Mineralocorticoid Receptor Antagonists and Cardiovascular Mortality in Patients With Atrial Fibrillation and Left Ventricular Dysfunction
Bibliographic record
Abstract
BACKGROUND: Patients with heart failure (HF) and atrial fibrillation (AF) may differ from the larger HF population with respect to comorbidities, including renal impairment and overall prognosis. Associated cardiorenal interactions may mitigate the effects of pharmacological agents. Our primary objective was to assess the impact of mineralocorticoid receptor antagonists on cardiovascular mortality in patients with AF and HF enrolled in the Atrial Fibrillation and Congestive Heart Failure (AF-CHF) trial. METHODS AND RESULTS: All 1376 patients randomized in the AF-CHF trial were included. The median baseline creatinine was 105.2 (Q1 88.4, Q3 125.0) μmol/L, and the median estimated glomerular filtration rate was 62.3 (Q1 49.0, Q3 77.2) mL/min per 1.73 m(2). The renal function was moderately or severely impaired (ie, estimated glomerular filtration rate <60 mL/min per 1.73 m(2)) in 46.5% of patients. In multivariable analyses, increased creatinine was associated with worsening HF but not mortality. Mineralocorticoid receptor antagonists were prescribed in 44.8% and were independently associated with a 1.4-fold increase in total mortality (hazard ratio, 1.4; 95% CI [1.1-1.8]; P=0.005) and a 1.4-fold increase in cardiovascular mortality (hazard ratio, 1.4; 95% CI [1.1-1.9]; P=0.009). This was driven by an increased incidence of sudden cardiac death (hazard ratio, 2.0; 95% CI [1.3, 3.0]; P=0.001). CONCLUSIONS: Renal dysfunction was highly prevalent in patients with AF and HF. Mineralocorticoid receptor antagonists were independently associated with an increased incidence of cardiovascular deaths, predominantly of presumed arrhythmic cause. Although these provocative findings merit prospective validation, they underscore the importance of careful monitoring of renal function and electrolytes in patients with AF and HF receiving mineralocorticoid receptor antagonists.
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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) | 0.000 | 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".