Ranolazine in High-Risk Patients With Implanted Cardioverter-Defibrillators
Bibliographic record
Abstract
BACKGROUND: Ventricular tachycardia (VT) and ventricular fibrillation (VF) remain a challenging problem in patients with implantable cardioverter-defibrillators (ICDs). OBJECTIVES: This study aimed to determine whether ranolazine administration decreases the likelihood of VT, VF, or death in patients with an ICD. METHODS: This was double-blind, placebo-controlled clinical trial in which high-risk ICD patients with ischemic or nonischemic cardiomyopathy were randomized to 1,000 mg ranolazine twice a day or placebo. The primary endpoint was VT or VF requiring appropriate ICD therapy or death, whichever occurred first. Pre-specified secondary endpoints included ICD shock for VT, VF, or death and recurrent VT or VF requiring ICD therapy. RESULTS: Among 1,012 ICD patients (510 randomized to ranolazine and 502 to placebo) the mean age was 64 ± 10 years and 18% were women. During 28 ± 16 months of follow-up there were 372 (37%) patients with primary endpoint, 270 (27%) patients with VT or VF, and 148 (15%) deaths. The blinded study drug was discontinued in 199 (39.6%) patients receiving placebo and in 253 (49.6%) patients receiving ranolazine (p = 0.001). The hazard ratio for ranolazine versus placebo was 0.84 (95% confidence interval: 0.67 to 1.05; p = 0.117) for VT, VF, or death. In a pre-specified secondary analysis, patients randomized to ranolazine had a marginally significant lower risk of ICD therapies for recurrent VT or VF (hazard ratio: 0.70; 95% confidence interval: 0.51 to 0.96; p = 0.028). There were no other significant treatment effects in other pre-specified secondary analyses, which included individual components of the primary endpoint, inappropriate shocks, cardiac hospitalizations, and quality of life. CONCLUSIONS: In high-risk ICD patients, treatment with ranolazine did not significantly reduce the incidence of the first VT or VF, or death. However, the study was underpowered to detect a difference in the primary endpoint. In prespecified secondary endpoint analyses, ranolazine administration was associated with a significant reduction in recurrent VT or VF requiring ICD therapy without evidence for increased mortality. (Ranolazine Implantable Cardioverter-Defibrillator Trial [RAID]; NCT01215253).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".