The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) Network's first protocol: deep phenotyping in three sub-Saharan African countries.

BACKGROUND: The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) Network is a new and broadly-based group of research scientists and health advocates based in the UK, Africa and North America. METHODS: This paper describes the protocol that underpins the clinical research activity of the Network, so that the investigators, and broader global health community, can have access to 'deep phenotyping' (social determinants of health, demographic and clinical parameters, placental biology and agnostic discovery biology) of women as they advance through pregnancy to the end of the puerperium, whether those pregnancies have normal outcomes or are complicated by one/more of the placental disorders of pregnancy (pregnancy hypertension, fetal growth restriction and stillbirth). Our clinical sites are in The Gambia (Farafenni), Kenya (Kilifi County), and Mozambique (Maputo Province). In each country, 50 non-pregnant women of reproductive age will be recruited each month for 1 year, to provide a final national sample size of 600; these women will provide culturally-, ethnically-, seasonally- and spatially-relevant control data with which to compare women with normal and complicated pregnancies. Between the three countries we will recruit ≈10,000 unselected pregnant women over 2 years. An estimated 1500 women will experience one/more placental complications over the same epoch. Importantly, as we will have accurate gestational age dating using the TraCer device, we will be able to discriminate between fetal growth restriction and preterm birth. Recruitment and follow-up will be primarily facility-based and will include women booking for antenatal care, subsequent visits in the third trimester, at time-of-disease, when relevant, during/immediately after birth and 6 weeks after birth. CONCLUSIONS: To accelerate progress towards the women's and children's health-relevant Sustainable Development Goals, we need to understand how a variety of social, chronic disease, biomarker and pregnancy-specific determinants health interact to result in either a resilient or a compromised pregnancy for either mother or fetus/newborn, or both. This protocol has been designed to create such a depth of understanding. We are seeking funding to maintain the cohort to better understand the implications of pregnancy complications for both maternal and child health.

The PRECISE (PREgnancy Care Integrating translational Science, Everywhere) database: open-access data collection in maternal and newborn health.

In less-resourced settings, adverse pregnancy outcome rates are unacceptably high. To effect improvement, we need accurate epidemiological data about rates of death and morbidity, as well as social determinants of health and processes of care, and from each country (or region) to contextualise strategies. The PRECISE database is a unique core infrastructure of a generic, unified data collection platform. It is built on previous work in data harmonisation, outcome and data field standardisation, open-access software (District Health Information System 2 and the Baobab Laboratory Information Management System), and clinical research networks. The database contains globally-recommended indicators included in Health Management Information System recording and reporting forms. It comprises key outcomes (maternal and perinatal death), life-saving interventions (Human Immunodeficiency Virus testing, blood pressure measurement, iron therapy, uterotonic use after delivery, postpartum maternal assessment within 48 h of birth, and newborn resuscitation, immediate skin-to-skin contact, and immediate drying), and an additional 17 core administrative variables for the mother and babies. In addition, the database has a suite of additional modules for 'deep phenotyping' based on established tools. These include social determinants of health (including socioeconomic status, nutrition and the environment), maternal co-morbidities, mental health, violence against women and health systems. The database has the potential to enable future high-quality epidemiological research integrated with clinical care and discovery bioscience.