Long-Term Comparison of the Implantable Cardioverter Defibrillator Versus Amiodarone
Bibliographic record
Abstract
BACKGROUND: The implantable cardioverter defibrillator (ICD) is superior to amiodarone for secondary prophylaxis of sudden cardiac death. However, the magnitude of this benefit over long-term follow-up is not known. Thus, our objective was to evaluate the long-term consequences of using amiodarone versus an ICD as first-line monotherapy in patients with a prior history of sustained ventricular tachycardia/ventricular fibrillation or cardiac arrest. METHODS AND RESULTS: A total of 120 patients were enrolled at St Michael's Hospital in the Canadian Implantable Defibrillator Study (CIDS) and were randomly assigned to receive either amiodarone (n=60) or an ICD (n=60). The treatment strategy was not altered after the end of CIDS unless the initial assigned therapy was not effective or was associated with serious side effects. After a mean follow-up of 5.6+/-2.6 years, there were 28 deaths (47%) in the amiodarone group, compared with 16 deaths (27%) in the ICD group (P=0.0213). Total mortality was 5.5% per year in the amiodarone group versus 2.8% per year in the ICD group (hazard ratio of amiodarone: ICD, 2.011; 95% confidence interval, 1.087 to 3.721; P=0.0261). In the amiodarone group, 49 patients (82% of all patients) had side effects related to amiodarone, of which 30 patients (50% of all patients) required discontinuation or dose reduction; 19 patients crossed over to ICD because of amiodarone failure (n=7) or side effects (n=12). CONCLUSIONS: In a subset of CIDS, the benefit of the ICD over amiodarone increases with time; most amiodarone-treated patients eventually develop side effects, have arrhythmia recurrences, or die.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".