A Retrospective Analysis of Glucagon-Like Peptide 1 Receptor Agonists in Treating Type 2 Diabetes Mellitus Complicated by Nonalcoholic Fatty Liver Disease

Abstract

Background: The objective of this study was to compare and analyze the variations in clinical indices before and after treatment of type 2 mellitus (T2DM) combined with nonalcoholic fatty liver disease (NAFLD) that were treated with glucagon-like peptide 1 receptor agonists (GLP-1RAs). Methods: The electronic medical record system was utilized to search for a total of 16 patients with type 2 diabetes complicated by NAFLD who were hospitalized at the First Affiliated Hospital of Yangtze University from October 2022 to April 2023 and treated with GLP-1RA for the first time. The clinical indices were compared before and after 12 weeks of treatment with GLP-1RA. Results: The liver-spleen CT ratio (L/S), alanine aminotransferase (ALT), gamma-glutamyltransferase (GGT), total cholesterol (TC), triglyceride (TG), and lowdensity lipoprotein cholesterol (LDL-C) in all patients treated with GLP-1RA after 12 weeks were significantly different (P < 0.05). Aspartate aminotransferase (AST) and high-density lipoprotein cholesterol (HDL-C) levels did not change significantly compared to the levels before treatment (P > 0.05). The patients were categorized into two groups based on the types of GLP-1RAs. The changes in L/S, TC, TG, and LDL-C in the long-acting group after treatment were statistically significant (P < 0.05), as were the changes in L/S, TC, and TG in the ultra-long-acting group after treatment (P < 0.05). LDL-C levels after treatment with ultra-long-acting GLP-1RA showed a difference at the 0.05 significance level from LDL-C levels after treatment with long-acting GLP-1RA. No statistically significant differences were observed in the levels of L/S, ALT, AST, GGT, TC, TG, and HDL-C. Conclusions: GLP-1RAs can improve liver function, regulate lipid metabolism, and reduce the severity of fatty liver in patients with T2DM complicated by NAFLD, which demon-How to cite this paper: Chen, J.Q. and Wu, H.Y.