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World J Hepatol. Mar 27, 2025; 17(3): 104580
Published online Mar 27, 2025. doi: 10.4254/wjh.v17.i3.104580
Hepatic cirrhosis and decompensation: Key indicators for predicting mortality risk
Sara Del Cioppo, Jessica Faccioli, Lorenzo Ridola
Sara Del Cioppo, Lorenzo Ridola, Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Rome 00185, Italy
Jessica Faccioli, Department of Translational and Precision Medicine, Sapienza University of Rome, Rome 00185, Italy
Co-first authors: Sara Del Cioppo and Jessica Faccioli.
Author contributions: Del Cioppo S and Faccioli J were responsible for conceptualization and manuscript writing; Ridola L was responsible for conceptualization, manuscript writing, and key revisions of important knowledge content; all of the authors read and approved the final version of the manuscript to be published.
Conflict-of-interest statement: All authors declare no conflict of interest in publishing the manuscript.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Lorenzo Ridola, PhD, Associate Professor, Department of Medical and Surgical Sciences and Biotechnologies, Sapienza University of Rome, Viale dell'Università 37, Rome 00185, Italy. lorenzo.ridola@uniroma1.it
Received: December 25, 2024
Revised: February 28, 2025
Accepted: March 10, 2025
Published online: March 27, 2025
Processing time: 91 Days and 15.1 Hours
Abstract

Liver cirrhosis represents the final stage of liver diseases. The transition from the compensated to the decompensated form is a critical phase, as it is associated with a negative impact on patient prognosis. Therefore, having a tool to identify patients at higher risk of complications and mortality is an ideal goal. Currently, the validated scores for this purpose are the model for end-stage liver disease score and the Child-Pugh score. However, these scores have limitations, as they do not account for other factors associated with liver cirrhosis that are equally relevant from a prognostic perspective. Among these, alterations in body composition, particularly sarcopenia, increase the risk of mortality and should therefore be considered in the comprehensive assessment of patients with liver cirrhosis.

Keywords: Liver cirrhosis; Prognostic score; Decompensation; Mortality; Sarcopenia; Child-Pugh; Model for end-stage liver disease; Artificial intelligence; Survival; Obesity

Core Tip: Identifying prognostic factors is crucial for improving risk prediction and guide clinical management in cirrhotic patients. While traditional models like model for end-stage liver disease and Child-Turcotte-Pugh are useful and provide important prognostic information, incorporating variables such as nutrition assessment, sarcopenia and muscle function, may offer a more comprehensive understanding of disease progression. This approach facilitates early detection of high-risk patients and enable timely interventions to avoid decompensation. So, considering additional prognostic factors can help clinicians to improve both outcomes and quality of life of cirrhotic patients. Furthermore, today, artificial intelligence can enhance the assessment of prognostic factors by analyzing complex data patterns.