BPG is committed to discovery and dissemination of knowledge
Articles Published Processes
1/22/2026 8:14:07 AM | Browse: 0 | Download: 0
Publication Name World Journal of Gastroenterology
Manuscript ID 113492
Country China
Received
2025-08-27 23:13
Peer-Review Started
2025-08-27 23:13
First Decision by Editorial Office Director
2025-11-04 09:38
Return for Revision
2025-11-04 09:38
Revised
2025-11-22 15:46
Publication Fee Transferred
Second Decision by Editor
2025-12-17 02:40
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director
2025-12-17 13:53
Articles in Press
2025-12-17 13:53
Edit the Manuscript by Language Editor
Typeset the Manuscript
2026-01-15 01:14
Publish the Manuscript Online
2026-01-22 08:14
ISSN 1007-9327 (print) and 2219-2840 (online)
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/
Copyright © The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Gastroenterology & Hepatology
Manuscript Type Retrospective Study
Article Title Machine learning-based prediction models for liver-related events in patients with hepatitis B-related cirrhosis and clinically significant portal hypertension
Manuscript Source Unsolicited Manuscript
All Author List Yan-Qiu Li, Zhuo-Jun Li, Yong-Qi Li, Ying Feng and Xian-Bo Wang
ORCID
Author(s) ORCID Number
Ying Feng http://orcid.org/0000-0002-6427-8752
Xian-Bo Wang http://orcid.org/0000-0002-3593-5741
Funding Agency and Grant Number
Funding Agency Grant Number
the High-level Chinese Medicine Key Discipline Construction Project zyyzdxk-2023005
Capital’s Funds for Health Improvement and Research 2024-1-2173
National Natural Science Foundation of China 82474419
National Natural Science Foundation of China 82474426
Beijing Municipal Natural Science Foundation 7232272
Beijing Traditional Chinese Medicine Technology Development Fund Project BJZYZD-2023-12
Corresponding Author Xian-Bo Wang, Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Chaoyang District, Beijing 100015, China. wangxb@ccmu.edu.cn
Key Words Hepatitis B; Liver cirrhosis; Clinically significant portal hypertension; Machine learning; Liver-related events; Prediction model
Core Tip This study developed and validated machine learning models to predict liver-related events in patients with compensated hepatitis B virus-related cirrhosis and clinically significant portal hypertension. Among five models, extreme gradient boosting and random forest achieved the best accuracy and clinical utility. The liver stiffness measurement-to-platelet ratio (LPR) emerged as the most influential predictor, interacting with hemoglobin, international normalized ratio, and spleen thickness. These findings highlight machine learning based on LPR as a robust noninvasive method and provide a novel, interpretable tool for early risk stratification and personalized management in compensated cirrhosis.
Publish Date 2026-01-22 08:14
Citation

Li YQ, Li ZJ, Li YQ, Feng Y, Wang XB. Machine learning-based prediction models for liver-related events in patients with hepatitis B-related cirrhosis and clinically significant portal hypertension. World J Gastroenterol 2026; 32(4): 113492

URL https://www.wjgnet.com/1007-9327/full/v32/i4/113492.htm
DOI https://dx.doi.org/10.3748/wjg.v32.i4.113492
Full Article (PDF) WJG-32-113492-with-cover.pdf
Manuscript File 113492_Auto_Edited_111120.docx
Answering Reviewers 113492-answering-reviewers.pdf
Audio Core Tip 113492-audio.m4a
Biostatistics Review Certificate 113492-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form 113492-conflict-of-interest-statement.pdf
Copyright License Agreement 113492-copyright-assignment.pdf
Signed Informed Consent Form(s) or Document(s) 113492-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document 113492-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate 113492-non-native-speakers.pdf
Supplementary Material 113492-supplementary-material.pdf
Peer-review Report 113492-peer-reviews.pdf
Scientific Misconduct Check 113492-scientific-misconduct-check.png
Scientific Editor Work List 113492-scientific-editor-work-list.pdf
CrossCheck Report 113492-crosscheck-report.pdf