A Mayo Clinic study finds that applying artificial intelligence (AI) to a widely available, inexpensive test – the electrocardiogram (EKG) – results in a simple, affordable early indicator of asymptomatic left ventricular dysfunction, which is a precursor to heart failure. The research team found that the AI/EKG test accuracy compares favorably with other common screening tests, such as mammography for breast cancer. The findings were published in Nature Medicine.
Asymptomatic left ventricular dysfunction is characterized by the presence of a weak heart pump with a risk of overt heart failure. It affects 7 million Americans, and is associated with reduced quality of life and longevity. But asymptomatic left ventricular dysfunction is treatable when identified.
However, there is no inexpensive, noninvasive, painless screening tool for asymptomatic left ventricular dysfunction available for diagnostic use. The Mayo study reports that the best existing screening test for asymptomatic left ventricular dysfunction is to measure natriuretic peptide levels (BNP), but results of BNP have been disappointing. And the test requires blood draws. Left ventricular dysfunction typically is diagnosed with expensive and less accessible imaging tests, such as echocardiograms, or CT or MRI scans.
“Congestive heart failure afflicts more than 5 million people and consumes more than $30 billion in health care expenditures in the U.S. alone,” says Paul Friedman, M.D., senior author and chair of the Midwest Department of Cardiovascular Medicine at Mayo Clinic. “The ability to acquire an ubiquitous, easily accessible, inexpensive recording in 10 seconds – the EKG – and to digitally process it with AI to extract new information about previously hidden heart disease holds great promise for saving lives and improving health,” he says.