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A simple routine eye test can predict the risk of heart attacks, says a new study

A simple routine eye test can predict the risk of heart attacks, says a new study
Science2 min read
  • The pattern of blood vessels obtained from the retina image can give a tell-tale sign of a heart attack.
  • Researchers say the tests will allow doctors to cut the danger of heart attack at an early stage.
  • The used model to analyse retinal images is much more effective when compared to current screening methods.
With the rise in the number of heart-related diseases, the need to keep the heart healthy seems to have come to the fore. Several studies are also coming up suggesting new ways to diagnose the risk of a heart attack at an early stage.

In one such study, researchers have found that a simple, non-invasive eye examination can predict the risk of a heart attack.

According to researchers, the combined information about the pattern of blood vessels in the retina combined with traditional clinical factors enables them to identify the risk of a heart attack. The researchers used data from the UK Biobank of 500,000 people. Data were combined in a model with factors such as age, blood pressure, sex, body mass index, and smoking status along with retinal images of people with myocardial infarction (MI) a type of heart attack.

The model was able to predict the risk of heart attack effectively when compared to current screening methods.

The findings of the new study were presented at the annual conference of the European Society of Human Genetics. The chairman of the conference, Alexandre Reymond said, “This study demonstrates the importance of implementing prevention now and how personalised health is providing us with the tools to do so.”

PhD student at Roslin institutes at the University of Edinburgh and the presenting author of the study, Ana Villaplana-Velasco said, “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.”

These findings may be also useful in identifying other ocular and systemic diseases such as stroke and diabetic retinopathy as every condition may have a retinal variation profile.

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