Efficacy and safety of dronedarone by atrial fibrillation history duration: Insights from the<scp>ATHENA</scp>study
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation/atrial flutter (AF/AFL) burden increases with increasing duration of AF/AFL history. HYPOTHESIS: Outcomes with dronedarone may also be impacted by duration of AF/AFL history. METHODS: In this post hoc analysis of ATHENA, efficacy and safety of dronedarone vs placebo were assessed in groups categorized by time from first known AF/AFL episode to randomization (ie, duration of AF/AFL history): <3 months (short), 3 to <24 months (intermediate), and ≥ 24 months (long). RESULTS: Of 2859 patients with data on duration of AF/AFL history, 45.3%, 29.6%, and 25.1% had short, intermediate, and long histories, respectively. Patients in the long history group had the highest prevalence of structural heart disease and were more likely to be in AF/AFL at baseline. Placebo-treated patients in the long history group also had the highest incidence of AF/AFL recurrence and cardiovascular (CV) hospitalization during the study. The risk of first CV hospitalization/death from any cause was lower with dronedarone vs placebo in patients with short (hazard ratio, 0.79 [95% confidence interval: 0.65-0.96]) and intermediate (0.72 [0.56-0.92]) histories; a trend favoring dronedarone was also observed in patients with long history (0.84 [0.66-1.07]). A similar pattern was observed for first AF/AFL recurrence. No new drug-related safety issues were identified. CONCLUSIONS: Patients with long AF/AFL history had the highest burden of AF/AFL at baseline and during the study. Dronedarone significantly improved efficacy vs placebo in patients with short and intermediate AF/AFL histories. While exploratory, these results support the potential value in initiating rhythm control treatment early in patients with AF/AFL.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".