Low cost device for early detection of Heart Failure developed
According to a new study, a low-cost device for early detection of Heart Failure can be developed by application of Artificial Intelligence to electrocardiogram (EKG). It is a ubiquitous, low-cost test that permits the EKG to serve as a powerful screening tool in asymptomatic individuals to identify asymptomatic left ventricular dysfunction (ALVD), a precursor to heart failure. The findings of the study have been published in the journal Nature Medicine.
Asymptomatic left ventricular dysfunction (ALVD) is present in 3–6% of the general population and associated with reduced quality of life and longevity but is treatable when found.
“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, MD., senior author and chair of the Midwest Department of Cardiovascular Medicine at Mayo Clinic. "The ability to acquire a 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.
However, there is no inexpensive, noninvasive, painless screening tool for asymptomatic left ventricular dysfunction available for diagnostic use. The Mayo study reported 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
The researchers at the Mayo Clinic tested the hypothesis that the application of artificial intelligence (AI) to the electrocardiogram (ECG), a routine method of measuring the heart’s electrical activity, could identify ALVD.
Using Mayo Clinic stored digital data, 625,326 paired EKG and transthoracic echocardiograms were screened to identify the population to be studied for analysis. To test their hypothesis, researchers created, trained, validated and then tested a neural network.
The study found that AI applied to a standard EKG reliably detects asymptomatic left ventricular dysfunction. The accuracy of the AI/EKG test compares favorably with other common screening tests, such as a prostate-specific antigen for prostate cancer, mammography for breast cancer and cervical cytology for cervical cancer.
Moreover, in patients without ventricular dysfunction, those with a positive AI screen were at four times the risk of developing future ventricular dysfunction, compared with those with a negative screen.
“In other words, the test not only identified the asymptomatic disease but also predicted the risk of future disease, presumably by identifying very early, subtle EKG changes that occur before heart muscle weakness,” said Dr. Friedman.
For full information log on to https://www.nature.com/articles/s41591-018-0240-2