New Algorithm based on Liver Stiffness for Predicting Gastroesophageal Varices and Variceal Hemorrhage in Patients with Chronic Liver Disease
Annals of Hepatology
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. 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
... 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. 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. 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.