Risk factor analysis and predictive model construction of lean MAFLD: a cross-sectional study of a health check-up population in China

作者：Ruya Zhu, Caicai Xu, Suwen Jiang, Jianping Xia, Bo-Ming Wu, Sijia Zhang, Jing Zhou, Hongliang Liu, Hongshan Li, Jianjun Lou · 发表于：European journal of medical research · 年份：2025 · DOI：10.1186/s40001-025-02373-1 · 被引用次数：10 · 研究领域：Liver Disease Diagnosis and Treatment、Diabetes, Cardiovascular Risks, and Lipoproteins、Nutrition and Health in Aging

AIM: Cardiovascular disease morbidity and mortality rates are high in patients with metabolic dysfunction-associated fatty liver disease (MAFLD). The objective of this study was to analyze the risk factors and differences between lean MAFLD and overweight MAFLD, and establish and validate a nomogram model for predicting lean MAFLD. METHODS: (n = 2104) and subjects with lean MAFLD (n = 849). The study population was randomly split (7:3 ratio) to a training vs. a validation cohort. Risk factors for lean MAFLD was identify by multivariate regression of the training cohort, and used to construct a nomogram to estimate the probability of lean MAFLD. Model performance was examined using the receiver operating characteristic (ROC) curve analysis and k-fold cross-validation (k = 5). Decision curve analysis (DCA) was applied to evaluate the clinical usefulness of the prediction model. RESULTS: The multivariate regression analysis indicated that the triglycerides and glucose index (TyG) was the most significant risk factor for lean MAFLD (OR: 4.03, 95% CI 2.806-5.786). The restricted cubic spline curves (RCS) regression model demonstrated that the relationships between systolic pressure (SBP), alanine aminotransferase (ALT), serum urate (UA), total cholesterol (TCHO), triglyceride (TG), triglyceride glucose (TyG) index, high density lipoprotein cholesterol (HDLC), and MAFLD were nonlinear and the cutoff values for lean MAFLD and overweight MAFLD were different. The nomogram was constru...