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Advances in Factors and Risk Prediction of Hepatic Encephalopathy After Transjugular Intrahepatic Portosystemic Shunt

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ABSTRACT Hepatic encephalopathy (HE) is a frequent complication that occurs following transjugular intrahepatic portosystemic shunt (TIPS) procedures and has a considerable effect on patient prognosis. HE development is associated with various factors, including the type of liver cirrhosis, laboratory indicators, patient medical history, and choice of shunt channel and stent during the procedure. In recent years, several risk prediction models have been extensively used to predict the occurrence of HE after TIPS. These models offer clinicians valuable insights, thereby assisting in the creation of effective preventive strategies and personalized treatment plans. This review summarizes the main factors that influence the development of HE after TIPS. Furthermore, it emphasizes the advancements in studies related to risk prediction models with the objective of providing clinical insights that can facilitate improvements in patient outcomes and optimize treatment strategies.
Title: Advances in Factors and Risk Prediction of Hepatic Encephalopathy After Transjugular Intrahepatic Portosystemic Shunt
Description:
ABSTRACT Hepatic encephalopathy (HE) is a frequent complication that occurs following transjugular intrahepatic portosystemic shunt (TIPS) procedures and has a considerable effect on patient prognosis.
HE development is associated with various factors, including the type of liver cirrhosis, laboratory indicators, patient medical history, and choice of shunt channel and stent during the procedure.
In recent years, several risk prediction models have been extensively used to predict the occurrence of HE after TIPS.
These models offer clinicians valuable insights, thereby assisting in the creation of effective preventive strategies and personalized treatment plans.
This review summarizes the main factors that influence the development of HE after TIPS.
Furthermore, it emphasizes the advancements in studies related to risk prediction models with the objective of providing clinical insights that can facilitate improvements in patient outcomes and optimize treatment strategies.

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