Abstract
OBJECTIVE: The study aimed to create and validate a straightforward nomogram to predict portal vein thrombosis (PVT) in cirrhotic patient post-splenectomy, and investigate the predictive potential of systemic inflammation markers. One objective of the study was to develop a predictive model utilizing these markers to detect high-risk individuals early on. METHODS: A retrospective analysis was conducted on 184 cases of patients with cirrhosis who underwent splenectomy at The First Affiliated Hospital of University of South China from January 2015 to September 2023. The cohort was randomly divided into training (n = 130) and validation (n = 54) groups. Univariate and multivariate logistic regression analysis was employed to construct the prediction model. The performance of the nomogram was evaluated based on its ability to discriminate, calibrate, and demonstrate clinical utility. RESULTS: According to univariate and multivariate logistic regression analysis, we found six prediction indexes of PVT in patients with cirrhosis after splenectomy: postoperative neutrophil-to-lymphocyte ratio (NLR), postoperative derived NLR (dNLR), C-reactive protein to albumin ratio (CAR), portal vein diameter (DPV), platelet change value (PVB), and D-dimer (p-value < 0.05). Our clinical prediction model was created based on the aforementioned risk factors and demonstrated superior predictive power in both the primary cohort (AUC = 0.876) and validation cohort (AUC = 0.817). The calibration curve demonstrated satisfactory agreement between model predictions and actual observations, and the decision curve analysis (DCA) curve indicated high clinical net benefit. CONCLUSION: Postoperative NLR, dNLR, CAR, PVB, DPV, and D-dimer were identified as the independent risk factors of PVT in cirrhotic patients post splenectomy. We had successfully established and validated a novel predictive model with good performance, based on systemic inflammatory indices in predicting PVT in cirrhosis after splenectomy.