Background In recent years, the incidence and prevalence of metabolic-associated fatty liver disease (MAFLD) have increased annually, and more than 25% of the global population suffers from MAFLD. Type 2 diabetes mellitus (T2DM) is closely related to MAFLD, but simple and accurate predictors of MAFLD in T2DM patients are scant.
Objective To investigate the correlation between albumin/gamma-glutamyl transferase ratio (AGTR) with T2DM combined with MAFLD, and to construct a nomogram to predict the risk of T2DM combined with MAFLD.
Methods A total of 1 050 adult patients with T2DM who were hospitalized in the Department of Endocrinology, Hebei General Hospital from 2018 to 2023 were enrolled. After several rounds of rigorous screening, a total of 723 eligible patients were included in the study, involving 430 cases in the T2DM combined with MAFLD group and 293 cases of T2DM without MAFLD. The basic information of patients were collected and analyzed, MAFLD was diagnosed by ultrasound. Spearman correlation analysis was used to analyze the correlation between AGTR and T2DM combined with MAFLD risk factors. Multivariate Logistic regression analysis was used to explore the risk factors for T2DM complicated with MAFLD. An individualized nomogram for predicting the risk of T2DM complicated with MAFLD was constructed and validated.
Results Compared with the T2DM without MAFLD group, the levels of BMI, alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), bile acids (BA), fasting blood glucose (FBG), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol (VLDL-C), apolipoprotein B (ApoB), uric acid (UA) in the T2DM combined with MAFLD group were significantly higher, while age, duration of T2DM, albumin (ALB), and high-density lipoprotein cholesterol (HDL-C) were significantly lower (P<0.05). Patients were divided into T1-T3 groups according to the AGTR tertiles. The general data of the three groups were compared. BMI, ALT, GGT, FBG, TC, TG, LDL-C, VLDL-C, ApoB, and UA were significantly lower than those of T1 and T2 groups, while HDL-C and AST were significantly lower than T1 groups (P<0.05). Age and course of T2DM in T3 group were significantly higher than those of T1 and T2 groups (P<0.05). BMI, ALT, AST, GGT, TG, VLDL-C, and UA in T2 group were significantly lower than those of T1 groups (P<0.05). Spearman correlation analysis showed that AGTR was positively correlated with age, course of T2DM, ALB, and HDL-C (P<0.05), and negatively correlated with VLDL-C, BMI, ALT, AST, GGT, BA, FBG, TC, TG, LDL-C, ApoB, and UA (P<0.05). Multivariate Logistic regression analysis showed that the increased BMI (OR=1.256, 95%CI=1.187-1.330), increased TG (OR=1.272, 95%CI=1.043-1.551), and the decreased AGTR (OR=0.707, 95%CI=0.562-0.890) were the influencing factors for the risk of T2DM combined with MAFLD (P<0.05). Receiver operating characteristic (ROC) curve analysis showed that the nomogram involving BMI, TG and AGTR effectively predict the risk of MAFLD in T2DM patients, with the area under the curve (AUC) of 0.827 (95%CI=0.790-0.864). The calibration curve showed that the predicted value was close to the ideal curve, indicating a good consistency. The clinical decision curve showed that the nomogram had good clinical prediction effect on T2DM combined with MAFLD.
Conclusion AGTR increase is a protective factor for T2DM combined with MAFLD. The individualized nomogram constructed based on BMI, TG, and AGTR can effectively predict the risk of T2DM combined with MAFLD.