Predicting response to non-selective beta-blockers with liver –spleen stiffness and heart rate in patients with liver cirrhosis and high-risk varices

This study aims to define a  noninvasive machine-learning based approach to determine response to NSBB in patients with liver cirrhosis and HRVs.MethodsWe conducted a prospective study on a cohort of cirrhotic patients with documented HRVs receiving NSBB treatment. Patients were followed-up with clinical and elastography appointments at 3, 6, and 12  months after NSBB treatment initiation. NSBB response was defined as stationary or downstaging variceal grading at the 12-month esophagogastroduodenoscopy (EGD). In contrast, non-response was defined as upstaging variceal grading at the 12-month EGD or at least one variceal hemorrhage episode duri ng the 12-month follow-up. We chose cut-off values for univariate and multivariate model with 100% specificity.ResultsAccording to least absolute shrinkage and selection operator (LASSO) regression, spleen stiffness (SS) and liver stiffness (LS) percentual decrease, along with changes in heart rate (HR) at 3  months were the most significant predictors of NSBB response. A decrease>  11.5% in SS, >  16.8% in LS, and >  25.3% in HR was associated with better prediction of clinical response to NSBB. SS percentual decrease showed the highest accuracy (86.4%) with high sensitivity (78.8%) when compared to LS and HR. The multivariate model incorporating SS, LS, and HR showed the highest discrimination and calibratio n metrics (AUROC = 0.96), with the optimal cut-off of 0.90 (sensitivity 94.2%, specificity 100%, PPV ...
Source: Hepatology International - Category: Infectious Diseases Source Type: research