Paul Albert of Eunice Kennedy Shriver National Institute of Child Health and Human Development in the U.S. will use a modeling approach to help clinicians with different resources better estimate gestational age, which is critical for monitoring maternal and child health. Gestational age is currently estimated using ultrasound, which is often unavailable in low-resource settings, or the date of the last menstrual period and external measurements of the uterus, which can be imprecise. The timing of these measurements during pregnancy also influences the accuracy of the estimate. They will develop an empirical Bayesian estimation strategy that can translate different combinations of measurements taken at different time points into an accurate estimate of gestational age, even without ultrasound. They will test their model using available measurements from 3,000 women of mixed race from the U.S.
More information about Explore New Ways to Measure Brain Development and Gestational Age (Round 14)