Research & Development

Simple eye exam could predict heart attack risk

Researchers have found that patterns of blood vessels in the retina could help identify individuals at risk of experiencing cardiac problems, according to The Guardian.
The researchers were able to identify participants’ myocardial infarction (MI) through a simple, noninvasive eye examination, combined with other information.
A heart attack, or MI, is a serious medical emergency in which the blood supply to the heart is suddenly blocked, usually by a blood clot. It is classified as a medical emergency.
The study revealed that variations in vascular patterns in the retina can imply the development of coronary heart disease. This disease is a precursor to a heart attack.
“The calculation of an individualised MI risk from those over 50 years old would seem to be appropriate,” said Villaplana-Velasco. “This would enable doctors to suggest behaviours that could reduce risk, such as giving up smoking, and maintaining normal cholesterol and blood pressure.”
The researchers used data from UK Biobank, a large-scale biomedical database and research resource, which contains the records of 500,000 people’s medical and lifestyle records, to calculate a measure known as fractal dimension. This data was then combined in a model with factors such as age, sex, systolic blood pressure, body mass index, and smoking status. The researchers studied those on the database who had experienced a heart attack after their retinal images had been collected. They commented that their model achieved its best predictive performance, over five years before the heart attack occurred. Ana Villaplana-Velasco, a PhD student at the Usher and Roslin institutes at the University of Edinburgh, UK, and the presenting author of the study, shared the following insight with The Guardian: “Strikingly, we discovered that our model was able to better classify participants with low or high MI risk in UK Biobank, when compared with established models that only include demographic data. The improvement of our model was even higher if we added a score related to the genetic propensity of developing MI.”