Comparison of Efficacy of Ivabradine With Traditional Therapy in Patients With Left Ventricular Dysfunction
Bibliographic record
Abstract
BACKGROUND: Heart failure patients usually present with disease exacerbation that overburdens the hospitals and also increases the risk of mortality with increased heart rate being the main issue. Consideration is being given to drugs for sole heart rate control in addition to conventional therapy. OBJECTIVE: To compare the outcomes of ivabradine to traditional treatment in patients with left ventricular systolic dysfunction. METHODOLOGY: This randomized controlled trial was conducted in the Department of Cardiology, Khyber Teaching Hospital, Peshawar from November 1, 2020, to May 31, 2021. Patients aged 30-65 years of age and of either gender with heart failure were enrolled in the study. Patients were screened for New York Heart Association (NYHA) class and were enrolled into one of the two groups. In group 1, patients were started on traditional treatment, while group 2 patients were given ivabradine as an add-on therapy. Follow-up was made at the end of the second month for evaluation of the outcomes. RESULTS: Each group had 119 patients, with a mean age of 58.05±4.98 years. Group 1, consisted of 61.3% of the patients in NYHA 3, while 38.65% were in NYHA 4. In group 2, NYHA 3 and NYHA 4 patients were 59.6% and 40.3%, respectively. Upon follow-up, there were greater improvements in group 2 as compared to group 1 based on NYHA classifications, with NYHA 2 [47.05% (group 2) vs. 13.44% (group 1)], NYHA 3 [42.85% (group 2) vs. 61.34% (group 1)] and NYHA 4 [10.08% (group 2) vs. 25.21% (group 1)], p < 0.05. CONCLUSIONS: Obtaining a more optimal heart rate with ivabradine in patients with congestive heart failure is reflected in an improvement in NYHA classification.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".