Development and validation of an interpretable machine learning model to predict malignant cerebral edema after endovascular treatment in acute anterior circulation large vessel occlusion stroke.

ABSTRACT:

Background

Malignant cerebral edema (MCE) is a life-threatening complication following endovascular treatment (EVT) in patients with acute anterior circulation large vessel occlusion (LVO) stroke. This study aimed to develop and validate a machine learning (ML)-based predictive model for early risk assessment of MCE in this population.

Methods

We retrospectively collected data of 364 acute ischemic stroke patients with acute anterior circulation large vessel occlusion from a comprehensive stroke center in Shanghai, between August 2018 and December 2024. Eighty percent of patients were randomly assigned to the training set, and the remaining 20 % to the internal validation set. Additional 162 patients from the One Pass Tirofiban In Management of Ischemic Stroke Thrombectomy I

SUBMITTER: Dong Z 

PROVIDER: S-EPMC12807922 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature