Affiliation:
1. School of Biomedical Sciences, Ulster University, York St, Belfast BT15 1ED, United Kingdom
2. Integrated Diagnostics
Laboratory, Ulster University, 3-5a Frederick St, Belfast, Northern Ireland, United Kingdom
Abstract
Abstract:
Cardiovascular disease remains a leading cause of death worldwide despite the use of
available cardiovascular disease risk prediction tools. Identification of high-risk individuals via risk
stratification and screening at sub-clinical stages, which may be offered by ocular screening, is important
to prevent major adverse cardiac events. Retinal microvasculature has been widely researched
for potential application in both diabetes and cardiovascular disease risk prediction. However,
the conjunctival microvasculature as a tool for cardiovascular disease risk prediction remains
largely unexplored. The purpose of this review is to evaluate the current cardiovascular risk assessment
methods, identifying gaps in the literature that imaging of the ocular microcirculation
may have the potential to fill. This review also explores the themes of machine learning, risk
scores, biomarkers, medical imaging, and clinical risk factors. Cardiovascular risk classification
varies based on the population assessed, the risk factors included, and the assessment methods. A
more tailored, standardised and feasible approach to cardiovascular risk prediction that utilises
technological and medical imaging advances, which may be offered by ocular imaging, is required
to support cardiovascular disease prevention strategies and clinical guidelines.
Publisher
Bentham Science Publishers Ltd.
Subject
Cardiology and Cardiovascular Medicine,General Medicine