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 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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.051 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".