Metabolic gestational age assessment in low resource settings: a validation protocol.

Area of Science:

• Neonatal health
• Biomarker analysis
• Global public health

Background:

• Preterm birth is a major cause of newborn illness and death globally.
• Accurate gestational age estimation is crucial for managing preterm birth but challenging in low-resource settings.
• Current methods like ultrasound are often inaccessible in resource-limited areas.

Purpose of the Study:

• To validate a novel algorithm for estimating gestational age from dried blood spot samples in low-resource countries.
• To assess the feasibility of using newborn screening analytes for gestational age determination.
• To pilot an algorithm for identifying small for gestational age infants.

Main Methods:

• Dried blood spot samples (heel-prick or cord blood) will be collected in Zambia, Kenya, Bangladesh, and Zimbabwe.
• Samples will be analyzed by the Newborn Screening Ontario laboratory for analyte values.
• An existing algorithm will be used to estimate gestational age and birth percentiles.

Main Results:

• The study aims to determine the accuracy of the algorithm in diverse, low-resource populations.
• Validation of the algorithm's performance in estimating gestational age is the primary outcome.
• The potential for real-time screening for other conditions will be explored.

Conclusions:

• This research could establish a feasible and accessible method for gestational age assessment in low- and middle-income countries.
• Accurate gestational age estimation from dried blood spots can aid in resource allocation and improve neonatal care.
• The findings may lead to improved identification and management of infants at risk due to preterm birth.