摘要
目的 本研究旨在探讨影响慢加急性肝衰竭(ACLF)患者90天死亡的独立预测因子,并构建风险预测模型,评估其与终末期肝病模型(MELD)、MELD-Na、MELD 3.0和中国重症乙型肝炎研究小组慢加急性肝衰竭2.0(COSSH-ACLFⅡ)评分的预测效能差异。方法 回顾性分析2018年7月—2024年7月内蒙古医科大学附属医院和呼和浩特市第二医院收治的394例ACLF患者临床资料。收集患者一般资料及入院时实验室指标,定量资料两组间比较采用成组t检验或MannWhitney U检验,定性资料两组间比较采用χ^(2)检验或校正χ^(2)检验。采用LASSO回归筛选变量,多因素Logistic回归构建预测模型并绘制列线图。通过受试者操作特征曲线(ROC曲线)及曲线下面积(AUC)、校准曲线和临床决策曲线评估模型性能。结果 本研究共纳入394例ACLF患者,其中训练集和内部验证集分别为136例和58例,外部验证集200例。全队列年龄(52.9±11.7)岁,男性占72.84%(287/394),HBV感染者占22.33%(88/394),酒精相关占45.94%(181/394),其他原因(包括药物性、自身免疫性等)占31.73%(125/394)。90天总体病死率为27.41%(108/394)。多因素Logistic回归显示,糖尿病[比值比(OR)=5.831, 95%置信区间(CI):1.587~21.424, P=0.008]、胱抑素-C(Cys-C)(OR=2.984, 95%CI:1.501~5.933, P=0.002)和自发性细菌性腹膜炎(SBP)(OR=5.692, 95%CI:2.150~15.071, P<0.001)均为独立危险因素,并以此绘制列线图。模型在训练集、内部验证集和外部验证集的AUC分别为0.836、0.881、0.878,显示出良好的区分度。校准曲线拟合良好,并有较高的临床净获益。按病因进行亚组分析显示,模型在HBV感染、酒精及其他病因所致ACLF患者中的AUC分别为0.850、0.858和0.908,表明该模型在不同病因人群中均具有良好的区分能力。与传统评分相比,该模型(AUC=0.836)显著优于单独使用MELD(AUC=0.619,Z=3.197,P=0.001)、MELD-Na(AUC=0.651,Z=2.998,P=0.003)、MELD 3.0(AUC=0.601, Z=3.682,P<0.001)和COSSH-ACLFⅡ(AUC=0.719, Z=2.396,P=0.017)评分的预测价值。结论 糖尿病、SBP和Cys-C是ACLF患者90天死亡的独立危险因素。与MELD、MELD-Na、MELD 3.0和COSSH-ACLFⅡ评分相比,该模型对ACLF患者90天预后具有更高的预测价值,且适用于多种病因所致的ACLF患者。
Objective To investigate the independent predictive factors for 90-day mortality in patients with acute-on-chronic liver failure(ACLF),to establish a risk predictive model,and to assess its predictive efficacy in comparison with MELD,MELD-Na,MELD 3.0,and COSSH-ACLFⅡ.Methods A retrospective analysis was performed for the clinical data of 394 patients with ACLF who were admitted to The Affiliated Hospital of Inner Mongolia Medical University and Hohhot Second Hospital from July 2018 to July 2024,and general information and laboratory markers on admission were collected from all patients.The independentsamples t test or the Mann-Whitney U test was used for comparison of quantitative data between two groups,and the chi-square test or the adjusted chi-square test was used for comparison of qualitative data between two groups.The LASSO regression analysis was used to identify related variables,and the multivariate logistic regression analysis was used to establish a predictive model and generate a nomogram.The receiver operating characteristic(ROC)curve,the area under the ROC curve(AUC),calibration curve,and clinical decision curve were used to assess the performance of the model.Results A total of 394 patients with ACLF were included in this study,with 136 patients in the training set,58 in the internal validation set,and 200 in the external validation set.The cohort had a mean age of 52.9±11.7 years,among whom male patients accounted for 72.84%(287/394),the patients with HBV infection accounted for 22.33%(88/394),the patients with alcohol-related causes accounted for 45.94%(181/394),and the patients with other causes(including drug-induced and autoimmune diseases)accounted for 31.73%(125/394).The overall 90-day mortality rate was 27.41%(108/394).The multivariate logistic regression analysis showed that diabetes(odds ratio[OR]=5.831,95%confidence interval[CI]:1.587—21.424,P=0.008),cystatin C(Cys-C)(OR=2.984,95%CI:1.501—5.933,P=0.002),and spontaneous peritonitis(SBP)(OR=5.692,95%CI:2.150—15.071,P<0.001)were independent risk factors,and a nomogram was generated based on these factors.This model had an AUC of 0.836 in the training set,0.881 in the internal validation set,and 0.878 in the external validation set,showing a good discriminatory ability.The calibration curve showed a good degree of fitting,with a relatively high net clinical benefit.The subgroup analysis based on etiology showed that the model had an AUC of 0.850 in the patients with HBV infection,0.858 in the patients with alcohol-induced ACLF,and 0.908 in the patients with other etiologies,indicating that the model had a good discriminatory ability across the populations with different etiologies.Compared with traditional scores,the model(AUC=0.836)had a significantly better predictive value than MELD(AUC=0.619,Z=3.197,P=0.001),MELD-Na(AUC=0.651,Z=2.998,P=0.003),MELD 3.0(AUC=0.601,Z=3.682,P<0.001),and COSSH-ACLFⅡ(AUC=0.719,Z=2.396,P=0.017)alone.Conclusion Diabetes,SBP,and Cys-C are independent risk factors for 90-day mortality in patients with ACLF.Compared with MELD,MELD-Na,MELD 3.0,and COSSH-ACLFⅡscores,this model has a higher predictive value for 90-day prognosis in patients with ACLF and is suitable for patients with ACLF caused by various etiologies.
作者
孙静
王婷济
段志娇
张丽
李艳梅
SUN Jing;WANG Tingji;DUAN Zhijiao;ZHANG Li;LI Yanmei(The First Clinical Medical College of Inner Mongolia Medical University,Hohhot 010059,China;Department of Gastroenterology,The Affiliated Hospital of Mongolia Medical College,Hohhot 010050,China;Department of Critical Care Medicine,Hohhot Second Hospital,Hohhot 010050,China)
出处
《临床肝胆病杂志》
北大核心
2026年第1期151-159,共9页
Journal of Clinical Hepatology
基金
内蒙古自治区自然科学基金(2025ZD009)
内蒙古自治区自然科学基金(2023QN08061)
内蒙古医科大学青年基金(YKD2023QN014)
2022年“草原英才”工程高层次培养人才项目。
