Efficacy and safety of dronedarone across age and sex subgroups: a<i>post hoc</i>analysis of the ATHENA study among patients with non-permanent atrial fibrillation/flutter
Bibliographic record
Abstract
AIMS: Age and sex may impact the efficacy of antiarrhythmic drugs on cardiovascular outcomes and arrhythmia recurrences in patients with atrial fibrillation (AF). We report on a post hoc analysis of the ATHENA study (NCT00174785), which examined cardiovascular outcomes in patients with non-permanent AF treated with dronedarone vs. placebo. METHODS AND RESULTS: Efficacy and safety of dronedarone were assessed in patients according to age and sex. Baseline characteristics were comparable across subgroups, except for cardiovascular comorbidities, which were more frequent with increasing age. Dronedarone significantly reduced the risk of cardiovascular hospitalization or death due to any cause among patients 65-74 [n = 1830; hazard ratio (HR) 0.71, 95% confidence interval (CI) 0.60-0.83; P < 0.0001] and ≥75 (n = 1925; HR 0.75, 95% CI 0.65-0.88; P = 0.0002) years old and among males (n = 2459; HR 0.74, 95% CI 0.64-0.84; P < 0.00001) and females (n = 2169; HR 0.77, 95% CI 0.67-0.89; P = 0.0002); outcomes were similar for time to AF/AFL recurrence. Among patients aged <65 years (n = 873), cardiovascular hospitalization or death due to any cause with dronedarone vs. placebo was associated with an HR of 0.89 (95% CI 0.71-1.11; P = 0.3). The incidence of all treatment-emergent adverse events (TEAEs) and TEAEs leading to treatment discontinuation was comparable among males and females, and increased with increasing age. CONCLUSIONS: These results support the use of dronedarone for the improvement of clinical outcomes among patients aged ≥65 years and regardless of sex.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".