Mineralocorticoid receptor antagonists for heart failure: systematic review and meta-analysis
Bibliographic record
Abstract
Mineralocorticoid receptor antagonists (MRAs) have been associated with improved patient outcomes in patients with heart failure with reduced ejection fraction (HFrEF) but not preserved ejection fraction (HFpEF). We conducted a systematic review and meta-analysis of selective and nonselective MRAs in HFrEF and HFpEF. We searched Cochrane Central Register of Controlled Trials, MEDLINE and EMBASE. We included randomized controlled trials (RCT) of MRAs in adults with HFpEF or HFrEF if they reported data on major adverse cardiac events or drug safety. We identified 15 studies representing 16321 patients. MRAs were associated with a reduced risk of cardiovascular death (RR 0.81 [0.75–0.87], I 2 0%), all-cause mortality (RR 0.83 [0.77–0.88], I 2 0%), and cardiac hospitalizations (RR 0.80 [0.70–0.92], I 2 58.4%). However, an a-priori specified subgroup analysis demonstrated that these benefits were limited to HFrEF (cardiovascular death RR 0.79 [0.73–0.86], I 2 0%; all-cause mortality RR 0.81 [0.75–0.87], I 2 0%; cardiac hospitalizations RR 0.76 [0.64–0.90], I 2 68%), but not HFpEF (all-cause mortality RR 0.92 [0.79–1.08], I 2 0%; cardiac hospitalizations RR 0.91 [0.67–1.24], I 2 17%). MRAs increased the risk of hyperkalemia (RR 2.03 [1.78–2.31], I 2 0%). Nonselective MRAs, but not selective MRAs increased the risk of gynecomastia (RR 7.37 [4.42–12.30], I 2 0% vs. RR 0.74 [0.43–1.27], I 2 0%). Evidence was of moderate quality for cardiovascular death, all-cause mortality and cardiovascular hospitalizations; and high-quality for hyperkalemia and gynecomastia. MRAs reduce the risk of adverse cardiac events in HFrEF but not HFpEF. MRA use in HFpEF increases the risk of harm from hyperkalemia and gynecomastia. Selective MRAs are equally effective as nonselective MRAs, without a risk of gynecomastia.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.022 | 0.035 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".