Artificial intelligence guided screening for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial
Authors: Demilade A. Adedinsewo, Andrea Carolina Morales-Lara, Bosede B. Afolabi, Oyewole A. Kushimo, Amam C. Mbakwem, Kehinde F. Ibiyemi, James Ayodele Ogunmodede, Hadijat Olaide Raji, Sadiq H. Ringim, Abdullahi A. Habib, Sabiu M. Hamza, Okechukwu S. Ogah, Gbolahan Obajimi, Olugbenga Oluseun Saanu, Olusoji E. Jagun, Francisca O. Inofomoh, Temitope Adeolu, Kamilu M. Karaye, Sule A. Gaya, Isiaka Alfa, Cynthia Yohanna, K. L. Venkatachalam, Jennifer Dugan, Xiaoxi Yao, Hanna J. Sledge, Patrick W. Johnson, Mikolaj A. Wieczorek, Zachi I. Attia, Sabrina D. Phillips, Mohamad H. Yamani, Yvonne Butler Tobah, Carl H. Rose, Emily E. Sharpe, Francisco Lopez-Jimenez, Paul A. Friedman, Peter A. Noseworthy, Rickey E. Carter
Journal: Nature Medicine (2024)

Nigeria has the highest reported incidence of peripartum cardiomyopathy worldwide. This open-label, pragmatic clinical trial randomized pregnant and postpartum women to usual care or artificial intelligence (AI)-guided screening to assess its impact on the diagnosis left ventricular systolic dysfunction (LVSD) in the perinatal period. The study intervention included digital stethoscope recordings with point of-care AI predictions and a 12-lead electrocardiogram with asynchronous AI predictions for LVSD. The primary end point was identification of LVSD during the study period. In the intervention arm, the primary end point was defined as the number of identified participants with LVSD as determined by a positive AI screen, confirmed by echocardiography. In the control arm, this was the number of participants with clinical recognition and documentation of LVSD on echocardiography in keeping with current standard of care. Participants in the intervention arm had a confirmatory echocardiogram at baseline for AI model validation. A total of 1,232 (616 in each arm) participants were randomized and 1,195 participants (587 intervention arm and 608 control arm) completed the baseline visit at 6 hospitals in Nigeria between August 2022 and September 2023 with follow-up through May 2024. Using the AI-enabled digital stethoscope, the primary study end point was met with detection of 24 out of 587 (4.1%) versus 12 out of 608 (2.0%) patients with LVSD (intervention versus control odds ratio 2.12, 95% CI 1.05–4.27; P = 0.032). With the 12-lead AI-electrocardiogram model, the primary end point was detected in 20 out of 587 (3.4%) versus 12 out of 608 (2.0%) patients (odds ratio 1.75, 95% CI 0.85–3.62; P = 0.125). A similar direction of effect was observed in prespecified subgroup analysis. There were no serious adverse events related to study participation. In pregnant and postpartum women, AI-guided screening using a digital stethoscope improved the diagnosis of pregnancy-related cardiomyopathy. ClinicalTrials.gov registration: NCT05438576 In this pragmatic, randomized clinical trial involving 1,196 pregnant and postpartum women from 6 hospitals in Nigeria, AI-based electrocardiogram screening proved accurate in detecting cardiomyopathies and suggests that it could improve detection of these conditions.