Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Aug 21, 2025; 31(31): 105229
Published online Aug 21, 2025. doi: 10.3748/wjg.v31.i31.105229
Dynamic nomogram predicts sepsis risk in patients with acute liver failure: Analysis of intensive care database with external validation
Rui Qi, Xin Wang, Zhi-Dan Kuang, Xue-Yi Shang, Fang Lin, Dan Chang, Jin-Song Mu
Rui Qi, Jin-Song Mu, Peking University 302 Clinical Medical School, Beijing 100039, China
Rui Qi, Xin Wang, Zhi-Dan Kuang, Xue-Yi Shang, Fang Lin, Dan Chang, Jin-Song Mu, Department of Critical Care Medicine, The Fifth Medical Center of Chinese PLA General Hospital, Beijing 100039, China
Author contributions: Qi R contributed to writing the original draft, data collection, and statistical analysis; Wang X contributed to statistical analysis and interpretation; Kuang ZD and Chang D contributed to data collection and data curation; Shang XY and Lin F contributed to reviewing and editing; Mu JS contributed to study conception and design, reviewing, and editing; All authors critically reviewed and approved the final manuscript; All authors were responsible for the decision to submit the manuscript for publication.
Supported by National Key Research and Development Program, No. 2022YFA1103501.
Institutional review board statement: Medical Information Mart for Intensive Care IV is a public database, and all patient information is anonymized to protect privacy. Therefore, the requirement for approval by the local ethics committee was waived. The Fifth Medical Center of Chinese PLA General Hospital cohort strictly complied with the ethical standards outlined in the Declaration of Helsinki and received approval from the Ethics Committee of the Fifth Medical Center of Chinese PLA General Hospital (No. KY-2024-10-163-1).
Informed consent statement: The Medical Information Mart for Intensive Care IV database obtained ethical approval from the Institutional Review Boards at both Beth Israel Deaconess Medical Center and Massachusetts Institute of Technology. Informed consent from patients in The Fifth Medical Center of Chinese PLA General Hospital cohort was waived due to the retrospective nature of the study.
Conflict-of-interest statement: All authors report no relevant conflicts of interest for this article.
Data sharing statement: The datasets used or analyzed during the current study are available from the corresponding author upon reasonable request at jinsongmu302@126.com.
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: Jin-Song Mu, MD, PhD, Associate Professor, Chief Physician, Peking University 302 Clinical Medical School, No. 100 Xisihuan Middle Road, Fengtai District, Beijing 100039, China. jinsongmu302@126.com
Received: January 16, 2025
Revised: April 8, 2025
Accepted: July 16, 2025
Published online: August 21, 2025
Processing time: 214 Days and 16.9 Hours
Core Tip

Core Tip: The study developed and validated a dynamic nomogram to predict sepsis risk in patients with acute liver failure using the Medical Information Mart for Intensive Care database and an external cohort. Key predictors included age, total bilirubin, lactate dehydrogenase, albumin, and mechanical ventilation. The model demonstrated satisfactory accuracy, outperformed Sequential Organ Failure Assessment and systemic inflammatory response syndrome scores. Decision curve analysis and calibration curves confirmed superior clinical utility and efficiency. The model-based risk stratification and online calculator might further facilitate risk evaluation and guide rational management.