Placebo-Controlled, Randomized Clinical Trial of Azimilide for Prevention of Ventricular Tachyarrhythmias in Patients With an Implantable Cardioverter Defibrillator
Bibliographic record
Abstract
BACKGROUND: Although implanted cardioverter defibrillators (ICDs) effectively treat sustained ventricular tachyarrhythmias, up to 50% of ICD recipients eventually require concomitant antiarrhythmic drug therapy to prevent symptomatic arrhythmia recurrences and hence reduce the number of device therapies. METHODS AND RESULTS: A total of 633 ICD recipients were enrolled in a randomized, double-blind, placebo-controlled study to evaluate the effect of daily doses of 75 or 125 mg of azimilide on recurrent symptomatic ventricular tachyarrhythmias and ICD therapies. Total all-cause shocks plus symptomatic ventricular tachycardia (VT) terminated by antitachycardia pacing (ATP) were significantly reduced by azimilide, with relative risk reductions of 57% (hazard ratio [HR]=0.43, 95% CI 0.26 to 0.69, P=0.0006) and 47% (HR=0.53, 95% CI 0.34 to 0.83, P=0.0053) at 75- and 125-mg doses, respectively. The reductions in all-cause shocks with both doses of azimilide did not achieve statistical significance. The incidence of all appropriate ICD therapies (shocks or ATP-terminated VT) was reduced significantly among patients taking 75 mg of azimilide (HR=0.52, 95% CI 0.30 to 0.89, P=0.017) and those taking 125 mg of azimilide (HR=0.38, 95% CI 0.22 to 0.65, P=0.0004). Five patients in the azimilide groups and 1 patient in the placebo group had torsade de pointes; all were successfully treated by the device. One patient taking 75 mg of azimilide had severe but reversible neutropenia. CONCLUSIONS: Azimilide significantly reduced the recurrence of VT or ventricular fibrillation terminated by shocks or ATP in ICD patients, thereby reducing the burden of symptomatic ventricular tachyarrhythmia.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".