Published online Nov 16, 2022. doi: 10.12998/wjcc.v10.i32.11743
Peer-review started: August 28, 2022
First decision: October 4, 2022
Revised: October 7, 2022
Accepted: October 18, 2022
Article in press: October 18, 2022
Published online: November 16, 2022
Processing time: 72 Days and 2.9 Hours
Although there are reports of models predicting esophageal varices; however, there were no models based on the standard liver and spleen volume calculation formula.
It is highly important to identify virus patients with esophageal varices (EVs) and guide them for gastroscopy, and a non-invasive predictive model can be used to identify EVs.
A non-invasive predictive model for EVs based on liver and spleen volume in viral cirrhosis patients.
A cross-sectional study based on viral cirrhosis crowd were conducted in the Second Affiliated Hospital of Xi'an Jiaotong University. By collecting the participants’ basic information and clinical data of the, we derived the independent risk factors and established the prediction model of EVs. We compared the established model with others. Area under the receiver operating characteristic curve, calibration plot and decision curve analysis were used to test the discriminating ability, calibration ability and clinical practicability in both internal and external validation group.
The portal vein diameter, the liver and spleen volume, and volume change rate were successfully used to establish the predictive model, which showed better predictive value than other models. The model indicating good discriminating ability, calibration ability and clinical practicability in both modelling and external validation group.
The developed model is a credible predictor of EVs with high specificity, calibrability and clinical efficacy.
Further studies to confirm this model’s potential using larger sample sizes are recommended. Besides, there is need to develop predictive models with high diagnostic accuracy, while considering the limitations herein.