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.