Heart failure during pregnancy is a dangerous and often underdetected condition because common symptoms—shortness of breath, extreme fatigue, and difficulty breathing when lying down—are easily mistaken for typical pregnancy discomforts. Breaking research presented at the European Society of Cardiology Congress on a Mayo Clinic study showed that an artificial intelligence (AI)-enabled digital stethoscope helped doctors identify twice as many cases of heart failure compared with a control group that received usual obstetric care and screening. Full results of the study are published in Natural medicine.
The trial was conducted in Nigeria, where more women suffer from pregnancy-related heart failure than anywhere else in the world. The results also indicate that screening tests involving the AI-powered digital stethoscope were 12 times more likely than traditional screening tests to detect heart pump weakness when assessed against an ejection fraction threshold of less than 45%, which is the cutoff value indicating a specific type of heart failure called peripartum cardiomyopathy.
“Recognizing this type of heart failure early is important for the mother’s health and well-being,” says Demilade Adedinsewo, M.D., a Mayo Clinic cardiologist and lead researcher on the study. “Symptoms of peripartum cardiomyopathy can get progressively worse as the pregnancy progresses or, more commonly, after delivery, and can be life-threatening for the mother if her heart becomes too weak. Medications can help 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 disease using either routine obstetric care or AI-enhanced solutions. Mayo Clinic researchers previously developed a basic 12-lead electrocardiogram (ECG) algorithm using AI to predict a weak heart pump, clinically known as low ejection fraction. Eko Health further improved a version of this algorithm for its point-of-care digital stethoscope, which has U.S. Food and Drug Administration (FDA) approval to detect heart failure with low ejection fraction.
Researchers found that physicians using the AI-based screening system with the digital stethoscope and 12-lead ECG detected weak heart function with high accuracy. Within the study cohort, the digital stethoscope helped detect twice as many cases of low ejection fraction <50%, and physicians using it were 12 times more likely to identify an ejection fraction <45% compared with usual care.
The AI-supported tools were evaluated at three different levels of ejection fraction used in clinical diagnosis. Less than 45% is the cutoff for diagnosing peripartum cardiomyopathy. Less than 40% indicates heart failure with reduced ejection fraction and has strong evidence in favor of specific medications to reduce symptoms and risk of death. An ejection fraction of less than 35% indicates severely low heart pumping function that often requires more intensive treatment, including advanced heart failure therapies and an implantable defibrillator if pumping function does not recover. Patients in the intervention group underwent an echocardiogram at study entry to confirm the AI predictions.
“This study provides evidence that we can better detect peripartum cardiomyopathy among women in Nigeria. However, there are more questions to be answered,” says Dr. Adedinsewo. “Our next steps would be to evaluate the usability and adoption of this tool by Nigerian healthcare providers (including physicians and nurses) and, more importantly, its impact on patient care. Peripartum cardiomyopathy affects approximately 1 in 2,000 women in the US and 1 in 700 African American women. Evaluating this AI tool in the US will allow further testing of its capabilities in diverse populations and healthcare settings.”
Funding for this clinical trial includes Mayo Clinic (Centers for Digital Health and Community Engagement and Health Research), the Mayo Clinic Program to Develop Interdisciplinary Research Careers in Women’s Health (BIRCWH), funded by the National Institutes of Health (NIH), and the Mayo Clinic Center for Clinical and Translational Sciences (CCATS), funded by the NIH.