Bayesian network-based survival prediction model for patients having undergone post-transjugular intrahepatic portosystemic shunt for portal hypertension
作者全名:Chen, Rong; Luo, Ling; Zhang, Yun-Zhi; Liu, Zhen; Liu, An-Lin; Zhang, Yi-Wen
作者地址:[Chen, Rong; Luo, Ling; Zhang, Yun-Zhi; Liu, Zhen; Liu, An-Lin; Zhang, Yi-Wen] Chongqing Med Univ, Affiliated Hosp 2, Dept Infect Dis, 288 Tianwen Ave, Chongqing 400016, Peoples R China
通信作者:Luo, L (通讯作者),Chongqing Med Univ, Affiliated Hosp 2, Dept Infect Dis, 288 Tianwen Ave, Chongqing 400016, Peoples R China.
来源:WORLD JOURNAL OF GASTROENTEROLOGY
ESI学科分类:CLINICAL MEDICINE
WOS号:WOS:001208044900008
JCR分区:Q1
影响因子:4.3
年份:2024
卷号:30
期号:13
开始页:
结束页:
文献类型:Article
关键词: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 survival. Although transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for managing PHT, it carries risks like hepatic encephalopathy, thus affecting patient survival prognosis. To 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 outcomes. Consequently, the development of an innovative modeling approach is essential to address this limitation. AIM To develop and validate a Bayesian network (BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone TIPS. METHODS 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 analyzed. Variables 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 PHT. RESULTS 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) score. Based 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 score. The 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 0.16. The model's accuracy, precision, recall, and F1 score were 0.90, 0.92, 0.97, and 0.95 respectively, with the area under the receiver operating characteristic curve being 0.72. CONCLUSION This study successfully developed a BN-based survival prediction model with good predictive capabilities. It offers valuable insights for treatment strategies and prognostic evaluations in patients having undergone TIPS surgery for PHT.
基金机构:Chinese Nursing Association [ZHKY202111]; Scientific Research Program of School of Nursing, Chongqing Medical University [20230307]; Chongqing Science and Health Joint Medical Research Program [2024MSXM063]
基金资助正文:Supported by the Chinese Nursing Association, No. ZHKY202111; Scientific Research Program of School of Nursing, Chongqing Medical University, No. 20230307; and Chongqing Science and Health Joint Medical Research Program, No. 2024MSXM063