Prevalence and risk factor analysis for the nonalcoholic fatty liver disease in patients with type 2 diabetes mellitus. Issue 10 (12th March 2021)

• Record Type: Journal Article
• Authors: Zhou, Qiumei; Wang, Yulong; Wang, Jiajia; Liu, Yating; Qi, Dehui; Yao, Wei; Jiang, Hui; Li, Tingting; Huang, Kaiquan; Zhang, Wancun; Huo, Xingxing
• Other Names: Yan. Liang-Jun section editor.
• Is Part Of: Medicine. Volume 100:Issue 10(2021)
• Publication Date: 2021-03-12
• Subjects: metabolism -- non-alcoholic fatty liver disease -- obesity -- routine examination -- screening -- type-2 diabetes mellitus; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000024940
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Although non-alcoholic fatty liver disease (NAFLD) is strongly associated with type 2 diabetes mellitus (T2DM), the diagnosis of NAFLD for T2DM patients remains a challenge. This study aimed to investigate the prevalence and risk factors for the NAFLD in T2DM outpatients. This is a retrospective, cross-sectional study that included 2405 T2DM patients treated and admitted for glucose control into the Endocrinology Department of our hospital from April 2017 to March 2019. Using strict exclusion criteria, the target patients were screened and divided into two groups: NAFLD patients (study group) and non-NAFLD patients (control group). Subsequently, 34 factors were compared between the two groups. Furthermore, multivariate analysis of the NAFLD risk factors was performed using logistic regression. Finally, the diagnostic significance of individual biochemical predictors, as well as the combined predictive indicator (CPI), for NAFLD was estimated using receiver operating characteristic (ROC) curve analysis. In this study, the overall prevalence of NAFLD in T2DM patients was 58.67%. Of the target patients, 17 factors were identified by univariate analysis to be associated with NAFLD, and 8 factors were found to be significant predictors for NAFLD using binary logistic regression modeling. Furthermore, the CPI and C-Peptide represent high diagnostic value for NAFLD in T2DM patients. This study provides a more comprehensive risk factor analysis for NAFLD in T2DM patients. These data can be used to provide timely diagnosis and effective management of NAFLD.