Retrospective Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jul 7, 2023; 29(25): 4072-4084
Published online Jul 7, 2023. doi: 10.3748/wjg.v29.i25.4072
Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness
Long-Bao Yang, Xin Gao, Hong Li, Xin-Xing Tantai, Fen-Rong Chen, Lei Dong, Xu-Sheng Dang, Zhong-Cao Wei, Chen-Yu Liu, Yan Wang
Long-Bao Yang, Xin Gao, Hong Li, Xin-Xing Tantai, Fen-Rong Chen, Lei Dong, Zhong-Cao Wei, Chen-Yu Liu, Yan Wang, Department of Gastroenterology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, Shaanxi Province, China
Xu-Sheng Dang, Department of Emergency, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710004, Shaanxi Province, China
Author contributions: Yang LB and Gao X contributed equally to this work; Li H, Dong L, and Dang XS designed the research study; Liu CY and Gao X performed the research; Tantai XX and Wei ZC contributed new reagents and analytic tools; Yang LB, Wang Y, and Chen FR analyzed the data and wrote the manuscript; and all authors have read and approve the final manuscript.
Supported by the Shaanxi Provincial Key Research and Development Plan, No. 2020SF-159.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of the Second Affiliated Hospital of Xi’an Jiaotong University (approval No. 2017-445).
Informed consent statement: This study is a retrospective study; thus, the ethics committee has exempted the informed consent of the patients.
Conflict-of-interest statement: There was no any interests conflicts.
Data sharing statement: No additional data are available.
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: Yan Wang, MD, Assistant Professor, Department of Gastroenterology, The Second Affiliated Hospital of Xi’an Jiaotong University, No. 157 of Xiwu Road, Xi’an 710004, Shaanxi Province, China. sarrye@163.com
Received: April 23, 2023
Peer-review started: April 23, 2023
First decision: May 15, 2023
Revised: May 20, 2023
Accepted: June 2, 2023
Article in press: June 2, 2023
Published online: July 7, 2023
Processing time: 65 Days and 17.3 Hours
ARTICLE HIGHLIGHTS
Research background

Acute bleeding due to esophageal varices (EVs) is a life-threatening complication in patients with cirrhosis. The diagnosis of EVs is mainly through upper gastrointestinal endoscopy, but the discomfort, contraindications and complications of gastrointestinal endoscopic screening reduce patient compliance.

Research motivation

To develop a safe, simple and non-invasive model to predict high risk EVs (HEVs) in patients with viral cirrhosis and identify patients who can be exempted from upper gastrointestinal endoscopy.

Research objectives

To establish a non-invasive prediction model based on spleen stiffness measurement (SSM) and live stiffness measurement (LSM) as an alternative to EVs screening.

Research methods

Two hundred Chinese adults, from March 2020 to November 2022, were included at the Second Affiliated Hospital of Xi’an Jiaotong University. Required data were collected by the medical records, and the EVs types of patients were determined by upper gastrointestinal endoscopy and the Baveno VI consensus. The effect of each parameter on HEVs was analyzed by univariate and multivariate analyses, and a non-invasive prediction model was established, and then the effect of each parameter on HEVs was analyzed by univariate and multivariate analyses, and a non-invasive prediction model was established.

Research results

After univariate and multivariate analyses, SSM and LSM were used to established a prediction model. The new non-invasive model was better than other four models to predict HEVs in patients with viral cirrhosis.

Research conclusions

The new model is reliable in predicting HEVs and can be used as an alternative to routine upper gastrointestinal endoscopy screening, which is helpful for clinical decision making.

Research perspectives

In the future, we will try to apply the new model to predict HEVs in patients with viral cirrhosis.