Published online Jun 7, 2020. doi: 10.3748/wjg.v26.i21.2839
Peer-review started: December 28, 2019
First decision: January 13, 2020
Revised: March 26, 2020
Accepted: April 21, 2020
Article in press: April 21, 2020
Published online: June 7, 2020
Several models for predicting high-risk esophageal varices (HEVs) have been reported; however, models that are based on liver and spleen volume calculation formula in HEVs have not been reported.
HEVs are EVs that have a high risk of bleeding, and the establishment of a non-invasive predictive model will be useful for the early identification of HEVs. These patients will benefit if necessary measures are taken in a timely manner.
This present study established a non-invasive prediction model based on the liver and spleen volume calculation formula for predicting HEVs in patients with viral cirrhosis.
Eighty-six EVs patients with viral cirrhosis, from October 2017 to December 2018, were included at the Second Affiliated Hospital of Xi’an Jiaotong University. By reviewing the medical records, required data were collected for. The impact of each parameter on HEVs was analyzed by univariate and multivariate analyses, the data from which were employed to establish a non-invasive prediction model. Then the established prediction model was compared with LSPS, VRI, APRI, and AAR. The discriminating ability, calibration ability, and clinical efficacy of the established model were verified in both the modeling group and the external validation group.
After univariate and multivariate analysis, liver-spleen volume ratio, spleen volume change rate, and aspartate aminotransferase were successfully used to establish the non-invasive prediction model for HEVs. The new model could better predict HEVs compared with LSPS, VRI, APRI, and AAR. The discriminating ability, calibration ability, and clinical efficacy of the new model were verified.
The non-invasive prediction model for predicting HEVs is a reliable model for predicting HEVs and has clinical applicability.
The predictive value of the new model needs to be confirmed in a large number of virus cirrhosis patients with EVs. Predictive models with high accuracy need to be established taking into account the limitations of the new model.