Analysis of influencing factors of non-alcoholic fatty liver disease and construction of nomogram predictive model
Objective To explore the influencing factors of non-alcoholic fatty liver disease(NAFLD),and to establish nomogram prediction model.Methods Retrospective analysis was carried out on the data of people who underwent routine health check-ups at health check-up centre of a hospital in Lanzhou from January to December 2021.These people were di-vided into NAFLD group(243 cases)and non-NAFLD group(372 cases)according to diagnostic criteria.Independent risk factors for NAFLD were screened by single-factor and multi-factor logistic regression analysis,and the nomogram prediction model was constructed by combining independent risk factors.The discrimination of the model was evaluated by the receiver operating characteristic(ROC)curve,the area under the curve(AUC)and C-index,and the calibration of the model was evaluated by Hosmer-Lemeshow test and calibration graph.Results Univariate analysis showed that there were statistically significant differences in gender,overweight,obesity,smoking,and ethnicity between the NAFLD group and the non-NAFLD group(P＜0.05).White blood cells(WBC),albumin(ALB),γ-gamma-glutamyltransferase(GGT),creatinine(CREA),uric acid(UA),triglycerides(TG),total cholesterol(CHOL)and glucose(GLU),alanine aminotransferase(ALT)of the NAFLD group were higher than those of the non-NAFLD group,while globulin(GLB)and high-density lipo-protein(HDL)levels were lower in the non-NAFLD group,and the differences were statistically significant(P＜0.05).Multivariate logistic regression analysis showed that overweight,obesity,UA,CHOL,GLU,and ALT were independent risk factors for NAFLD,while HDL was an independent protective factor,and the differences were statistically significant(all P＜0.05).The discrimination results of the ROC curve evaluation model showed that AUC was 0.85(95％CI:0.819-0.880),sensitivity was 79.40％,specificity was 79.60％,and the C-index of the model was 0.855.The results of calibra-tion curve evaluation model effectiveness showed that:x2=12.850,P=0.117.Conclusion Overweight,obesity,UA,CHOL,GLU and ALT are risk factors for NAFLD.The established nomogram predictive model has good discrimination and validity,and can be used as a tool for personalized assessment of NAFLD by both doctors and patients.
万方数据
维普
