Newborn metabolic profiles have been shown to accurately estimate gestational age, identify preterm infants at risk for complications, such as sepsis and respiratory distress syndrome, and are associated with perinatal survival. However, to our knowledge, their use to evaluate risk for longer-term neurodevelopmental impairment or disability outcomes has not been explored, particularly in low- and- middle-income countries.

This study followed up approximately 200 infants from the Gestational Age Dating (GAD) study led by Stanford University and University of Zimbabwe. Using the Griffiths Scales of Child Development, 3rd Edition (Griffiths III) for development assessment, Teller cards for vision and formal audiology evaluation, GAD children were seen between 2-3 years old to assess their neurodevelopment, possible sensory impairment and overall health. The goal of this work is to build and test metabolic predictive models to distinguish young children with neurotypical development from those with neurodevelopmental impairment by linking long-term neurodevelopmental data with existing maternal and newborn biomarker data.