Blood Pressure Predicted From Artificial Intelligence Analysis of Retinal Images Correlates With Future Cardiovascular Events.

ABSTRACT:

Background

High systolic blood pressure (SBP) is one of the leading modifiable risk factors for premature cardiovascular death. The retinal vasculature exhibits well-documented adaptations to high SBP and these vascular changes are known to correlate with atherosclerotic cardiovascular disease (ASCVD) events.

Objectives

The purpose of this study was to determine whether using artificial intelligence (AI) to predict an individual's SBP from retinal images would more accurately correlate with future ASCVD events compared to measured SBP.

Methods

95,665 macula-centered retinal images drawn from the 51,778 individuals in the UK Biobank who had not experienced an ASCVD event prior to retinal imaging were used. A deep-learning model was trained to predict an individual's SB

SUBMITTER: Squirrell DM 

PROVIDER: S-EPMC11612377 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature