Using machine learning to predict heart disease risk in women with pregnancy complications
Official title: Leveraging machine learning for cardiovascular disease risk prediction and prevention in women with a history of adverse pregnancy outcomes
Funded at Brigham and Women's Hospital · NIH-10996161 · Data updated 2026-11-12
This study is looking to help women who have had tough pregnancies by figuring out which ones might be more likely to have heart problems later on, so doctors can give them the right support and care they need.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Brigham and Women's Hospital NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | December 15, 2023 |
| Project end | November 30, 2027 |
| Funding year | 2025 |
| Award (this year) | $741,241 |
| NIH project number | 5R01HL167960-02 |
| Project ID | NIH-10996161 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are women who have experienced adverse pregnancy outcomes such as preeclampsia, gestational diabetes, or preterm delivery.
✕Less likely to help
Patients who have not experienced any adverse pregnancy outcomes or who do not have a history of cardiovascular disease may not benefit from this research.
What this research studies
This research aims to identify women who have experienced adverse pregnancy outcomes (APOs) and are at a higher risk for cardiovascular disease (CVD) later in life. By leveraging machine learning techniques, the study will analyze various factors such as individual APOs, delivery complications, and maternal demographics to create a risk classification system. This system will help healthcare providers better understand which women need closer monitoring and intervention after experiencing an APO. The goal is to develop a clinical decision support tool that can guide care and improve health outcomes for these women.
Why it matters
Potential benefit: If successful, this research could lead to improved risk assessment and prevention strategies for cardiovascular disease in women with a history of adverse pregnancy outcomes.
How similar studies have gone: Other research has shown promise in using machine learning for risk prediction in various health conditions, suggesting that this approach could be effective in this context as well.
Where this research is happening
-
Brigham and Women's Hospital
Boston, United States Active
Researchers
- Principal investigator: Rich-Edwards, Janet W — Brigham and Women's Hospital
- Study coordinator: Rich-Edwards, Janet W
Related research
Other NIH-funded projects on the same topics.
-
Pregnancy complications and women's long-term heart health
This project looks at whether complications during pregnancy predict higher risk of heart and blood vessel disease later in life for women.
-
Cardiovascular Risk in at-risk Hispanic women after pregnancy complications
We’re studying how pregnancy challenges in Hispanic women relate to heart and mental health later in life, to help identify who’s at higher risk and what care they might need.
-
Connecting women with pregnancy high blood pressure to heart-health care after birth
This project looks at how health care systems help or block women who had high blood pressure during pregnancy from getting heart-health care after delivery.
-
Finding women at risk for heart disease after pregnancy complications
This project uses machine learning to find which women who had pregnancy complications are most likely to develop heart disease so they can get earlier follow-up and prevention.
-
Pregnancy outcomes and heart health after pregnancy
Looks at how pregnancy problems like high blood pressure, early delivery, or having a small baby relate to hidden heart and blood vessel changes during and after pregnancy.
-
Heart and metabolic health after pregnancy complications in Puerto Rican women
This project looks at how pregnancy complications and mood during pregnancy relate to heart, diabetes, and mental health years later for Puerto Rican women.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.