Risk Factors for Silent Brain Infarcts and White Matter Disease in a Real-World Cohort Identified by Natural Language Processing.

ABSTRACT:

Objective

To assess the frequency of silent brain infarcts (SBIs) and white matter disease (WMD) and associations with stroke risk factors (RFs) in a real-world population.

Patients and methods

This was an observational study of patients 50 years or older in the Kaiser Permanente Southern California health system from January 1, 2009, through June 30, 2019, with head computed tomography or magnetic resonance imaging for nonstroke indications and no history of stroke, transient ischemic attack, or dementia. A natural language processing (NLP) algorithm was applied to the electronic health record to identify individuals with reported SBIs or WMD. Multivariable Poisson regression estimated risk ratios of demographic characteristics, RFs, and scan modality on the presence of SBI

SUBMITTER: Leung LY 

PROVIDER: S-EPMC9284412 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature