肝纤维化无创评估指标的预测价值及模型的建立  

Establishment of non-invasive evaluation indices of hepatic fibrosis through a predictive model

作　　者：郑朋超 王学梅[1] 许东阳[1] 桑亮[1] ZHENG Pengchao;WANG Xuemei;XU Dongyang;SANG Liang(Department of Ultrasound,The First Hospital of China Medical University,Shenyang 110001,China)

机构地区：[1]中国医科大学附属第一医院超声科,沈阳110001

出　　处：《中国医科大学学报》2021年第3期220-223,229,共5页Journal of China Medical University

基　　金：辽宁省自然科学基金(20170541039)。

摘　　要：目的探讨在肝纤维化诊断中的无创评估指标,建立预测肝纤维化程度的无创模型。方法筛选2015年1月至2019年7月于我院行肝脏组织穿刺活检且具备完整临床检查和实验室检查指标的患者113例。根据肝脏组织穿刺活检病理结果将肝纤维化程度分为S0~S4期,比较各分期间无创评估指标的差异,通过logistic回归分析,筛选出能预测肝纤维化的相关指标,并建立预测肝纤维化程度的模型。结果单因素分析结果显示,随着肝纤维化分期的增加,血红蛋白、谷丙转氨酶、谷草转氨酶、γ-谷氨酰转移酶(γ-GGT)、实时剪切波弹性成像杨氏模量呈上升趋势,而血小板(PLT)值呈下降趋势;有序多因素方差分析结果显示,PLT、γ-GGT、杨氏模量在预测肝纤维化程度中有统计学意义(P<0.05),建立的回归模型为Logit P=2.329-0.012×PLT+0.018×γ-GGT+0.128×杨氏模量。结论血清学指标和SWE杨氏模量在评估肝纤维化程度中具有重要临床意义,应用杨氏模量、PLT、γ-GGT构建的模型可预测肝纤维化程度。Objective To investigate non-invasive indices in evaluating hepatic fibrosis and to establish a non-invasive model for predicting the degree of hepatic fibrosis.Methods A total of 113 patients,who underwent hepatic biopsy in our hospital and had complete clinical examinations between January 2015 and July 2019,were screened and divided into S0-S4 stages according to the degree of hepatic fibrosis.The relevant non-invasive indices were screened to establish a predictive model of hepatic fibrosis after comparing the differences of the non-invasive indices in each stage through logistic regression analysis.Results Univariate analysis showed an upward trend of serum hemoglobin,alanine aminotransferase,aspartate aminotransferase,andγ-glutamyltransferase(γ-GGT)levels,increased Young’s modulus obtained from shear wave elastography,and a downward trend of platelet(PLT)levels with the aggravation of hepatic fibrosis.Logistic regression analysis revealed significant differences in serum PLT,γ-GGT,and Young’s modulus in judging the severity of hepatic fibrosis(P<0.05).The regression model was established as Logit P=2.329-0.012×PLT+0.018×γ-GGT+0.128×Young’s modulus.Conclusion Serological indices and Young’s modulus may have important significance for the diagnosis of hepatic fibrosis.The severity of hepatic fibrosis can be predicted by using the model consisting of the Young’s modulus,PLT,andγ-GGT levels.

关 键 词：肝纤维化 无创 预测 模型 

分 类 号：R445.1[医药卫生—影像医学与核医学]