影响慢性乙型肝炎患者进展为肝硬化的多因素分析  

Multivariate analysis of liver fibrosis progress in patients with chronic hepatitis B

作　　者：汤磊[1] 彭蕾[1] 叶珺[1] 张振华[1] 邹桂舟[1] Tang Lei;Peng Lei;Ye Jun(Department of Infectious Diseases,Second Affiliated Hospital,Anhui Medical University,Hefei 230601,Anhui Province,China)

机构地区：[1]安徽医科大学第二附属医院感染病科,合肥市230601

出　　处：《实用肝脏病杂志》2022年第4期538-541,共4页Journal of Practical Hepatology

基　　金：2021年安徽省重大疑难疾病中西医协同攻关项目。

摘　　要：目的探讨影响慢性乙型肝炎(CHB)患者发生肝硬化的因素。方法2010~2016年我科住院的CHB患者135例,均接受肝活检,并随访5(7,11)年。随访结束时,临床诊断肝硬化。应用Logistic回归分析并建立预测模型,应用受试者工作特征(ROC)曲线下面积(AUC)评估诊断效能。结果入组时肝组织学检查显示,非肝纤维化组81例,显著纤维化组54例;随访结束时,临床诊断非肝硬化组111例,肝硬化组24例(来自无纤维化组7例,来自显著肝纤维化组17例);非肝硬化组与肝硬化组年龄、是否抗病毒治疗、血清HBV DNA、血小板计数(PLT)、血浆凝血酶原时间国际标准化比值(INR)、部分活化的凝血活酶时间(APTT)和红细胞分布宽度(RDW)差异具有统计学意义(均P<0.05);多因素回归分析显示INR(P=0.010,OR=369.352)、APTT(P=0.001,OR=1.169)、RDW(P=0.035,OR=1.402)、PLT(P=0.018,OR=0.989)、年龄(P=0.024,OR=1.052)、血小板与淋巴细胞比值(P/L比值,P=0.044,OR=0.983)和抗病毒与否(P=0.000,OR=7.600)为肝硬化发生的独立危险因素,由此建立预测模型为Logit(P)=-17.407+0.528×INR+0.161×APTT+0.079×年龄+2.401×抗病毒与否(否=0,是=1)。该综合模型预测肝硬化发生的AUC为0.872,其敏感度为91.7%,特异度为75.7%。结论研究CHB患者发生肝硬化的影响因素,有助于早期阻断病情发展,而年龄和抗病毒治疗可能是重要的影响因素。Objective The aim of this study was to explore the factors impacting liver fibrosis progress in patients with chronic hepatitis B(CHB).Methods A total of 135 patients with CHB were encountered in our Department of Infectious Diseases,Second Affiliated Hospital,Anhui Medical University,between 2010 and 2016,and all patients underwent liver biopsy,and followed-up for 5(7,11)years.The multivariate Logistic regression analysis was carried out,the prediction model was established and the area under the receiver operating characteristic(ROC)curve(AUC)was calculated to evaluate the diagnostic performance of the model.Results At the presentation,the histopatholotical examination showed non-fibrosis in 81 cases and significant liver fibrosis in 54 cases in our series;at the end of follow-up,we found non-cirrhosis in 111 cases and liver cirrhosis in 24 cases(from non-fibrosis in 7 cases and from significant fibrosis in 17 cases)based on clinical diagnosis;there were significant differences respect to age,antiviral treatment,serum HBV DNA loads,platelet counts(PLT),plasma prothrombin time international normalized ratio(INR),activated partial thromboplastin time(APTT)and erythrocyte distribution width(RDW)between patients with non-cirrhosis and cirrhosis(all P<0.05);the Logistic regression analysis showed that INR(P=0.010,OR=369.352),APTT(P=0.001,OR=1.169),RDW(P=0.035,OR=1.402),PLT(P=0.018,OR=0.989),age(P=0.024,OR=1.052),platelet to lymphocyte ratio(P/L,P=0.044,OR=0.983)and antiviral or not(P=0.000,OR=7.600)were the independent risk factors for liver cirrhosis;thereby,we established a prediction model as follows:Logit(P)=-17.407+0.528×INR+0.161×APTT+0.079×Age+2.401×Antiviral or not(no=0,yes=1);the AUC of the model in predicting liver cirrhosis was 0.872,with the sensitivity of 91.7%and the specificity of 75.7%.Conclusion The age and antiviral therapy could be the important factors impacting liver cirrhosis occurrence,and early intervention might prevent the disease progression.

关 键 词：肝硬化 慢性乙型肝炎 无创预测模型 诊断 

分 类 号：R512.62[医药卫生—内科学] R575.2[医药卫生—临床医学]