Mineralocorticoid receptor antagonists and atrial fibrillation: a meta-analysis of clinical trials
Bibliographic record
Abstract
BACKGROUND AND AIMS: Mineralocorticoid receptor antagonists (MRAs) improve cardiovascular outcomes in a variety of settings. This study aimed to assess whether cardioprotective effects of MRAs are modified by heart failure (HF) and atrial fibrillation (AF) status and to study their impact on AF events. METHODS: MEDLINE, Embase, and Cochrane Central databases were searched to 24 March 2023 for randomized controlled trials evaluating the efficacy of MRAs as compared with placebo or usual care in reducing cardiovascular outcomes and AF events in patients with or at risk for cardiovascular diseases. Random-effects models and interaction analyses were used to test for effect modification. RESULTS: Meta-analysis of seven trials (20 741 participants, mean age: 65.6 years, 32% women) showed that the efficacy of MRAs, as compared with placebo, in reducing a composite of cardiovascular death or HF hospitalization remains consistent across patients with HF [risk ratio = 0.81; 95% confidence interval (CI): 0.67-0.98] and without HF (risk ratio = 0.84; 95% CI: 0.75-0.93; interaction P = .77). Among patients with HF, MRAs reduced cardiovascular death or HF hospitalization in patients with AF (hazard ratio = 0.95; 95% CI: 0.54-1.66) to a similar extent as in those without AF (hazard ratio = 0.82; 95% CI: 0.63-1.07; interaction P = .65). Pooled data from 20 trials (21 791 participants, mean age: 65.2 years, 31.3% women) showed that MRAs reduce AF events (risk ratio = 0.76; 95% CI: 0.67-0.87) in both patients with and without prior AF. CONCLUSIONS: Mineralocorticoid receptor antagonists are similarly effective in preventing cardiovascular events in patients with and without HF and most likely retain their efficacy regardless of AF status. Mineralocorticoid receptor antagonists may also be moderately effective in preventing incident or recurrent AF events.
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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 | 0.022 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.053 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".