Evaluation of G3BP1 in the Prognosis of Acute and Acute-on-chronic Liver Failure After the Treatment of Artificial Liver Support System

Overview

Journal World J Hepatol

Publisher Baishideng Publishing Group

Specialty Gastroenterology

Date 2024 Mar 18

PMID 38495274

Authors

Wen-Yuan Li

Lu-Wen Wang

Jin Dong

Yao Wang

Affiliations

Soon will be listed here.

Abstract

Background: The increased expression of G3BP1 was positively correlated with the prognosis of liver failure.

Aim: To investigate the effect of G3BP1 on the prognosis of acute liver failure (ALF) and acute-on-chronic liver failure (ACLF) after the treatment of artificial liver support system (ALSS).

Methods: A total of 244 patients with ALF and ACLF were enrolled in this study. The levels of G3BP1 on admission and at discharge were detected. The validation set of 514 patients was collected to verify the predicted effect of G3BP1 and the viability of prognosis.

Results: This study was shown that lactate dehydrogenase (LDH), alpha-fetoprotein (AFP) and prothrombin time were closely related to the prognosis of patients. After the ALSS treatment, the patient' amount of decreased G3BP1 index in difference of G3BP1 between the value of discharge and admission (difG3BP1) < 0 group had a nearly 10-fold increased risk of progression compared with the amount of increased G3BP1 index. The subgroup analysis showed that the difG3BP1 < 0 group had a higher risk of progression, regardless of model for end-stage liver disease high-risk or low-risk group. At the same time, compared with the inflammatory marks [tumor necrosis factor-α, interleukin (IL)-1β and IL-18], G3BP1 had higher discrimination and was more stable in the model analysis and validation set. When combined with AFP and LDH, concordance index was respectively 0.84 and 0.8 in training and validation cohorts.

Conclusion: This study indicated that G3BP1 could predict the prognosis of ALF or ACLF patients treated with ALSS. The combination of G3BP1, AFP and LDH could accurately evaluate the disease condition and predict the clinical endpoint of patients.

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