Washington D.C. [USA]: Artificial intelligence (AI) enabled electrocardiogram (EKG) can detect recent atrial fibrillation that occurred without symptoms or that is impending, potentially improving treatment options, suggests a study.
The study published in the journal of ‘The Lancet’ could improve the efficiency of the EKG, a noninvasive and widely available method of heart disease screening.
Accuracy and timeliness are important in making an atrial fibrillation diagnosis. Left undetected, atrial fibrillation can cause stroke, heart failure, and other cardiovascular diseases. Knowing that a patient has atrial fibrillation helps direct treatment with blood thinners, noted Paul Friedman, senior author of the study.
“When people come in with a stroke, we really want to know if they had AF in the days before the stroke, because it guides the treatment,” said Dr Friedman.
“Blood thinners are very effective for preventing another stroke in people with AF. But for those without AF, using blood thinners increases the risk of bleeding without substantial benefit. That is important knowledge. We want to know if a patient has AF.”
Using approximately 450,000 EKGs of the over 7 million EKGs in the Mayo Clinic digital data vault, researchers trained AI to identify subtle differences in a normal EKG that will indicate changes in heart structure caused by atrial fibrillation. These changes are not detectable without the use of AI.
Researchers then tested the AI on normal-rhythm EKGs from a group of 36,280 patients, of whom 3,051 were known to have atrial fibrillation. The AI-enabled EKG correctly identified the subtle patterns of atrial fibrillation with 90 per cent accuracy.
Dr Friedman said that he is surprised by the findings of this research. If proven out, he said, AI-guided EKGs could direct the right treatment for disease caused by atrial fibrillation, even without symptoms. Moreover, this technology can be processed using a smartphone or watch, making it readily available on a large scale.
“An EKG will always show the heart’s electrical activity at the time of the test, but this is like looking at the ocean now and being able to tell that there were big waves yesterday,” said Dr Friedman.
“AI can provide powerful information about the invisible electrical signals that our bodies give off with each heartbeat — signals that have been hidden in plain sight.”
(This story has been published from a wire agency feed without modifications to the text.)