A linear clinical prediction model and nomogram evaluating risk of portal vein thrombosis in liver cirrhosis

As one of the complications of liver cirrhosis, portal vein thrombosis (PVT) brings a significant clinical challenge. To find the predictive clinical variables evaluating the probability of PVT, a prediction model was established and a nomogram was built for visualization. Our study selected 245 cirrhosis patients admitted in First Hospital of Jilin University during August 2020 to June 2024, the majority of whom were admitted during July 2022 to June 2023. All patients were randomly separated into a training set and a validation set. Binary logistic and Lasso regression were used to establish predictive models with the occurrence of PVT events within 24 months after discharge as the clinical outcome. In discovery set, 64 (26.1%) of them had events of PVT within 24 months after their discharge. A linear model “ASP” was constructed with logarithm of alkaline phosphatase (Log 10 ALP), splenectomy and portal vein width selected for predicting PVT risk, preformed with its AUC reached 0.793, 0.750 and 0.760 in training, internal validation and external validation set, respectively. We finally screened out three clinical variables identifying high-risk PVT patients in liver cirrhosis beforehand. ALP level might be a potential clinical parameter connected to PVT, but need to be further verified.