ArticleFrontiers in neurology
Development and validation of a predictive model for cognitive impairment after first-episode acute ischemic stroke without reperfusion therapy.
Article in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: To construct and validate a predictive model of cognitive impairment after first-episode acute ischemic stroke (AIS) based on multiple factors. Methods: A total of 627 patients with first-episode AIS admitted to the Affiliated Huai'an Hospital of Xuzhou Medical University between January 2023 and June 2024 were enrolled in this study. Patients were followed up 6 months after discharge. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Among them, 188 patients with cognitive impairment were assigned to the cognitively impaired group, and 439 cognitively normal patients were assigned to the non-impaired group. These 627 patients were randomly split 8:2 into a training cohort ( Results: LASSO regression finally identified 10 predictors, such as education level, C-reactive protein (CRP), frontal lobe infarction, number of infarcts. Subsequent multivariable logistic regression analysis revealed that the number of infarcts (OR = 2.17, 95% CI: 1.65-2.86, Conclusion: This study successfully constructed a predictive model of cognitive impairment after AIS based on multi-factor analysis and machine learning. By visualizing the model in the form of the nomogram, clinicians can quickly assess the risk based on the individual patient data, thus enabling early identification and individualized intervention.
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