NIH announces winners of data challenge to identify risk factors for first-time pregnancies

Tuesday, December 7, 2021

NIH announces winners of data challenge to identify risk factors for first-time pregnancies

The winners of the 2023 蜜芽传媒鈥檚 were announced today in conjunction with the White House 鈥渄ay of action鈥 on maternal health. Twelve prizes were awarded to seven winners who proposed innovative solutions to identify risk factors in first-time pregnancies. Without a prior pregnancy for comparison, it is difficult to identify risks for adverse pregnancy outcomes. Early detection of these risks can help reduce pregnancy complications and prevent maternal deaths.

鈥淎ny maternal death is one too many,鈥 said Diana W. Bianchi, M.D., director of NIH鈥檚 Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), which administered the challenge. 鈥淎 healthy pregnancy and childbirth should be a given, but sadly, it鈥檚 not. Understanding and reducing pregnancy-related complications and deaths 鈥 or maternal morbidity and mortality 鈥 is a high priority for NIH.鈥

In the United States, more than 700 women die each year from pregnancy complications or giving birth, according to the Centers for Disease Control and Prevention. Another 50,000 women experience life-threatening complications that are considered 鈥渘ear misses鈥 for maternal death, sometimes causing serious, long-term health problems. The that Black women are three times more likely to die from a pregnancy-related cause than white women. Women over age 35 years or those residing in rural areas are also at higher risk.

Last year, in research funding to prevent maternal morbidity and mortality. While most of these funds went toward traditional funding mechanisms, challenges offer unique opportunities to stimulate ideas and solutions. The Decoding Maternal Morbidity Data Challenge prizes totaled $400,000. Seven prizes of $50,000 were awarded for innovation, and five additional prizes of $10,000 were awarded for addressing health disparities.

All the proposals analyzed participant data from NICHD鈥檚 , a racially, ethnically and geographically diverse sample of people who are pregnant for the first time. NuMoM2b was established in 2010 and has compiled data on more than 10,000 pregnant women, including research data beginning in the sixth week of pregnancy and continuing through delivery. 

鈥淭he winning teams developed methods to analyze the data, accurately flagging cases that were high-risk for complications,鈥 said NICHD鈥檚 Maurice Davis, D.H.A., who managed the challenge. 鈥淭hese computational methods can now be used to analyze additional data from other pregnancies. These solutions have the potential to make a real difference and save lives.鈥

The team leads for each of the winning proposals are as follows (asterisks denote winners of both prize categories):

Nicole Carlson, Ph.D.*
Emory University, Atlanta

Ali Ebrahim, Ph.D
Delfina, San Francisco

Britnee Johnston*
Johnston and Company, LLC, Salt Lake City

Monica Keith, Ph.D.*
University of Washington, Seattle

Yaping Li
Feng Ya, LLC, Watkinsville, Georgia

Ainesh Pandey*
IBM Data Science and AI Elite, San Francisco

Ansaf Salleb-Aouissi, Ph.D.
Columbia University, New York City

For more information about the challenge and a list of all team members, please visit: .

About the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): NICHD leads research and training to understand human development, improve reproductive health, enhance the lives of children and adolescents, and optimize abilities for all. For more information, visit .

About the 2023 蜜芽传媒 (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov.

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