New Study Shows Routine Eye-Retina Scanning Can Show Risk Of Coronary Artery Disease

A quick eye test can detect heart attacks by five years earlier before they occur, according to a new study. According to researchers, abnormal blood vessel patterns in the retina are a symptom of coronary artery disease.

A routine eye exam can show individuals at risk of coronary artery disease

The study gives hope for identifying people who are most in danger during regular eye exams. Long before a probable sudden death, healthier habits like improved diets and increased exercise would be advised, as well as cholesterol-lowering statins or other medications.

Lead author and Post-doctoral student at the University of Edinburg Ana Villaplana-Velasco said, “This would enable doctors to suggest behaviors that could reduce risks, such as giving up smoking and maintaining normal cholesterol and blood pressure.”

A small membrane in the back of the eye called the retina contains light-sensitive cells. As people get older, they start to deteriorate.

According to Villaplana-Velasco, They previously recognized that differences in the retina’s vasculature could provide insights into human health. Since retinal scanning is a non-invasive procedure, researchers decided to look into the potential health advantages of these images.

The UK Biobank database, which contains more than 500,000 Britons’ health records and other information, served as the basis for the conclusions.

Researchers computed fractal dimension  to evaluate retinal vasculatur patterns 

First, researchers computed a parameter called fractal dimension (Df) to investigate the branching characteristics of the retinal vasculatur. According to Villaplana-Velasco, they discovered that reduced Df, simpler vessel branching topologies, is connected to coronary heart disease and, subsequently, heart attack.

Following the collection of participants’ retinal scans, the Scottish team created a customized “prediction model” using participants who had experienced a heart attack. Df was integrated with conventional clinical variables such as sex, age, BMI, blood pressure, and smoking history.

Surprisingly, when compared to existing models that just take into account demographic information, researchers found that their model was able to categorize individuals with high or low heart attack risk more accurately. If they included a score for the genetic tendency of having a heart attack, the model’s improvement was significantly greater.

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