Ivabradine in Patients with Ischemic Heart Disease - A Prospective, Longitudinal, Comparative Study to Metoprolol
Bibliographic record
Abstract
Background: Coronary artery disease (CAD) is the leading cause of morbidity and mortality in developing countries with stable angina being the most common symptom. Heart rate is a key etiological factor in the pathophysiology of CAD as tachycardia induces myocardial ischemia by increasing oxygen demand and decreasing perfusion. So reduction in heart rate is the cornerstone of CAD management. Reducing heart rate with conventional drugs like ß-blocker is associated with drug interaction and adverse effects. Ivabradine is a novel heart rate lowering agent which is a selective inhibitor of the pacemaker I(f) current in the SA node. Objectives: To compare the efficacy and safety of ivabradine to metoprolol in patients with CAD. Methods: A prospective, longitudinal, comparative study was carried out in the Department of Cardiology of our hospital. 60 patients diagnosed with CAD were divided in to 2 treatment groups: Group 1 and 2 received Ivabradine(5mg/day) and Metoprolol(50mg/day) respectively. Patients were assessed for HR, Ejection fraction (EF), Canadian cardiovascular society (CCS) class of angina, QOL scores. Two follow ups were done at 90, 180 days. Long term QOL (EQVAS) evaluated compared statistically. Results: Ivabradine reduced HR from 89.07±1.99 to 75.17±0.40 bpm and metoprolol from 90.47±1.75 to 77.53±0.86bpm, EF from 42.67± 1.09% to 52.37± 0.33%. Both groups showed significant but comparable improvement in CCS class of angina and EQ-5D-3L dimensions at 6 months. Over longer term (18 months) statistically superior significance in Ivabradine group in EQVAS (p.02). Also there was significant decrease in episodes of angina attack and also the requirement of nitroglycerine tablets. Conclusion: Ivabradine was found to be safer and more effective in preventing and treating angina attacks in patients with CAD.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".