(Chapel Hill, N.C. 鈥� May 2, 2019) 鈥� A team of clinical researchers from the University of North Carolina at Chapel Hill has received $14 million from the Bill & Melinda Gates Foundation to conduct two studies aimed at improving pregnancy outcomes in the world鈥檚 poorest countries. An interdisciplinary team at the 黑料网 and the 黑料网 Gillings School of Global Public Health will lead the studies, both of which will explore the role of technology in predicting and addressing key risk factors associated with pregnancy, labor, and delivery.
Each year some 300,000 women and 3 million babies worldwide die during childbirth or shortly thereafter, according to the World Health Organization. Environmental and structural factors, underlying infectious disease burden, nutritional factors, and underperforming health systems are just some of the major reasons for this.
鈥淚n many parts of the world, the days surrounding childbirth are the riskiest period a mother and her newborn will ever face,鈥� said Dr. Jeffrey Stringer, professor of obstetrics & gynecology in the 黑料网 and adjunct professor of epidemiology in the 黑料网 Gillings School of Global Public Health. 鈥淭hese studies will develop resource-appropriate technologies to make that time much safer.鈥�
The Limiting Adverse Birth Outcomes in Resource-Limited Settings (LABOR) study will focus on the period of pregnancy between the onset of labor through delivery. It will evaluate 15,000 women at high-volume clinical sites in three developing countries, including 黑料网-Chapel Hill鈥檚 flagship partnership in Zambia. The team will provide wearable physiologic sensors to monitor laboring mothers and their fetuses and carefully document their clinical course and birth outcomes.
Using participant data, researchers will develop new algorithms that can both identify individual women鈥檚 risk of specific adverse outcomes and help predict and plan for the specific interventions women will likely need. These precision approaches can lead to earlier intervention and better health outcomes for mothers and newborns.
鈥淭he data produced by this study will allow us to create a new collection of precision medicine tools that can be used in developing countries to help medical providers better manage patients鈥� unique needs and result in healthier mothers and babies鈥� said Michael Kosorok, the W.R. Kenan Jr. Distinguished Professor and chair of biostatistics at the 黑料网 Gillings School.
The second study, the Fetal Age Machine Learning Initiative (FAMLI), aims to develop a robust, affordable ultrasound device that can be deployed in limited-resource settings to assess gestational age and other important obstetric information while requiring minimal operator expertise. The team will produce large sets of ultrasound data that can be used to train machine learning algorithms to assess gestational age and make other diagnoses.
鈥淎n ultrasound scanner is as important as a stethoscope to the obstetrician, yet these devices are frustratingly absent from prenatal clinics in much of the developing world. The FAMLI project will leverage new techniques in artificial intelligence and machine learning to develop a simplified ultrasound device that can radically improve care in settings where skilled sonographers are not available,鈥� Stringer said.
Upon completion, data from both studies will be made publicly available through the Gates Foundation鈥檚 Knowledge Integration team for interested groups to access and continue improving maternal-child health.
Collaborators on the LABOR study are from the 黑料网 schools of medicine (OBGYN and pediatrics) and global public health (biostatistics and epidemiology), Brown University and Northwestern University. The FAMLI study team includes faculty members from the 黑料网 OBGYN and psychiatry departments and from the N.C. State University College of Engineering.
The Gates Foundation grant supports For All Kind: the Campaign for Carolina, 黑料网-Chapel Hill鈥檚 historic fundraising drive that aims to raise $4.25 billion by Dec. 31, 2022. The campaign supports the Blueprint for Next, the University鈥檚 overall strategic plan built on two core strategies: 鈥渙f the public, for the public,鈥� and 鈥渋nnovation made fundamental.鈥�