An individual patient-based meta-analysis of the effects of dronedarone in patients with atrial fibrillation
Bibliographic record
Abstract
AIMS: Dronedarone is a non-iodinated benzofuran derivative with antiarrhythmic properties. In placebo-controlled atrial fibrillation (AF) trials, the drug was found to have divergent effects on endpoints such as cardiovascular death or hospitalization. The objective of this meta-analysis of all placebo-controlled studies was to provide insights on possible reasons for these divergent effects. METHODS AND RESULTS: Individual data on 9664 patients were used from all AF placebo-controlled studies. The primary outcome measure was cardiovascular death. Cardiovascular hospitalization and hospitalization for heart failure were secondary endpoints. Predefined procedures were used to reduce inter-study heterogeneity adjusting for important baseline variables using a Cox model. Despite adjustments, a significant inter-trial heterogeneity of the outcome of cardiovascular mortality persisted (P-value of 0.005 for the treatment effect × study interaction). Further analyses were conducted in subgroups based on baseline clinical criteria: digoxin co-prescription, advanced heart failure, coronary artery disease, or the presence of permanent AF. These analyses allowed the calculation of a global treatment effect in two important patient subgroups, those with permanent AF in whom there was harm with respect to cardiovascular mortality [hazard ratio (HR) = 2.32; 95% confidence interval (CI) 1.13-4.75] and hospitalization for heart failure (HR = 1.674; 95% CI 1.05-2.67); and those with non-permanent AF in whom there was benefit in terms of cardiovascular hospitalization [HR = 0.751 95% CI (0.68-0.83)]. CONCLUSION: This meta-analysis demonstrates significant heterogeneity of dronedarone treatment effects across the placebo-controlled randomized trials. The most important predictor of a harmful effect of dronedarone on cardiovascular death and heart failure hospitalization was the presence of permanent AF.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| 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".