Mineralocorticoid Receptor Antagonist Pattern of Use in Heart Failure with Reduced Ejection Fraction: Findings from BIOSTAT-CHF
Bibliographic record
Abstract
Abstract Aims Mineralocorticoid receptor antagonists (MRAs) are recommended (unless contraindicated) to all patients with heart failure with reduced ejection fraction (HFrEF). However, MRAs are still largely underused in routine clinical practice. This study aims to describe the determinants and pattern of use of MRAs in HFrEF. Methods and results BIOSTAT-CHF is a European multicentre, prospective study which enrolled patients suboptimally treated with angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEi/ARBs) and/or beta-blockers, with the aim of optimizing guideline-based use of these agents. From the original 2516 subjects, this retrospective post hoc analysis included the 1325 patients with an indication for MRA therapy (i.e. left ventricular ejection fraction ≤35%, estimated glomerular filtration rate ≥30 mL/min/1.73 m2, K+ ≤5.0 mmol/L). The mean age was 66.1 ± 12.2 years. At baseline an MRA was prescribed to 741 (56%) patients. Patients who were prescribed MRAs at baseline were younger, more often male, had higher body mass index, lower sodium, higher proportion of hypertension history and ACEi/ARB prescription (all P < 0.05). Of the 1049 patients who completed the baseline plus the 9 month visit, 585 (56%) had an MRA prescribed at baseline and 662 (63%) had an MRA prescribed at 9 months. Among the 585 patients with MRA at baseline, 91 (16%) had discontinued therapy and among the 461 (44%) patients without MRA at baseline 168 (36%) had initiated therapy subsequently. MRA discontinuation was more likely in subjects with higher left ventricular ejection fraction and NYHA class III/IV (P < 0.05 for both). MRA prescription both at baseline and 9 months was not associated with the outcome of death or heart failure hospitalization (adjusted hazard ratio 1.02, 95% confidence interval 0.66–1.58; P = 0.93). Conclusions In this prospective observational study across Europe, MRAs were largely under-prescribed and frequently discontinued. Owing to these dynamic changes, outcome inferences are inconclusive.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".