Abstract
This study aims to identify an optimal model for assessing the recurrence frequency of Budd-Chiari syndrome (BCS) and further analyze the factors contributing to BCS recurrence. A total of 754 patients who were admitted to the Affiliated Hospital of Xuzhou Medical University between January 2015 and July 2022 were included. We constructed 4 different count outcome models: Poisson, negative binomial (NB) model, zero-inflated Poisson (ZIP) model, and zero-inflated negative binomial (ZINB) model. We selected the model with the best fitting performance to explore factors associated with BCS recurrence. Of 754 respondents, 511 reported no recurrence. Log-likelihood ratio tests indicated that the NB model performed better than the Poisson regression model (χ2 = 124.91, P < .001), and the ZINB model outperformed the ZIP model (χ2 = 34.29, P < .001). In the ZINB model, the analysis of the counting process revealed that the variables significantly associated with recurrence frequency included age (odds ratio [OR] = 0.69; 95% confidence interval [CI]: 0.57-0.84), sex (female: OR = 1.77; 95% CI: 1.24-2.55), anticoagulant use (warfarin vs new oral anticoagulants [NOACs]: OR = 2.11, 95% CI: 1.34-3.31; not using anticoagulants vs NOACs: OR = 1.98, 95% CI: 1.20-3.28), absence of cirrhosis (OR = 0.57, 95% CI: 0.40-0.82), and neutrophil count (NEU) (OR = 1.22, 95% CI: 1.04-1.42). The zero-inflated model proved robust in identifying factors influencing BCS recurrence compared with the other models. Influence of sex, surgery, anticoagulation, cirrhosis, hospital duration, apolipoprotein A, and NEU on the recurrence risk and frequency of BCS.