Value of atherogenic index of plasma in predicting metabolic associated fatty liver disease in patients with type 2 diabetes mellitus / 临床肝胆病杂志

ABSTRACT

Objective To investigate the association between atherogenic index of plasma (AIP) and metabolic associated fatty liver (MAFLD) in type 2 diabetes mellitus (T2DM). Methods A total of 375 patients with T2DM who were hospitalized and treated in Department of Endocrinology, The First Affiliated Hospital of Zhengzhou University, from September 2021 to September 2022 were enrolled, and according to the presence or absence of MAFLD, they were divided into T2DM+MAFLD group with 245 patients and T2DM group with 130 patients. Related clinical data were recorded, and AIP was calculated. According to the quartiles of AIP, the patients were divided into Q1 group (AIP≤0.20), Q2 group (0.20 0.48). The independent-samples t test was used for comparison of normally distributed continuous data between groups, and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous data between groups; the trend chi-square test was used for the trend analysis of categorical data. The multivariate logistic regression analysis was used to investigate the effect of AIP on MAFLD, and the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) were used to assess the value of the indicators such as AIP, body mass index (BMI), and alanine aminotransferase (ALT) in predicting T2DM with MAFLD. Results Compared with the T2DM group, the T2DM+MAFLD group had significant increases in BMI, systolic pressure, uric acid, fasting blood glucose, glycosylated hemoglobin, ALT, aspartate aminotransferase, gamma-glutamyl transpeptidase, alkaline phosphatase, triglyceride, low-density lipoprotein, and AIP and a significant reduction in high-density lipoprotein (all P < 0.05). The trend chi-square test showed that the prevalence rate of MAFLD in T2DM patients tended to increase with the increase in AIP level ( χ trend 2 =20.338, P < 0.05). The multivariate logistic regression analysis showed that compared with the Q1 group, the Q4 group had a significant increase in the risk of MAFLD (odds ratio =2.396, 95% confidence interval 1.018-5.640, P =0.045). The ROC curve analysis showed that the diagnostic model of AIP combined with BMI and ALT had the best diagnostic performance (AUC=0.816), with a sensitivity of 70.2% and a specificity of 78.5% at the optimal cut-off value of 0.670. Conclusion AIP is an independent risk factor for MAFLD in T2DM patients, and AIP combined with BMI and ALT has a good predictive value for T2DM with MAFLD.