Risk prediction models for hepatic encephalopathy post-transjugular intrahepatic portosystemic shunt: A systematic...

Transjugular intrahepatic portosystemic shunt (TIPS) is an established treatment for portal hypertension (PH), with expanding indications. Hepatic encephalopathy (HE) is the main complication, affecting up to 50% of patients. Accurate prediction of HE risk is necessary for patient selection. Hence, we aimed to provide an overview of prediction models for post-TIPS HE.

We conducted a systematic review of studies developing or validating prediction models for post-TIPS HE that included ≥100 patients. The search, conducted up to December 2025, covered databases including Embase and MEDLINE. Outcomes assessed included AUCs/C-indices and risk of bias, evaluated using PROBAST.

Twenty-seven studies were included, of which 24 developed prediction models. All used retrospective cohorts of patients with cirrhosis (population size: 106-621), with 25 cohorts from Asia (93%). Models varied in HE severity and prediction time frame, with 11 studies (41%) not reporting any. Discrimination varied across studies. The Child-Pugh and MELD scores, evaluated in nine studies, showed moderate performance (AUCs/C-indices: 0.60-0.75). Models that included imaging predictors (42%) reported higher discrimination than clinical models alone (0.73-0.97 vs. 0.61-0.86). Common clinical predictors were age (68%), Child-Pugh score (40%), and creatinine (28%). Models had a high risk of bias in PROBAST assessment (96%). Methodological concerns included inappropriate patient exclusion (63%), low events-per-variable ratio (81%), inadequate validation (79%), and neglect of competing risks (93%). Applicability concerns involved the use of highly selected populations (44%) and specialized imaging predictors (33%).

Current prediction models for post-TIPS HE, despite sometimes demonstrating strong discrimination, cannot reliably support clinical decision-making because of methodological and applicability concerns. Future research should prioritize models with accessible predictors, broad patient representation, appropriate consideration of competing risks, and rigorous validation to minimize overfitting.

Despite numerous studies, there remains no consensus on whether prediction models for post-TIPS hepatic encephalopathy can be integrated into clinical practice. This paper provides a comprehensive overview of existing models by highlighting their strengths and limitations. In addition, it identifies recurrent predictors across models and proposes a framework for future research aimed at improving the prediction of this challenging complication.