Development of an explainable prediction model for portal vein system thrombosis post-splenectomy in patients with cirrhosis.

ABSTRACT:

Background

Portal vein system thrombosis (PVST) is a common and potentially life-threatening complication following splenectomy plus pericardial devascularisation (SPDV) in patients with cirrhosis and portal hypertension. Early prediction of PVST is critical for timely intervention. This study aimed to develop a machine learning-based prediction model for PVST occurrence within 3 months after splenectomy.

Methods

392 patients with cirrhosis who underwent splenectomy at the Second Affiliated Hospital of Xi'an Jiaotong University between 1 July 2016 and 31 December 2022 were enrolled in this study and followed up for 3 months. The predictive model integrated 37 candidate predictors based on accessible clinical data, including demographic characteristics, disease features, imag

SUBMITTER: Qu D 

PROVIDER: S-EPMC11987112 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature