Statistical analysis
Statistical analysis was performed using SPSS version 19.0 (IBM, New York, USA) and the time receiver operating characteristic curve (ROC) package in R version 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria). All statistical tests were two-sided with a 5% significance level. Continuous variables and categorical variables were summarized and compared. Propensity score matching (PSM) is calculated by logistic regression based on baseline characteristics, including age, gender, Child-Pugh score total bilirubin, alanine aminotransferase, aspartate transaminase, albumin, PLT, LSM, etiology and the score of the novel model were applied to achieve a balance between carvedilol and non-NSBBs cohorts. The diagnostic accuracy of the novel model was assessed using the areas under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Comparisons of accuracy were made with the DeLong method between the novel model, ANTICIPATE model and Baveno VII criteria. Moreover, we considered a diagnostic model adequate with NPV ≥90% for ruling out CSPH and PPV ≥90% for ruling in CSPH.