Scientists find a better way to predict heart disease

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In a new study from the University of Utah, researchers found that artificial intelligence could lead to better ways to predict the onset and course of cardiovascular disease.

They developed unique computational tools to precisely measure the synergistic effects of existing medical conditions on the heart and blood vessels.

The researchers say this comprehensive approach could help physicians foresee, prevent, or treat serious heart problems, perhaps even before a patient is aware of the underlying condition.

In the study, the team used machine learning software to sort through more than 1.6 million electronic health records (EHRs) after names and other identifying information were deleted.

They used a form of artificial intelligence called probabilistic graphical networks (PGM) to calculate how any combination of these comorbidities could influence the risks associated with heart transplants, congenital heart disease, or sinoatrial node dysfunction (SND, a disruption or failure of the heart’s natural pacemaker).

Among adults, the researchers found that:

Individuals who had a prior diagnosis of cardiomyopathy (disease of the heart muscle) were at 86 times higher risk of needing a heart transplant than those who didn’t.

Those who had viral myocarditis had about a 60 times higher risk of requiring a heart transplant.

Usage of milrinone, a vasodilating drug used to treat heart failure, pushed the transplant risk 175 times This was the strongest individual predictor of a heart transplant.

Comorbidities had a significantly different influence on the transplant risk among children.

Overall, the risk of pediatric heart transplant ranged from 17 to 102 times higher than children who didn’t have pre-existing heart conditions, depending on the underlying diagnosis.

The researchers also examined the influences that a mother’s health during pregnancy had on her children.

Women who had high blood pressure during pregnancy were about twice as likely to give birth to infants who had congenital heart and circulatory problems.

Children with Down syndrome had about three times greater risk of having a heart anomaly.

Researchers believe this research could lead to the development of a practical clinical tool for patient care.

If you care about heart health, please read studies about high blood pressure drugs that could increase heart failure risk, and combo therapy that could cut risk of heart attack and stroke by half.

For more information about heart health, please see recent studies about simple way to reduce irregular heartbeat, and results showing this hormone may reduce irregular heartbeat, inflammation.

The study is published in PLOS Digital Health. One author of the study is Martin Tristani-Firouzi, M.D.

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