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Retrospective Study
Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.
World J Hepatol. Sep 27, 2026; 18(9): 123456
Published online Sep 27, 2026. doi: 10.4254/wjh.123456
Analysis of risk factors and a prediction model for rebleeding in liver cirrhosis patients with esophagogastric variceal bleeding
Ping-Ping Li, Xiao Zhong, Da-Ya Zhang, Fei-Hu Bai
Ping-Ping Li, Xiao Zhong, Da-Ya Zhang, Fei-Hu Bai, Department of Gastroenterology, The Second Affiliated Hospital of Hainan Medical University, Haikou 570216, Hainan Province, China
Co-first authors: Ping-Ping Li and Xiao Zhong.
Author contributions: Li PP, Zhong X, and Zhang DY collected data; Li PP, Zhang DY and Bai FH designed the study and performed statistical analysis; Li PP, Zhong X, Zhang DY and Bai FH drafted the manuscript, recruited participants; all authors read and approved the final manuscript; Li PP and Zhong X have made crucial and indispensable contributions towards the completion of the project and thus qualified as the co-first authors of the paper.
AI contribution statement: Not applicable, as no AI tools were used in the research or manuscript preparation.
Supported by the 2025 Hainan Flexible Talent Introduction and Innovation Platform Performance Assessment; the Academic Improvement Support Program of Hainan Medical University, No. XSTS2025001 and No. XSTS2026051; Funded Project of the 2026 Undergraduate Scientific Research and Innovation Training Program, Hainan Medical University, No. RZ2600001129; the National Clinical Key Specialty Capacity Building Project, No. 202330; Hainan Provincial Education Reform Project, No. hnjg2024-67; and the Joint Scientific and Technological Innovation Project of Health Commission of Hainan Province, No. WSJK2024MS150.
Institutional review board statement: The protocol was approved by the institutional ethics committee of the Second Hospital of Hainan Medical University (No. 2026-K20-01) and performed per Helsinki’s Declaration.
Informed consent statement: All participants provided written informed consent for data collection and storage.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Data sharing statement: The datasets used and/or analyzed in this study can be reasonably obtained from the corresponding author.
Corresponding author: Fei-Hu Bai, Chief Physician, Department of Gastroenterology, The Second Affiliated Hospital of Hainan Medical University, No. 368 Yehai Avenue, Longhua District, Haikou 570216, Hainan Province, China. hy214654@muhn.edu.cn
Received: May 25, 2026
Revised: July 21, 2026
Accepted: August 28, 2026
Published online: September 27, 2026
Processing time: 117 Days and 16.2 Hours
Core Tip

Core Tip: This single-center retrospective study enrolled 130 cirrhotic patients with esophagogastric variceal bleeding (EGVB) in 2024 and conducted a one-year follow-up, including 62 rebleeding cases and 68 non-rebleeding cases, aiming to address the high mortality of EGVB rebleeding and the lack of simple non-invasive predictive tools for Hainan population. The study identified four independent risk factors for rebleeding -decreased red blood cell, elevated blood urea nitrogen, ascites, and thickening of the gallbladder wall (TGBW); notably, TGBW was originally validated as a novel non-invasive imaging predictor with an odds ratio value of 0.199 (P < 0.001). A reliable nomogram prediction model was further constructed with an original area under the curve (AUC) of 0.853 and a bootstrap internal validation AUC of 0.855, presenting favorable calibration and clinical applicability. Since this model merely requires routine blood tests and ultrasonic indicators, it can realize convenient and non-invasive risk stratification to guide secondary clinical prevention for local patients. Nevertheless, this research is limited by its retrospective nature, single-center setting and relatively small sample size; and further multi-center prospective studies are required to verify the generalizability of the model.

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