Cardiovascular Disease Risk Prediction
It is well established that early detection and prevention is a cost effective means of managing healthcare budgets. With the growing problems associated with diabetes and cardiovascular risk, the UK Government launched the Vascular Check Programme, now rebranded Health Check, with the aim of early detection of those at risk of adverse events. This screening programme is free to anyone over the age of 40 years and involves an appointment, usually at a GP surgery. Certain clinical and demographic parameters are collated and a risk assessment is made with appropriate onward management decided as a result.
iGradingCVD has been designed to allow a point of care assessment of cardiovascular risk which would be more accessible to the general population and which has the potential to provide a more appropriate and individual assessment of risk, as it is based on the state of the vasculature in the person.
iGradingCVD combines Medalytix’ automated algorithms for retinopathy, used in the company’s first product, iGradingM, with a CVD risk prediction algorithm developed from extensive epidemiological CVD datasets to provide a fully automated means of non-invasively assessing the CVD risk of a person from a simple retinal photograph.
iGradingCVD is unique in the field and combines two different algorithmic approaches from two world-leading groups in their respective areas of expertise – the University of Aberdeen (retinal image analysis) and Centre for Eye Research Australia (CVD risk prediction).
The algorithms for automated detection of retinopathy incorporated within the iGradingCVD product are the most extensively validated in the field and are the only ones that have been clinically validated within a live screening programme.
The CVD risk prediction algorithm has been developed by the academic and clinical team at the Centre for Eye Research Australia in Melbourne. This team are a leading group in the epidemiology of retinal assessment and cardiovascular risk, and the algorithm has been developed using the largest database of epidemiological studies relating cardiovascular risk and retinal features in the world.
Risk prediction engines are used in clinical practice to predict a person’s risk of having an adverse cardiovascular event, such as a stroke or a heart attack. These prediction engines typically combine a number of parameters including age, gender, smoking, blood pressure, weight/ BMI, blood lipid levels, whether diabetes is present or not, whether there is a family history or not, but always require a clinical investigation and a blood test of some description. These involve significant time and money. iGradingCVD is a new, non-invasive approach to assessment of CVD risk using an automated retinal analysis which can provide an alternative approach to current practice. Early assessments indicate equivalent performance to current accepted risk prediction engines and further validation work is underway.
The combination of these two world-leading approaches makes iGradingCVD a unique and powerful tool in the non-invasive, automated detection of CVD risk.