Development and Internal Validation of a Clinical Imaging-Based Stroke Prediction Model in a Community Cohort.

ABSTRACT:

Background

Existing stroke prediction models tend to overestimate contemporary stroke risk and inadequately incorporate neuroimaging parameters. This study aimed to develop a novel and accurate stroke prediction model for a community-based population by integrating comprehensive neuroimaging data.

Methods

A prospective cohort study was conducted involving 1586 eligible participants from northern rural China. Baseline clinical and neuroimaging data were collected, with annual follow-ups to assess incident stroke. Least absolute shrinkage and selection operator regression was used to identify key predictors, which were subsequently incorporated into a Cox proportional hazards model to develop the final predictive model. Internal validation was performed via 500 times bootstrap

SUBMITTER: Wang YY 

PROVIDER: S-EPMC12553450 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature