Adjunctive antiarrhythmic drug therapy in patients with implantable cardioverter defibrillators: a systematic review
Bibliographic record
Abstract
AIMS: To assess the efficacy and safety of adjunctive antiarrhythmic drug therapy for preventing implantable cardioverter defibrillator (ICD) therapies. METHODS AND RESULTS: We conducted a systematic literature search to identify all randomized, controlled trials assessing the efficacy of adjunctive antiarrhythmic drug therapy. Trial data were reviewed and extracted independently by two investigators in an unblinded, standardized manner. Eight trials including a total of 1889 patients were analysed. There was heterogeneity in the type of antiarrhythmic used in the treatment arm (amiodarone, sotalol, azimilide, and dofetilide) as well as in the control group (five trials compared with placebo and three trials compared with beta-blocker). The main outcome, risk of shock therapy, was reduced when comparing amiodarone plus beta-blocker with beta-blocker alone (HR 0.27; 95% CI 0.14-0.52) and when comparing sotalol with placebo (HR 0.55; 95% CI 0.4-0.78). The effect was not conclusive when comparing sotalol with other beta-blocker (HR 0.61; 95% CI 0.37-1) and azimilide or dofetilide with placebo (HR 0.78; 95% CI 0.58-1.04 and HR 0.67; 95% CI 0.43-1.04, respectively). Although there were some benefits for secondary outcomes in all antiarrhythmics, the magnitude of the benefit was higher with amiodarone. CONCLUSION: Amiodarone is the most effective treatment to reduce ICD shock therapies. The benefit of other antiarrhythmics is limited to secondary outcomes.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".