Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospective cohort study design.

ABSTRACT:

Objective

Despite extensive exploration of potential biomarkers of cardiovascular diseases (CVDs) derived from retinal images, it remains unclear how retinal images contribute to CVD risk profiling and how the results can inform lifestyle modifications. Therefore, we aimed to determine the performance of cardiovascular risk prediction model from retinal images via explicitly estimating 10 traditional CVD risk factors and compared with the model based on actual risk measurements.

Design

A prospective cohort study design.

Setting

The UK Biobank (UKBB), a prospective cohort study, following the health conditions including CVD outcomes of adults recruited between 2006 and 2010.

Participants

A subset of data from the UKBB which contains 52 297 entries with retinal i

SUBMITTER: Qian Y 

PROVIDER: S-EPMC11474751 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature