基于超声肝纹理指数与临床参数构建代谢相关脂肪性肝病发生重度肝脂肪变性的预测模型  

Prediction model for severe hepatic steatosis in metabolic-associated fatty liver disease based on ultrasound liver texture index and clinical parameters

作　　者：朱林锋 林涛 胡萍 金清[1] 陈泉 ZHU Lin-feng;LIN Tao;HU Ping;JIN Qing;CHEN Quan(Department of Ultrasound,Kunshan Traditional Chinese Medicine Hospital,Kunshan 215300,Jiangsu,CHINA;Department of Endocrinology,Kunshan Traditional Chinese Medicine Hospital,Kunshan 215300,Jiangsu,CHINA)

机构地区：[1]昆山市中医医院超声科,江苏昆山215300 [2]昆山市中医医院内分泌科,江苏昆山215300

出　　处：《海南医学》2025年第7期1014-1018,共5页Hainan Medical Journal

基　　金：江苏省苏州市科技发展计划指导性项目(编号:SKYXD2022070)。

摘　　要：目的探讨基于超声肝纹理指数(LTI)及临床参数构建的列线图模型对代谢相关脂肪性肝病(MAFLD)发生重度肝脂肪变性的预测价值。方法回顾性分析2023年2~12月昆山市中医院收治的118例MAFLD患者的临床资料,将56例发生重度肝脂肪变性的患者纳入研究组,62例未发生重度肝脂肪变性的患者纳入对照组。比较两组患者的LTI值及临床参数。采用多因素Logistic回归筛选MAFLD发生重度肝脂肪变性的危险因素并构建列线图模型,采用受试者工作特征(ROC)曲线、校准曲线、决策曲线(DCA)评估模型对MAFLD发生重度肝脂肪变性的预测效能。结果研究组患者的体质量指数(BMI)、LTI值、尿酸(UA)、甘油三酯(TG)、谷丙转氨酶(ALT)、谷草转氨酶(AST)、空腹胰岛素(FINS)水平分别为(26.95±2.54)kg/m^(2)、2.54(2.48,2.87)、367.20(312.57,420.57)μmol、2.00(1.40,3.29)mmol/L、28.40(21.70,41.02)U/L、24.60(20.75,30.50)U/L、12.80(9.66,18.20)m U/L,明显高于对照组的(24.99±2.95)kg/m^(2)、2.40(2.33,2.49)、311.55(267.53,377.35)μmol、1.58(0.98,2.24)mmol/L、21.55(16.70,28.68)U/L、22.65(18.33,28.10)U/L、8.69(5.77,10.95)m U/L,差异均有统计学意义(P<0.05)。多因素Logistic回归分析结果显示,LTI、BMI、TG均是MAFLD发生重度肝脂肪变性的独立危险因素(P<0.05)。基于上述危险因素构建预测MAFLD发生重度肝脂肪变性的列线图模型,ROC曲线显示模型的AUC为0.893(95%CI:0.838~0.948);校准曲线及DCA曲线显示该模型具有较好的校准度和临床应用价值。结论基于LTI定量检测技术及临床参数构建的列线图模型对代谢相关脂肪性肝病发生重度肝脂肪变性具有良好的预测价值,有助于临床对此类患者早期干预并治疗。Objective To explore the predictive value of a nomogram model based on the ultrasound Liver Texture Index(LTI)and clinical parameters for severe hepatic steatosis in patients with Metabolic-Associated Fatty Liver Disease(MAFLD).Methods A retrospective analysis was conducted on the clinical data of 118 MAFLD patients admitted to Kunshan Traditional Chinese Medicine Hospital from February to December 2023.Among them,56 patients with severe hepatic steatosis were included in the study group,while 62 patients without severe hepatic steatosis were included in the control group.The LTI values and clinical parameters of the two groups were compared.Multivariate logistic regression was used to identify risk factors for severe hepatic steatosis in MAFLD and to construct a nomogram model.The predictive performance of the model was evaluated using Receiver Operating Characteristic(ROC)curves,calibration curves,and Decision Curve Analysis(DCA).Results The study group had significantly higher levels of body mass index(BMI),LTI,uric acid(UA),triglycerides(TG),alanine aminotransferase(ALT),aspartate aminotransferase(AST),and fasting insulin(FINS)compared to the control group(P<0.05):(26.95±2.54)kg/m^(2),2.54(2.48,2.87),367.20(312.57,420.57)μmol,2.00(1.40,3.29)mmol/L,28.40(21.70,41.02)U/L,24.60(20.75,30.50)U/L,12.80(9.66,18.20)mU/L vs(24.99±2.95)kg/m^(2),2.40(2.33,2.49),311.55(267.53,377.35)μmol,1.58(0.98,2.24)mmol/L,21.55(16.70,28.68)U/L,22.65(18.33,28.10)U/L,8.69(5.77,10.95)mU/L.Multivariate logistic regression analysis showed that LTI,BMI,and TG were independent risk factors for severe hepatic steatosis in MAFLD(P<0.05).A nomogram model was constructed based on these risk factors,and the ROC curve showed an area under the curve(AUC)of 0.893(95%CI:0.838-0.948).The calibration curve and DCA indicated that the model had good calibration and clinical application value.Conclusion The nomogram model based on LTI quantitative detection technology and clinical parameters has good predictive value for severe hepatic steatosis in M

关 键 词：代谢相关脂肪性肝病 肝纹理指数 肝脂肪变性 临床参数 列线图 

分 类 号：R575.5[医药卫生—消化系统]