Heart failure while pregnant is a dangerous and sometimes under-detected condition because common symptoms — shortness of breath, extreme fatigue and trouble respiration while lying down — are easily mistaken for typical pregnancy discomforts. Late-breaking research presented on the European Society of Cardiology Congress on a Mayo Clinic study showed a man-made intelligence (AI)-enabled digital stethoscope helped doctors discover twice as many cases of heart failure in comparison with a control group that received usual obstetric care and screening. Full study findings are published in Nature Medicine.
The trial was conducted in Nigeria, where more women experience pregnancy-related heart failure than anywhere on this planet. The outcomes also indicate that screening including the AI-enabled digital stethoscope were 12-times more likely than traditional screening to flag heart pump weakness when evaluated at a ejection fraction threshold lower than 45%, which is the cutoff indicating a selected style of heart failure called peripartum cardiomyopathy.
“Recognizing the sort of heart failure early is very important to the mother’s health and well-being,” says Demilade Adedinsewo, M.D., a cardiologist at Mayo Clinic and lead investigator of the study. “The symptoms of peripartum cardiomyopathy can get progressively worse as pregnancy advances, or more commonly following childbirth, and might endanger the mother’s life if her heart becomes too weak. Medicines can assist when the condition is identified but severe cases may require intensive care, a mechanical heart pump, or sometimes a heart transplant, if not controlled with medical therapy.”
The randomized, controlled, open-label clinical trial included nearly 1,200 participants who were screened for heart conditions through typical obstetric care or AI-enhanced solutions. Mayo Clinic researchers previously developed a foundational 12-lead AI-electrocardiogram (ECG) algorithm to predict a weak heart pump, clinically often called low ejection fraction. A version of this algorithm was further enhanced by Eko Health for its point-of-care digital stethoscope which is U.S. Food and Drug Administration (FDA)-cleared to detect heart failure with low ejection fraction.
The researchers found that doctors using AI-based screening with the digital stethoscope and 12-lead ECG detected weak heart function with high accuracy. Inside the study cohort, the digital stethoscope helped flag twice as many cases of low ejection fraction <50% and doctors using it were 12-times more more likely to discover an ejection fraction <45% as in comparison with usual care.
The AI-supported tools were evaluated at three different levels of ejection fraction utilized in clinical diagnosis. Lower than 45% is the cut point for diagnosing peripartum cardiomyopathy. Lower than 40% indicates heart failure with reduced ejection fraction and has strong evidence in favor of specific medications to cut back symptoms and the chance of death. An ejection fraction of lower than 35% signals severely low heart pump function that always requires more intense management, including advanced heart failure therapies and an implantable defibrillator if pump function doesn’t get well. Patients within the intervention group each had an echocardiogram at study entry to supply confirmation of the AI-predictions.
“This study provides evidence that we are able to higher detect peripartum cardiomyopathy amongst women in Nigeria. Nevertheless, there are more inquiries to be answered,” says Dr. Adedinsewo. “Our next steps can be to guage usability and adoption of this tool by Nigerian healthcare providers (including doctors and nurses) and importantly, its impact on patient care. Peripartum cardiomyopathy affects roughly 1 in 2,000 women throughout the U.S. and as many as 1 in 700 African American women. Evaluating this AI tool within the U.S. will further test its abilities in varied populations and healthcare settings.”
Funding for this clinical trial includes Mayo Clinic (Centers for Digital Health and Community Health and Engagement Research), the Mayo Clinic Constructing Interdisciplinary Research Careers in Women’s Health (BIRCWH) Program funded by the National Institutes of Health (NIH), and Mayo Clinic’s Center for Clinical and Translational Sciences (CCATS) funded by the NIH.
