Bayesian network-based survival prediction model for patients having undergone post-transjugular intrahepatic portosystemic shunt for portal hypertension

作     者：Rong Chen Ling Luo Yun-Zhi Zhang Zhen Liu An-Lin Liu Yi-Wen Zhang 

作者机构：Department of Infectious DiseasesSecond Affiliated Hospital of Chongqing Medical UniversityChongqing 400016China 

出 版 物：《World Journal of Gastroenterology》 (世界胃肠病学杂志（英文版）)

年 卷 期：2024年第30卷第13期

页      面：1859-1870页

核心收录：

学科分类：1002[医学-临床医学] 100210[医学-外科学(含：普外、骨外、泌尿外、胸心外、神外、整形、烧伤、野战外)] 10[医学] 

基　　金：Supported by the Chinese Nursing Association,No.ZHKY202111 Scientific Research Program of School of Nursing,Chongqing Medical University,No.20230307 Chongqing Science and Health Joint Medical Research Program,No.2024MSXM063 

主　　题：Bayesian network Cirrhosis Portal hypertension Transjugular intrahepatic portosystemic shunt Survival prediction model 

摘      要：BACKGROUND Portal hypertension(PHT),primarily induced by cirrhosis,manifests severe symptoms impacting patient *** transjugular intrahepatic portosystemic shunt(TIPS)is a critical intervention for managing PHT,it carries risks like hepatic encephalopathy,thus affecting patient survival *** our knowledge,existing prognostic models for post-TIPS survival in patients with PHT fail to account for the interplay among and collective impact of various prognostic factors on ***,the development of an innovative modeling approach is essential to address this *** To develop and validate a Bayesian network(BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone *** The clinical data of 393 patients with cirrhosis-induced PHT who underwent TIPS surgery at the Second Affiliated Hospital of Chongqing Medical University between January 2015 and May 2022 were retrospectively *** were selected using Cox and least absolute shrinkage and selection operator regression methods,and a BN-based model was established and evaluated to predict survival in patients having undergone TIPS surgery for *** Variable selection revealed the following as key factors impacting survival:age,ascites,hypertension,indications for TIPS,postoperative portal vein pressure(post-PVP),aspartate aminotransferase,alkaline phosphatase,total bilirubin,prealbumin,the Child-Pugh grade,and the model for end-stage liver disease(MELD)*** on the above-mentioned variables,a BN-based 2-year survival prognostic prediction model was constructed,which identified the following factors to be directly linked to the survival time:age,ascites,indications for TIPS,concurrent hypertension,post-PVP,the Child-Pugh grade,and the MELD *** Bayesian information criterion was 3589.04,and 10-fold cross-validation indicated an average log-likelihood loss of 5.55 with a standard deviation of *** model’s acc