New model predicting gastroesophageal varices and variceal hemorrhage in patients with chronic liver disease

Abstract

Introduction and objectives: The predictors for gastroesophageal varices (GOV) and hemorrhage development have not been well studied in different liver diseases or different population. This study aimed to evaluate whether a new algorithm focusing on chronic hepatitis B (CHB) patients is also applicable to other chronic liver diseases (CLDs) in Chinese population.

Patients or materials and methods: We retrospectively analyzed 659 CHB patients and 386 patients with other CLDs. A total of 439 CHB patients were included in training set, the other 220 CHB patients and other patients with CLDs were included in validation set. A new algorithm for diagnosing GOV was established and its sensitivity and specificity for predicting the varices was verified.

Results: Multivariable logistic regression revealed that the rough surface of the liver (p<0.001), splenic thickness (p<0.001), and liver stiffness (p=0.006) were independent predictors of GOV. The new algorithm was considered to be a reliable diagnostic model to evaluate the presence of varices. The AUROC was 0.94 (p<0.001) in CHB validation set and 0.90 (<0.001) in non-CHB validation set. When the cut-off value was chosen as -1.048, the sensitivity and specificity in diagnosing GOV in CHB population were 89.1% and 82.5%, respectively. Importantly, the new algorithm accurately predicted the variceal hemorrhage not only in CHB patients, but also in patients with other CLDs.

Conclusion: The new algorithm is regarded as a reliable model to prognosticate varices and variceal hemorrhage, and stratified not only the high-risk CHB patients, but also in patients with other CLDs for developing GOV and variceal bleeding.

Keywords: Algorithm; Chronic hepatitis B; Gastroesophageal varices; Variceal hemorrhage.