Predicting cerebral infarction and transient ischemic attack in healthy individuals and those with dysmetabolism: a machine learning approach combined with routine blood tests.

ABSTRACT: Ischemic cerebral infarction is the most prevalent type of stroke, causing significant disability and death worldwide. Transient ischemic attack (TIA) is a strong predictor of subsequent stroke. Individuals with dysmetabolism, such as hypertension, hypercholesterolemia, and diabetes, are at increased risk for cerebral infarction (CI) and TIA. In resource-limited settings, diagnosing CI and TIA can be particularly difficult due to a lack of advanced imaging and specialized expertise. Therefore, we aim to develop a simple, convenient, blood-based approach that could assist clinicians in diagnosing CI and TIA, especially in regions where advanced imaging or stroke-specific expertise is limited. All study subjects were patients admitted to the First Hospital of Xiamen University and healthy ch

SUBMITTER: Yang Y 

PROVIDER: S-EPMC12003726 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature