Pharmacologic Treatment of Heart Failure With Reduced Ejection Fraction
Bibliographic record
Abstract
BACKGROUND: In 2022, a network meta-analysis showed that a combination of β-blockers, angiotensin receptor-neprilysin inhibitors (ARNi), mineralocorticoid receptor antagonists (MRAs), and sodium-glucose cotransporter 2 inhibitors (SGLT2i) was most effective in reducing all-cause mortality in heart failure with reduced ejection fraction (HFrEF). This study updates the treatment benefit by including additional large randomized controlled trials (RCTs) since 2022, including the VICTOR (Vericiguat Global Study in Participants with Chronic Heart Failure) trial. OBJECTIVES: The goal of this study was to evaluate and compare regimens of pharmacotherapy in patients with HFrEF. METHODS: MEDLINE, Embase, and Cochrane Central Register of Controlled Trials databases were searched for RCTs in patients with HFrEF through April 2025. Using frequentist network meta-analysis, HRs for all-cause mortality (primary outcome), cardiovascular death, and the composite of cardiovascular death or heart failure hospitalization (secondary outcomes) were estimated. Absolute benefits were quantified as life-years gained by using BIOSTAT-CHF (Biology Study to Tailored Treatment in Chronic Heart Failure) and ASIAN-HF (Asian Sudden Cardiac Death in Heart Failure) cohort data. RESULTS: The analysis included 103,754 patients across 89 randomized controlled trials. Relative to placebo, quintuple therapy with ARNi, β-blockers, MRAs, SGLT2i, and vericiguat most effectively reduced all-cause mortality (HR: 0.35; 95% CI: 0.27-0.45), followed by quadruple therapy with ARNi, β-blockers, MRAs, and SGLT2i (HR: 0.39; 95% CI: 0.32-0.49). For a representative 70-year-old patient, quadruple therapy (ARNi/β-blockers/MRAs/SGLT2i) provided 5.3 additional life-years (95% CI: 2.8-7.7) vs no treatment, while quintuple therapy (ARNi/β-blockers/MRA/SGLT2i/vericiguat) provided 6.0 additional life-years (95% CI: 3.7-8.4). CONCLUSIONS: This analysis reinforces the substantial mortality and morbidity benefit associated with the currently recommended quadruple therapy regimen (ARNi, β-blockers, MRAs, and SGLT2i) in patients with HFrEF. The addition of vericiguat may provide an incremental survival gain of approximately 0.7 year beyond that achieved with quadruple therapy. However, these results should be regarded as exploratory, as they are derived from a secondary endpoint of a single trial.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".