Prediction of post-stroke cognitive impairment after acute ischemic stroke using machine learning.

ABSTRACT:

Background and objectives

Post-stroke cognitive impairment (PSCI) occurs in up to 50% of patients with acute ischemic stroke (AIS). Thus, the prediction of cognitive outcomes in AIS may be useful for treatment decisions. This PSCI cohort study aimed to determine the applicability of a machine learning approach for predicting PSCI after stroke.

Methods

This retrospective study used a prospective PSCI cohort of patients with AIS. Demographic features, clinical characteristics, and brain imaging variables previously known to be associated with PSCI were included in the analysis. The primary outcome was PSCI at 3-6 months, defined as an adjusted z-score of less than - 2.0 standard deviation in at least one of the four cognitive domains (memory, executive/frontal, visuospatial, a

SUBMITTER: Lee M 

PROVIDER: S-EPMC10468853 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature