Gestational age dating using newborn metabolic screening: A validation study in Busia, Uganda

Abstract

Background Limited ultrasound capacity in low-resource settings makes correct gestational age (GA) dating difficult. Previous work demonstrated that newborn metabolic profiles can accurately determine gestational age, but this relationship has not been evaluated in low-income countries. The objective of this study was to validate and adapt a metabolic GA dating model developed using newborn blood spots for use in a low-resource setting in rural Uganda. Methods A cohort of pregnant women was followed prospectively and heel stick blood spots were collected from 666 newborns in Busia, Uganda at the time of delivery. They were dried, frozen, and shipped to the US where they were tested for 47 metabolites. Metabolic model performance was assessed using early ultrasound determined GA as the standard. Models tested included previously built multivariable models and models specifically adapted to the Busia population. Results The previously built model successfully dated 81.2% of newborns within two weeks of their ultrasound GA. Only 4.8% of GAs were off by greater than three weeks. In the model adapted to the local population, 89.2% of GAs matched their corresponding ultrasound to within two weeks. The model-derived preterm birth rate was 7.2% compared to 5.9% by ultrasound. Conclusions These results suggest that metabolic dating is a reliable method to determine GA in a low-income setting. Metabolic dating offers the potential to better elucidate preterm birth rates in low-resource settings, which is important for assessing population-level patterns, tailoring clinical care, and understanding the developmental trajectories of preterm infants.