Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Apr 27, 2024; 16(4): 625-639
Published online Apr 27, 2024. doi: 10.4254/wjh.v16.i4.625
Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis
Xiao-Wei Tang, Wen-Sen Ren, Shu Huang, Kang Zou, Huan Xu, Xiao-Min Shi, Wei Zhang, Lei Shi, Mu-Han Lü
Xiao-Wei Tang, Wen-Sen Ren, Kang Zou, Huan Xu, Xiao-Min Shi, Wei Zhang, Lei Shi, Mu-Han Lü, Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
Xiao-Wei Tang, Wen-Sen Ren, Kang Zou, Huan Xu, Xiao-Min Shi, Wei Zhang, Lei Shi, Mu-Han Lü, Nuclear Medicine and Molecular Imaging Key Laboratory, The Affiliated Hospital of Southwest Medical University, Luzhou 646099, Sichuan Province, China
Shu Huang, Department of Gastroenterology, Lianshui People’ Hospital of Kangda College Affiliated to Nanjing Medical University, Huaian 223499, Jiangsu Province, China
Co-first authors: Xiao-Wei Tang and Wen-Sen Ren.
Author contributions: Tang XW and Ren WS contributed equally to this work; Ren WS, Lü MH, Tang XW, and Huang S designed the research study; Ren WS, Zou K, Xu H and Shi XM collected the data; Ren WS, Zhang W and Shi L analyzed the data and constructed the nomogram model; Ren WS, Lü MH and Tang XW wrote the manuscript. All authors have read and approve the final manuscript.
Supported by Natural Science Foundation of Sichuan Province, No. 2022NSFSC1378.
Institutional review board statement: This study was reviewed and approved by the Institutional Review Committee of the Affiliated Hospital of Southwest Medical University (approval No. KY2023387).
Informed consent statement: This is an informed consent exemption statement. All data were downloaded from the Medical Information Mart for Intensive Care IV and the eICU collaborative research database. The two databases are publicly available. Before extracting data from the database, we completed the Collaborative Institutional Training Initiative Program course and were authorized to use the database.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: Data is available on the website (https://physionet.org/).
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: Mu-Han Lü, MD, PhD, Chief Physician, Department of Gastroenterology, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Road, Jiangyang District, Luzhou 646099, Sichuan Province, China. lvmuhan@swmu.edu.cn
Received: October 17, 2023
Peer-review started: October 17, 2023
First decision: January 2, 2024
Revised: February 23, 2024
Accepted: March 18, 2024
Article in press: March 18, 2024
Published online: April 27, 2024
Processing time: 189 Days and 16.6 Hours
Core Tip

Core Tip: Liver cirrhosis patients admitted to the intensive care unit have a high mortality rate. In this study, we collected clinical data from patients with liver cirrhosis and constructed a nomogram predictive model that gained high accuracy in predicting in-hospital mortality. The accuracy was also confirmed by external validation, which suggests that the model can help us identify high-risk patients.