GLP-1 Receptor Agonists in Heart Failure: A Systematic Review and Meta-analysis with Phenotype-Specific Effects and Dual Analytical Frameworks
- Journal
- Drugs (Q1)
- Published
- 26 September 2026
- Study design
- Systematic review / meta-analysis of RCTs
- Evidence level
- Level 1, High (CEBM 1a)
- Authors
- Yahui Yuan, Chun Chen, Xiuming Li, Jingyi Guo, Qiaoyun Liu, YuPing Lin, et al.
- PMID
- 42791433
- DOI
- 10.1007/s40265-026-02380-4
Why clinicians should know about it
- Picked for Pharmacology (medical) (top studies of the week, 27 September 2026).
- Picked for Cardiology and Cardiovascular Medicine (top studies of the week, 27 September 2026): GLP‑1 RAs meta‑analysis shows HF phenotype effects
Abstract
BACKGROUND: Although glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce cardiovascular risk in patients with type 2 diabetes mellitus (T2D), evidence in heart failure (HF) has expanded across diverse trial populations and HF phenotypes but remains fragmented. We therefore performed an integrated systematic review and meta-analysis to evaluate the effects of GLP-1 RAs across the spectrum of HF using complementary trial-level and phenotype-based analyses. METHODS: PubMed, Embase, and Web of Science were systematically searched for studies published from inception to August 10, 2025. To provide an integrated assessment across heterogeneous HF populations, treatment effects were evaluated using dual analytical frameworks: trial-level analyses according to study design (dedicated HF with preserved ejection fraction [HFpEF] trials, HF with reduced ejection fraction [HFrEF] trials, and HF subgroups from cardiovascular outcome trials [CVOTs]) and phenotype-based analyses according to left ventricular ejection fraction (HFpEF vs HFrEF using a pragmatic threshold of 40%). A prespecified targeted analysis was conducted to specifically assess the efficacy of semaglutide. The primary outcomes were major adverse cardiovascular events (MACE), and the secondary outcomes included hospitalization for HF (HHF), the composite of cardiovascular death or any worsening HF events, cardiovascular death alone, and all-cause mortality. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using random‑effects models. RESULTS: This meta-analysis included 14 trials, with a pooled total of 15,882 patients with HF. In phenotype‑based analyses for HFpEF, GLP‑1 RAs significantly reduced MACE (HR 0.79; 95% CI 0.66-0.94; p = 0.010), HHF (HR 0.48; 95% CI 0.27-0.85; p = 0.012), the composite of cardiovascular death or worsening HF (HR 0.57; 95% CI 0.37-0.89; p = 0.013), and all‑cause mortality (HR 0.75; 95% CI 0.62-0.89; p = 0.001). In contrast, in HFrEF, no significant reductions were observed for HHF, the composite of cardiovascular death or worsening HF, all-cause mortality, or MACE, although a reduction in cardiovascular death was noted (HR 0.71; 95% CI 0.54-0.95; p = 0.019). Trial-level analyses showed that cardiovascular benefits were primarily observed in HF subgroups from CVOTs, including reductions in MACE (HR 0.82; 95% CI 0.73-0.92; p = 0.001), cardiovascular death (HR 0.88; 95% CI 0.77-1.00; p = 0.05) and myocardial infarction (MI)/non-fatal MI (HR 0.84; 95% CI 0.70-1.00; p = 0.046). Semaglutide showed benefits in HHF and the composite of cardiovascular death or worsening HF events predominantly among overweight or obese patients with HFpEF. GLP-1 RAs also improved functional capacity and quality of life in HFpEF. CONCLUSION: GLP-1 RAs were associated with favorable cardiovascular and HF-related outcomes in HFpEF, predominantly among overweight or obese individuals, whereas evidence of benefit in HFrEF remains limited. In trial-level analyses, benefits were primarily observed for atherosclerotic endpoints in HF subgroups from CVOTs. By integrating evidence, this study provides a unified overview of the effects of GLP-1 RAs across the spectrum of HF and supports further phenotype-specific randomized trials, particularly dedicated studies in HFrEF. TRIAL REGISTRATION: Protocol registration PROSPERO (CRD420251079970).
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.