of ivabradine in reducing the burden of ventricular arrhythmias in various clinical settings. HIPPOKRATIA 2022, 26 (2):49-54.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.006 | 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".