Effect of Hypoglycemic Drugs on Patients with Heart Failure with or without T2DM: A Bayesian Network Meta-analysis.

Abstract

Background: Anti-diabetic drugs have been noted to have a cardioprotective effect in patients with diabetes and heart failure (HF). The purpose of this study was to perform a Bayesian network meta-analysis to evaluate the impact of various anti-diabetic drugs on the prognosis of HF patients with and without diabetes.

Methods: We searched PubMed, Embase, Cochrane, and Web of Science for randomized controlled trials (RCTs) published before November 2024 that investigated the use of anti-diabetic medications in patients with HF. Primary outcomes included re-admission due to HF, all-cause death, cardiovascular death, serum N-terminal pro-brain natriuretic peptide (NTpro-BNP) levels, and left ventricular ejection fraction (LVEF). A Bayesian network meta-analysis was used to compare the effectiveness of different anti-diabetic drugs.

Results: A total of 33 RCTs involving 29,888 patients were included. Sotagliflozin was the most effective in reducing the risk of re-admission due to HF and all-cause death, with a cumulative probability of 0.84 and 0.83, respectively. Liraglutide reduced the risk of cardiovascular death in HF patients with a cumulative probability of 0.97 and had the best efficacy in reducing NTpro-BNP levels with a cumulative probability of 0.69. Empagliflozin was best in improving LVEF in HF patients, with a cumulative probability of 0.69.

Conclusions: This Bayesian network meta-analysis demonstrates that sotagliflozin may be the best option for HF patients with and without diabetes. However, due to the small number of articles in this study, our results must be treated cautiously. Subsequently, there is an urgent need for more high-quality studies to validate our findings.