Predicting death or recurrence of portal hypertension symptoms after TIPS procedures

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

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.

Machine Learning Insights: Predicting Hepatic Encephalopathy After TIPS Placement

PURPOSE

To develop and assess machine learning (ML) models' ability to predict post-procedural hepatic encephalopathy (HE) following transjugular intrahepatic portosystemic shunt (TIPS) placement.

MATERIALS AND METHODS

In this retrospective study, 327 patients who underwent TIPS for hepatic cirrhosis between 2005 and 2019 were analyzed. Thirty features (8 clinical, 10 laboratory, 12 procedural) were collected, and HE development regardless of severity was recorded one month follow-up. Univariate statistical analysis was performed with numeric and categoric data, as appropriate. Feature selection is used with a sequential feature selection model with fivefold cross-validation (CV). Three ML models were developed using support vector machine (SVM), logistic regression (LR) and CatBoost, algorithms. Performances were evaluated with nested fivefold-CV technique.

RESULTS

Post-procedural HE was observed in 105 (32%) patients. Patients with variceal bleeding (p = 0.008) and high post-porto-systemic pressure gradient (p = 0.004) had a significantly increased likelihood of developing HE. Also, patients having only one indication of bleeding or ascites were significantly unlikely to develop HE as well as Budd-Chiari disease (p = 0.03). The feature selection algorithm selected 7 features. Accuracy ratios for the SVM, LR and CatBoost, models were 74%, 75%, and 73%, with area under the curve (AUC) values of 0.82, 0.83, and 0.83, respectively.

CONCLUSION

ML models can aid identifying patients at risk of developing HE after TIPS placement, providing an additional tool for patient selection and management.

Transjugular Intrahepatic Portosystemic Shunt: Devices Evolution, Technical Tips and Future Perspectives

Portal hypertension (PH) constitutes a pivotal factor in the progression of cirrhosis, giving rise to severe complications and a diminished survival rate. The transjugular intrahepatic portosystemic shunt (TIPS) procedure has undergone significant evolution, with advancements in stent technology assuming a central role in managing PH-related complications. This review aims to outline the progression of TIPS and emphasizes the significant influence of stent advancement on its effectiveness. Initially, the use of bare metal stents (BMSs) was limited due to frequent dysfunction. However, the advent of expanding polytetrafluoroethylene-covered stent grafts (ePTFE-SGs) heralded a transformative era, greatly enhancing patency rates. Further innovation culminated in the creation of ePTFE-SGs with controlled expansion, enabling precise adjustment of TIPS diameters. Comparative analyses demonstrated the superiority of ePTFE-SGs over BMSs, resulting in improved patency, fewer complications, and higher survival rates. Additional technical findings highlight the importance of central stent placement and adequate stent length, as well as the use of smaller calibers to reduce the risk of shunt-related complications. However, improving TIPS through technical means alone is inadequate for optimizing patient outcomes. An extensive understanding of hemodynamic, cardiac, and systemic factors is required to predict outcomes and tailor a personalized approach. Looking forward, the ongoing progress in SG technology, paired with the control of clinical factors that can impact outcomes, holds the promise of reshaping the management of PH-related complications in cirrhosis.

The role of transjugular intrahepatic portosystemic shunt in patients with cirrhosis and ascites: Recent evolution and open questions

In selected patients with cirrhosis and ascites, transjugular intrahepatic portosystemic shunt (TIPS) placement improves control of ascites and may reduce mortality. In this review, we summarize the current knowledge concerning the use of TIPS for the treatment of ascites in patients with cirrhosis, from pathophysiology of ascites formation to hemodynamic consequences, patient selection, and technical issues of TIPS insertion. The combination of these factors is important to guide clinical decision-making and identify the best strategy for each individual patient. There is still a need to identify the best timing for TIPS placement in the natural history of ascites (recurrent vs. refractory) as well as which type and level of renal dysfunction is acceptable when TIPS is proposed for the treatment of ascites in cirrhosis. Future studies are needed to define the optimal stent diameter according to patient characteristics and individual risk of shunt-related side effects, particularly hepatic encephalopathy and insufficient cardiac response to hemodynamic consequences of TIPS insertion.

Serological indices and ultrasound variables in predicting the staging of hepatitis B liver fibrosis: A comparative study based on random forest algorithm and traditional methods

Objective

To compare the diagnostic efficacy of serological indices and ultrasound (US) variables in hepatitis B virus (HBV) liver fibrosis staging using random forest algorithm (RFA) and traditional methods.

Methods

The demographic and serological indices and US variables of patients with HBV liver fibrosis were retrospectively collected and divided into serology group, US group, and serology + US group according to the research content. RFA was used for training and validation. The diagnostic efficacy was compared to logistic regression analysis (LRA) and APRI and FIB-4 indices.

Results

For the serology group, the diagnostic performance of RFA was significantly higher than that of APRI and FIB-4 indices. The diagnostic accuracy of RFA in the four classifications (S0S1/S2/S3/S4) of the hepatic fibrosis stage was 79.17%. The diagnostic accuracy for significant fibrosis (≥S2), advanced fibrosis (≥S3), and cirrhosis (S4) was 87.99%, 90.69%, and 92.40%, respectively. The area under the curve (AUC) values were 0.945, 0.959, and 0.951, respectively. For the US group, there was no significant difference in diagnostic performance between RFA and LRA. The diagnostic performance of RFA in the serology + US group was significantly better than that of LRA. The diagnostic accuracy of the four classifications (S0S1/S2/S3/S4) of the hepatic fibrosis stage was 77.21%. The diagnostic accuracy for significant fibrosis (≥S2), advanced fibrosis (≥S3), and cirrhosis (S4) was 87.50%, 90.93%, and 93.38%, respectively. The AUC values were 0.948, 0.959, and 0.962, respectively.

Conclusion

RFA can significantly improve the diagnostic performance of HBV liver fibrosis staging. RFA based on serological indices has a good ability to predict liver fibrosis staging. RFA can help clinicians accurately judge liver fibrosis staging and reduce unnecessary biopsies.

Progress in Endoscopic and Interventional Treatment of Esophagogastric Variceal Bleeding

Esophagogastric variceal bleeding (EGVB) is one of the main complications of portal hypertension, especially in patients with liver cirrhosis, and has a very high fatality rate. At present, the treatment methods for rupture and bleeding of gastroesophageal varices (GV) include drug therapy, compression hemostasis with three-lumen and two-balloon tube, endoscopic therapy, and interventional and surgical operations. Endoscopy and intervention or their combined application is the mainstream treatment modes in clinical practice, especially their combined application has been increasingly recognized by front-line clinicians. This article intends to discuss the application characteristics of the two treatment methods.