Estimating Gestational Age and Prediction of Preterm Birth Using Metabolomics Biomarkers

Abstract

Preterm birth (PTB) is a leading cause of morbidity and mortality in children aged under 5 years globally, especially in low-resource settings. It remains a challenge in many low-income and middle-income countries to accurately measure the true burden of PTB due to limited availability of accurate measures of gestational age (GA), first trimester ultrasound dating being the gold standard. Metabolomics biomarkers are a promising area of research that could provide tools for both early identification of high-risk pregnancies and for the estimation of GA and preterm status of newborns postnatally.

Keywords: Gestational age; Machine learning; Maternal newborn health; Metabolomics; Newborn screening; Perinatal epidemiology; Prediction modeling; Preterm birth.