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TIPS术治疗的肝硬化并发EVB患者医院内死亡风险预测模型的构建与应用*
引用本文:徐超,李兰,罗东,赵海云,彭飞.TIPS术治疗的肝硬化并发EVB患者医院内死亡风险预测模型的构建与应用*[J].实用肝脏病杂志,2022,25(6):840-843.
作者姓名:徐超  李兰  罗东  赵海云  彭飞
作者单位:635000 四川省达州市中西医结合医院急诊内科(徐超,罗东,赵海云,彭飞);四川大学华西医院中西医结合科(李兰)
基金项目:*四川省卫生与健康委员会科研项目(编号:H171626)
摘    要:目的 构建肝硬化门静脉高压症并发食管胃底静脉曲张破裂出血(EVB)患者医院内死亡的风险预测模型。方法 2018年6月~2020年6月我院收治的107例肝硬化门静脉高压症并发EVB患者,均接受经颈静脉肝内门体静脉分流术(TIPS)治疗。应用Logistic回归分析影响患者死亡的危险因素,基于独立影响因素构建医院内死亡的风险预测模型,应用Bootstrap法对预测模型进行内部验证,应用受试者工作特征曲线(ROC)下面积(AUC)评估预测模型的预测效能。结果 本组患者医院内死亡25例(23.4%),生存82例;单因素分析显示,死亡患者Child-Pugh分级、出血部位、门静脉内径、肝性脑病和失血性休克发生率等与生存患者比,均存在显著性差异(P<0.05),多因素Logistic回归分析显示,门静脉内径(OR=2.201,95%CI:1.544~3.139)、肝性脑病(OR=3.093,95%CI:1.731~5.524)和失血性休克(OR=1.101,95%CI:1.040~1.165)是影响患者医院内死亡的独立危险因素(P<0.05);对所构建的列线图预测模型,经内部验证,其C-index为0.937(95%CI:0.734~0.879),具有良好的区分度;应用ROC曲线分析显示,预测模型的曲线下面积(AUC)为0.896(95%CI:0.796~0.958,P<0.001),其预测的敏感度和特异度分别为91.3%和88.1%。结论 了解影响肝硬化门静脉高压症并发EVB患者医院内死亡的独立危险因素,并据此构建的风险预测列线图模型具有良好的区分度和预测效能,有助于临床对高风险患者的筛查和及时处理。

关 键 词:肝硬化  食管胃底静脉曲张破裂出血  经颈静脉肝内门体静脉分流术  院内死亡  列线图预测模型  
收稿时间:2021-11-12

Construction and application of risk prediction model for nosocomial death in cirrhotics with esophagogastric variceal bleeding after TIPS treatment
Xu Chao,Li Lan,Luo Dong,et al..Construction and application of risk prediction model for nosocomial death in cirrhotics with esophagogastric variceal bleeding after TIPS treatment[J].Journal of Clinical Hepatology,2022,25(6):840-843.
Authors:Xu Chao  Li Lan  Luo Dong  
Institution:Department of Emergent Internal Medicine, Integrated Traditional Chinese and Western Medicine Hospital, Dazhou 635000, Sichuan Province, China
Abstract:Objective The aim of this study was to construct a risk prediction model for nosocomial death in cirrhotics with portal hypertension and esophagogastric variceal bleeding (EVB). Methods A retrospective cohort study was conducted on the clinical data of 107 patients with cirrhotic portal hypertension and EVB who were admitted to our hospital between June 2018 and June 2020. All patients received transjugular intrahepatic portosystemic shunt (TIPS) therapy. The Logistic regression analysis was performed to screenindependent risk factors influencing the prognosis of patients with cirrhotic portal hypertension and EVB. A risk prediction model for nosocomial death was constructed based on these independent factors, and its predictive efficacy was verified by the area under receiver operating characteristic curve (AUC). Results 25 patients (23.4%) died and 82 patients survived in our series; the univariate Logistic regression analysis showed that Child class, portal vein diameter, the sites of bleeding, the incidence rates of hepatic encephalopathy and hemorrhagic shock in died patients were significantly different compared to in survivals (P<0.05), and the multivariate Logistic regression analysis demonstrated that the portal vein diameter (OR=2.201, 95%CI: 1.544-3.139), hepatic encephalopathy (OR=3.093, 95%CI: 1.731-5.524) and hemorrhagic shock (OR=1.101, 95%CI: 1.040-1.165) were the independent risk factors for nosocomial death (P<0.05); the C-index of the constructed nomogram model we built up by internal verification for predicting nosocomial death of patients with cirrhotic portal hypertension and EVB was 0.937 (95%CI: 0.734-0.879), witha good discrimination, and the AUC was 0.896 (95%CI: 0.796-0.958, P<0.001), with the sensitivity and specificity of the prediction model were 91.3% and 88.1%, respectively. Conclusion The early recognition of risk factors of nosocomial death in patients with cirrhotic portal hypertension and EVB is important for appropriate management of patients, and the risk prediction model we constructed might have a good predictive efficacy.
Keywords:Cirrhosis  Esophagogastric variceal bleeding  Transjugular intrahepatic portosystemic shunt  Nosocomial death  Nomogram prediction model  
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