Heart failure during pregnancy is a dangerous condition that is often overlooked due to symptoms that can be mistaken for typical pregnancy discomforts. A new study conducted by Mayo Clinic in Nigeria, a country where pregnancy-related heart failure is more prevalent than anywhere else in the world, utilized an artificial intelligence (AI)-enabled digital stethoscope to improve detection rates. The study found that the use of AI-based screening methods identified twice as many cases of heart failure compared to traditional obstetric care and screening methods. The AI-enabled digital stethoscope was particularly successful in flagging cases of heart pump weakness related to peripartum cardiomyopathy, a specific type of heart failure that can be life-threatening if not detected and treated early.
The study included nearly 1,200 participants who were randomly assigned to receive screening through either traditional obstetric care or AI-enhanced solutions. Mayo Clinic researchers had previously developed an AI-electrocardiogram (ECG) algorithm to predict weak heart pump function, which was further enhanced by Eko Health for use with their digital stethoscope. The results of the study showed that doctors using AI-based screening with the digital stethoscope and ECG were able to detect weak heart function with high accuracy, particularly in cases of low ejection fraction. The AI-enabled tools were able to identify cases with low ejection fraction at three different levels, providing valuable information for diagnosing and treating heart failure during pregnancy.
Peripartum cardiomyopathy can worsen as pregnancy progresses or following childbirth, putting the mother’s health and life at risk if left untreated. While medications can help manage the condition, severe cases may require intensive care, a mechanical heart pump, or even a heart transplant. The study conducted in Nigeria aimed to evaluate the effectiveness of AI-based screening methods in improving the detection of peripartum cardiomyopathy, with promising results that suggest the potential for early intervention and improved outcomes for affected women. The use of AI tools in healthcare settings can help address critical issues such as under-detection of heart failure during pregnancy.
The findings of the study highlight the potential benefits of using AI-enabled digital stethoscopes in improving the detection of heart failure during pregnancy, particularly in high-risk populations such as those in Nigeria. The next steps for researchers will include evaluating the usability and adoption of these tools by healthcare providers in Nigeria and assessing the impact on patient care. Peripartum cardiomyopathy affects a significant number of women, particularly African American women, and early detection is crucial for improving outcomes and survival rates. By further testing AI tools in diverse populations and healthcare settings, researchers aim to validate their effectiveness and potential for widespread adoption in clinical practice.
Funding for the clinical trial was provided by Mayo Clinic, the NIH-funded BIRCWH Program, and Mayo Clinic’s Center for Clinical and Translational Sciences. The study has implications for improving the detection and management of heart failure during pregnancy, highlighting the potential of AI technologies in enhancing healthcare outcomes. With further research and implementation in varied populations, AI-enabled tools such as digital stethoscopes have the potential to revolutionize the way heart conditions are detected and treated, ultimately improving maternal health and reducing the risk of life-threatening complications during pregnancy.
