Research advances in predictive models for post-hemorrhagic stroke seizures
10.19845/j.cnki.zfysjjbzz.2025.0017
- VernacularTitle:出血性卒中后癫痫发作预测模型研究进展
- Author:
Fang SHI
1
;
Dengfeng HAN
1
Author Information
1. Department of Neurology， The First Affiliated Hospital of Xinjiang Medical University， Urumqi 830054， China
- Publication Type:Journal Article
- Keywords:
Hemorrhagic stroke;
Seizure;
Risk factor;
Prediction model;
Machine learning
- MeSH:
Seizures
- From:
Journal of Apoplexy and Nervous Diseases
2025;42(1):83-88
- CountryChina
- Language:Chinese
-
Abstract:
The occurrence of seizures after hemorrhagic stroke is a significant contributor to mortality in patients with hemorrhagic stroke. Compared with ischemic stroke， hemorrhagic stroke is more frequently to cause seizures， with high disability and high mortality. If not detected early and treated in time， seizures may aggravate patient’s conditions in the acute stage， and cause accidental injuries in the recovery stage， increasing the burden on patient’s family. Early prediction and timely treatment of seizures can improve the survival rate and quality of life of patients. With science and technology advances， domestic and international researchers have established prediction models for seizures after hemorrhagic stroke， which use machine learning methods to process and identify relevant data， improving the accuracy of prediction for the disease. This review aims to summarize risk factors for post-hemorrhagic stroke seizures and related prediction models， so as to provide guidance for clinical diagnosis and treatment.
- Full text:2025071513132580963出血性卒中后癫痫发作预测模型研究进展.pdf
