AUTHOR=Liang Huixin , Si Hang , Liu Mingzhu , Yuan Lianxiong , Ma Ruiying , Zhang Genglin , Yang Jianrong , Mo Zhishuo , Zhao Qiyi 

TITLE=Non-Invasive Prediction Models for Esophageal Varices and Red Signs in Patients With Hepatitis B Virus-Related Liver Cirrhosis

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2022.930762

DOI=10.3389/fmolb.2022.930762

ISSN=2296-889X

ABSTRACT=Background
Red signs are closely related to esophageal variceal bleeding, and, despite improvements in therapy, the mortality rate remains high. We aimed to identify non-invasive predictors of esophageal varices and red signs in patients with hepatitis B virus-related liver cirrhosis.
Methods
This retrospective study included 356 patients with hepatitis B virus-related liver cirrhosis after applying inclusion/exclusion criteria among 661 patients. All patients underwent endoscopy, ultrasonography, laboratory examinations, and computed tomography/magnetic resonance imaging. Univariate and multivariate logistic regression analysis were performed, and prediction models for esophageal varices and red signs were constructed.
Results
Multivariate analysis revealed that spleen diameter, splenic vein diameter, and lymphocyte ratio were independent risk factors for esophageal varices and red signs. On this basis, we proposed two models: i) a spleen diameter-splenic vein diameter-lymphocyte ratio-esophageal varices prediction model (SSL-EV model); and ii) a spleen diameter-splenic vein diameter-lymphocyte ratio-red sign prediction model (SSL-RS model). The areas under the receiver operating characteristic curve for the two prediction models were 0.843 and 0.783, respectively. With a cutoff value of 1.55, the first prediction model had 81.3% sensitivity and 76.1% specificity for esophageal varices prediction. With a cutoff value of -0.20, the second prediction model had 72.1% sensitivity and 70.7% specificity for the prediction of red signs.
Conclusions
We proposed a new statistical model, the spleen diameter-splenic vein diameter-lymphocyte ratio-red sign prediction model (SSL-RS model), to predict the presence of red signs non-invasively. Combined with the spleen diameter-splenic vein diameter-lymphocyte ratio-esophageal varices prediction model (SSL-EV model), these non-invasive prediction models will be helpful in guiding clinical decision-making and preventing the occurrence of esophageal variceal bleeding.