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ORIGINAL RESEARCH article

Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1475292
This article is part of the Research Topic World Hepatitis Day 2024: Advancing Hepatitis Elimination, Public Health Strategies and Innovations View all articles

Analysis of risk factors for sepsis-related liver injury and construction of a prediction model

Provisionally accepted
Xin Nie Xin Nie Chi Wang Chi Wang Wan He Wan He He Zhang He Zhang Fei Ding Fei Ding Ying Liu Ying Liu He He He He Yong He Yong He *
  • West China Hospital, Sichuan University, Chengdu, China

The final, formatted version of the article will be published soon.

    Abstract Background: Sepsis is a leading cause of mortality in critically ill patients, and the liver is a key organ affected by sepsis. Sepsis-related liver injury (SRLI) is an independent risk factor for multiple organ dysfunction syndrome (MODS) and mortality. However, there is no clear diagnostic standard for SRLI, making early detection and intervention challenging. Objective: This study aimed to investigate the predictive value of serum indices for the occurrence of SRLI in adults to guide clinical practice. Methods In this study, we investigated the predictive value of serum indices for SRLI in adults. We retrospectively analyzed data from 1573 sepsis patients admitted to West China Hospital, Sichuan University, from January 2015 to December 2019. Patients were divided into those with and without liver injury. Stepwise logistic regression identified independent risk factors for SRLI, and a predictive model was constructed. The model's diagnostic efficacy was assessed using receiver operating characteristic (ROC) curve analysis. Results Our results showed that alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (GGT), carbon dioxide combining power (CO2-CP), antithrombin III (AT III), fibrin/fibrinogen degradation products (FDP), and red blood cell distribution width (RDW-CV) were independent predictors of SRLI. The area under the curve (AUC) of the predictive model was 0.890, with a sensitivity of 80.0% and a specificity of 82.91%, indicating excellent diagnostic value. Conclusions In conclusion, this study developed a highly accurate predictive model for SRLI using clinically accessible serum indicators, which could aid in early detection and intervention, potentially reducing mortality rates.

    Keywords: Sepsis, liver injury, Early prediction, Risk factors, ROC Curve

    Received: 03 Aug 2024; Accepted: 20 Nov 2024.

    Copyright: © 2024 Nie, Wang, He, Zhang, Ding, Liu, He and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yong He, West China Hospital, Sichuan University, Chengdu, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.