Efficacy and safety of dronedarone versus placebo in patients with atrial fibrillation stratified according to renal function: Post hoc analyses of the EURIDIS‐ADONIS trials
Bibliographic record
Abstract
BACKGROUND: The use of antiarrhythmic drugs (AADs) in patients with chronic kidney disease (CKD) is complex because impaired renal clearance can cause increased drug levels, and risk of intolerance or adverse events. Due to the propensity for CKD to occur alongside atrial fibrillation/atrial flutter (AF/AFL), it is essential that AAD safety and efficacy are assessed for patients with CKD. HYPOTHESIS: Dronedarone, an approved AAD, may present a suitable therapeutic option for patients with AF/AFL and concomitant CKD. METHODS: EURIDIS-ADONIS (EURIDIS, NCT00259428; ADONIS, NCT00259376) were identically designed, multicenter, double-blind, parallel-group trials investigating AF/AFL control with dronedarone 400 mg twice daily versus placebo (randomized 2:1). In this post hoc analysis, the primary endpoint was time to first AF/AFL. Patients were stratified according to renal function using the CKD-Epidemiology Collaboration equation and divided into estimated glomerular filtration rate (eGFR) subgroups of 30-44, 45-59, 60-89, and ≥90 ml/min. Time-to-events between treatment groups were compared using log-rank testing and Cox regression. RESULTS: At baseline, most (86%) patients demonstrated a mild or mild-to-moderate eGFR decrease. Median time to first AF/AFL recurrence was significantly longer with dronedarone versus placebo for all eGFR subgroups except the 30 to 44 ml/min group, where the trend was similar but statistical power may have been limited by the small population. eGFR stratification had no significant effect on serious adverse events, deaths, or treatment discontinuations. CONCLUSIONS: This analysis suggests that dronedarone could be an effective therapeutic option for AF with an acceptable safety profile in patients with impaired renal function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".