Ivabradine in Combination with Metoprolol Improves Symptoms and Quality of Life in Patients with Stable Angina Pectoris: A post hoc Analysis from the ADDITIONS Trial
Bibliographic record
Abstract
OBJECTIVES: Elevated heart rate can increase myocardial oxygen demand and reduce myocardial perfusion, provoking myocardial ischemia and angina symptoms. We evaluated adding ivabradine to the therapy of patients on metoprolol. METHODS: ADDITIONS (prActical Daily efficacy anD safety of Procoralan® In combinaTION with betablockerS) was a multicenter, 4-month, noninterventional, prospective, open-label trial that involved stable-angina patients. Along with metoprolol, patients received ivabradine (5 or 7.5 mg, b.i.d.). We investigated the effect of ivabradine on heart rate, angina attacks, nitrate consumption, quality of life (QoL) and tolerability as well as the influence of baseline heart rate. RESULTS: Heart rate fell by 19.7 ± 11.2 bpm, with an 8-fold decrease in weekly angina attacks (1.7 ± 2.2 to 0.2 ± 0.7) and nitrate consumption (2.4 ± 3.4 to 0.3 ± 0.9). Patient numbers in Canadian Cardiovascular Society class I more than doubled (i.e. from 29 to 65%) and QoL improved (the EQ-5D index and visual analog scale scores rose from 0.68 ± 0.27 to 0.84 ± 0.20 and 58.1 ± 18.4 to 72.2 ± 15.5 mm, respectively). The effect of ivabradine was greater in patients with a baseline heart rate ≥70 bpm (mean reduction in heart rate -21.2 ± 10.4 bpm, with a relative reduction in angina attacks and short-acting nitrate consumption of 87.1 and 87.2%, respectively). CONCLUSIONS: Ivabradine combined with metoprolol safely and effectively reduces heart rate, angina attacks and nitrate use, and improves QoL in stable-angina patients.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".