{Reference Type}: Multicenter Study
{Title}: A modified model for predicting mortality after transjugular intrahepatic portosystemic shunt: A multicentre study.
{Author}: Zhao Y;Yang Y;Lv W;Zhu S;Chen X;Wang T;Huang M;An T;Duan C;Yu X;Li Q;Chen J;Luo J;Zhou S;Lu L;Huang M;Fu S;
{Journal}: Liver Int
{Volume}: 44
{Issue}: 2
{Year}: 2024 Feb 27
{Factor}: 8.754
{DOI}: 10.1111/liv.15790
{Abstract}: <B>OBJECTIVE: </B>The transjugular intrahepatic portosystemic shunt has controversial survival benefits; thus, patient screening should be performed preoperatively. In this study, we aimed to develop a model to predict post-transjugular intrahepatic portosystemic shunt mortality to aid clinical decision making.<BR><B>METHODS: </B>A total of 811 patients undergoing transjugular intrahepatic portosystemic shunt from five hospitals were divided into the training and external validation data sets. A modified prediction model of post-transjugular intrahepatic portosystemic shunt mortality (ModelMT ) was built after performing logistic regression. To verify the improved performance of ModelMT , we compared it with seven previous models, both in discrimination and calibration. Furthermore, patients were stratified into low-, medium-, high- and extremely high-risk subgroups.<BR><B>RESULTS: </B>ModelMT demonstrated a satisfying predictive efficiency in both discrimination and calibration, with an area under the curve of .875 in the training set and .852 in the validation set. Compared to previous models (ALBI, BILI-PLT, MELD-Na, MOTS, FIPS, MELD, CLIF-C AD), ModelMT showed superior performance in discrimination by statistical difference in the Delong test, net reclassification improvement and integrated discrimination improvement (all p < .050). Similar results were observed in calibration. Low-, medium-, high- and extremely high-risk groups were defined by scores of ≤160, 160-180, 180-200 and >200, respectively. To facilitate future clinical application, we also built an applet for ModelMT .<BR><B>CONCLUSIONS: </B>We successfully developed a predictive model with improved performance to assist in decision making for transjugular intrahepatic portosystemic shunt according to survival benefits.