Prediction of Pregnancy-Related Cardiovascular Outcomes Using Electrocardiogram-Based Deep Learning Estimation of Cardiorespiratory Fitness
BACKGROUND: from the resting 12-lead electrocardiogram (ECG). OBJECTIVES: with incident pregnancy-related CV complications. METHODS: with pregnancy-related CV complications up to 1 year postpartum (severe hypertensive disorders of pregnancy, major adverse cardiac events, and maternal death). RESULTS: had 61% greater odds of CV complications than the highest quartile (OR: 1.61; 95% CI: 1.13-2.30; P = 0.008). CONCLUSIONS: Lower ECG-estimated cardiorespiratory fitness was associated with a higher risk of pregnancy-related CV complications, supporting artificial intelligence-enabled ECG analysis as a scalable tool for antepartum risk stratification of pregnancy-related CV complications.
Authors
- Jennifer E. Ho (ORCID: https://orcid.org/0000-0002-7987-4768)
- James Sawalla Guseh (ORCID: https://orcid.org/0000-0003-0992-5635)
- Katherine E. Economy (ORCID: https://orcid.org/0000-0001-6359-0739)
- Mahnaz Maddah (ORCID: https://orcid.org/0000-0002-9837-6000)
- Logan Brown
- Danielle Pace
- Timothy Churchill
- Emily S. Lau (ORCID: https://orcid.org/0000-0001-9361-6397)
- Yunong Zhao
- Shaan Khurshid
- Kaitlyn James
- Valentina D’Souza
- Camille Powe
- Patrick T. Ellinor
Institutions
- Broad Institute (US)
- Brigham and Women's Hospital (US)
- Beth Israel Deaconess Medical Center (US)
- Beth Israel Deaconess Hospital (US)
- Massachusetts General Hospital (US)
- Massachusetts Institute of Technology (US)
Publication Details
- Journal
- JACC Advances
- Published
- 2026-04-24
- DOI
- https://doi.org/10.1016/j.jacadv.2026.102764
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- American Heart Association
- Massachusetts Life Sciences Center
- Fondation Leducq
- National Institutes of Health
- Caltech Conte Center for Social Decision Making