Enhancing Prediction of Adverse Pregnancy Outcomes in Africa Through Partnerships and Innovation
Pregnancy complications such as pre-eclampsia (high blood pressure during pregnancy), poor fetal growth, unexplained stillbirth, and spontaneous preterm birth are major causes of illness and death for mothers and babies in sub-Saharan Africa. These conditions, known as the Great Obstetrical Syndromes, are thought to result from problems with the development of the placenta early in pregnancy. However, there is limited information from African populations to help identify women at risk or improve prevention and treatment. This study will enroll 4,000 first-time pregnant women in Uganda before 18 weeks of pregnancy and follow them throughout pregnancy until delivery. Participants will attend routine study visits where information about their health, pregnancy, and social circumstances will be collected. Physical examinations, ultrasound scans, and blood samples will be obtained at several time points during pregnancy, and blood and placental samples will be collected at birth. Some samples will be analyzed during the study, while others will be stored for future research with appropriate ethical approval. The study will examine which clinical, biological, and social factors are associated with pregnancy complications. Researchers will use statistical methods and artificial intelligence (AI) techniques to identify patterns that may help predict which women are at increased risk of developing these conditions. The knowledge gained from this study may support the development of better screening tools and strategies for preventing pregnancy complications, improve maternal and newborn health outcomes in Uganda and other African settings, and establish a valuable biobank to support future maternal and newborn health research.
Viable singleton pregnancy at the time of the dating ultrasound scan [+5]