The influence of metabolic health and obesity on the risk of liver fibrosis progression in metabolic associated fatty liver disease

Liu Yunxiao; Niu Lina; Wang Zhuanguo; Yu Hong; Sun Wei; Guo Yan; Guo Feng; Wang Xiaozhong

doi:10.3760/j.issn.1673-4777.2024.03.017

Abstract：Objective To investigate the effects of metabolic health and obesity on the risk associated with liver fibrosis in metabolic associated fatty liver disease(MAFLD).Methods From January 2020 to December 2022,347 patients diagnosed with MAFLD in the Traditional Chinese Medical Hospital Affiliated to Xinjiang Medical University were enrolled.Patients were classified into the metabolic healthy non-obese group(77 cases),the metabolic unhealthy non-obese group(65 cases),the metabolic healthy obese group(91 cases)and the meta-bolic unhealthy obese group(114 cases),according to whether they had metabolic health or their body mass index(BMI)was≥28 kg/m2.The differences in clinical data,non-invasive liver fibrosis indicators and the degree of liver fibrosis were compared among the four groups.Univariable and multivariable Logistic regression analyses were performed to evaluate the risk factors for significant liver fibrosis in MAFLD.The Logistic regression model would be evaluated by the receiver operating characteristic(ROC)curve analysis in order to predict the progressive liver fibrosis in MAFLD.Results When non-obese or obese,the proportion of moderate to severe liver fibrosis(≥ F2 stage)and progressive liver fibrosis in patients with unhealthy metabolism were significantly higher than those in metabolically healthy people.Multivariable analysis showed that body mass index,alanine aminotransferase(ALT),controlled attenuation parameter(CAP)and aspartate transaminase to platelet count ratio index(APRI)were independent risk factors for liver fibrosis in MAFLD(all P＜0.05).The above risk factors were included in Logistic regression analysis.The regression analysis model was as follows:logit(P)=-11.67+BMI x 0.20+ALT x0.02+CAP x 0.01+APRI x 2.73.The ROC curve for predicting advanced liver fibrosis occurrence in MAFLD was drawn by predictive probabilities logit(P).When logit(P)＞0.478,the area under the curve was 0.782,the diagnostic sensitivity was 63.3％,and the specificity was 84.5％.Conclusion Body mass index,ALT,CAP,and APRI are risk factors for progressive liver fibrosis in MAFLD patients,indicating that reducing body mass,protecting liver and lowering enzymes,and controlling metabolic factors are beneficial for delaying the development of liver fibrosis in MAFLD patients.