Reviews on Imaging-based Risk Prediction Models for Ischemic Stroke

Stroke significantly impacts national health due to its high incidence, disability, mortality, and recurrence rates, resulting in a substantial economic burden. Risk prediction models for ischemic stroke help identify high-risk populations for early prevention, diagnosis, and treatment. Various risk...

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Bibliographic Details
Main Author: Cui Liuping, Liu Ran, Liu Yumei, Zhou Fubo, Tao Yunlu, Xing Yingqi
Format: Article
Language:English
Published: Editorial Office of Advanced Ultrasound in Diagnosis and Therapy 2025-06-01
Series:Advanced Ultrasound in Diagnosis and Therapy
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Online Access:https://www.journaladvancedultrasound.com/fileup/2576-2516/PDF/1751848701315-1912304829.pdf
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Summary:Stroke significantly impacts national health due to its high incidence, disability, mortality, and recurrence rates, resulting in a substantial economic burden. Risk prediction models for ischemic stroke help identify high-risk populations for early prevention, diagnosis, and treatment. Various risk-scoring models have been developed for primary and secondary prevention of ischemic stroke, estimating the probability of cardiovascular events over a specified timeframe based on the presence of known risk factors. However, these risk-scoring models often lack precision for cardiovascular disease risk assessments across diverse baseline risk conditions. Integrating image-based biomarkers into existing risk-prediction models may enhance risk stratification accuracy. This review presents the most used models for ischemic stroke prediction and underscores the clinical utility of biomarkers in the management of ischemic stroke.
ISSN:2576-2516