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
Abstract
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. According to the bleeding risk of EVs, the Baveno VI consensus divides varices into high bleeding risk EVs (HEVs) and low bleeding risk EVs (LEVs). We sought to identify a non-invasive prediction model based on spleen stiffness measurement (SSM) and liver stiffness measurement (LSM) as an alternative to EVs screening.

AIM

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

METHODS

Data from 200 patients with viral cirrhosis were included in this study, with 140 patients as the modelling group and 60 patients as the external validation group, and the EVs types of patients were determined by upper gastrointestinal endoscopy and the Baveno VI consensus. Those patients were divided into the HEVs group (66 patients) and the LEVs group (74 patients). The effect of each parameter on HEVs was analyzed by univariate and multivariate analyses, and a non-invasive prediction model was established. Finally, the discrimination ability, calibration ability and clinical efficacy of the new model were verified in the modelling group and the external validation group.

RESULTS

Univariate and multivariate analyses showed that SSM and LSM were associated with the occurrence of HEVs in patients with viral cirrhosis. On this basis, logistic regression analysis was used to construct a prediction model: Ln [P/(1-P)] = -8.184 -0.228 × SSM + 0.642 × LSM. The area under the curve of the new model was 0.965. When the cut-off value was 0.27, the sensitivity, specificity, positive predictive value and negative predictive value of the model for predicting HEVs were 100.00%, 82.43%, 83.52%, and 100%, respectively. Compared with the four prediction models of liver stiffness-spleen diameter to platelet ratio score, variceal risk index, aspartate aminotransferase to alanine aminotransferase ratio, and Baveno VI, the established model can better predict HEVs in patients with viral cirrhosis.

CONCLUSION

Based on the SSM and LSM measured by transient elastography, we established a non-invasive prediction model for HEVs. 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.

Keywords: Cirrhosis, High-risk esophageal varices, Non-invasive prediction model, Spleen stiffness measurement, Liver stiffness measurement, Upper gastrointestinal endoscopy

Core Tip: The non-invasive prediction model for predicting high risk esophageal varices (HEVs) in patients with viral cirrhosis was successfully established based on the spleen stiffness measurement and liver stiffness measurement. It is a novel model that has not been reported. The model was shown to be better than previous prediction models. 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.