Preterm birth is a problem everywhere, in low- and high-income countries, and it is getting worse. In 2010, about 15 million babies—just over 10% of live births worldwide—were born preterm. More than 1 million of these babies died, most of them in low-income countries where advanced newborn care is less available. The preterm babies who survive can face serious health problems, including cerebral palsy, intellectual impairment, chronic lung disease, and vision and hearing loss.
Unfortunately, it can be difficult in lower-income settings to determine if a baby is being born pre-term, because it can be difficult to pinpoint a fetus’s gestational age—that is, how much time has passed since conception. With better information about gestational age, health workers can take steps during pregnancy, during labor, and after birth to make sure babies stay alive and healthy.
Through a multidisciplinary comparison and contrast of analytic methods using longitudinal study data, Ki was able to evaluate how to improve on existing clinical practice for obtaining gestational age to identify preterm kids in LMIC. The most accurate tool used in standard high-income countries’ clinical practice has been to measure gestational age during early ultrasound. Early ultrasound measurement of crown-rump length provides a reliable estimate of gestational age, but later in pregnancy, fetuses tend to vary more in size, and so crown-rump length provides a less reliable estimate. Ki’s work starts to translate HIC practices to LMIC settings to get to more timely interventions to LMIC pre-term babies.
With better information about gestational age, health workers can make sure babies stay alive and healthy.
In low- and middle-income countries, it is rare for women to have access to ultrasound early in their pregnancies. In these countries, gestational age is usually measured during pregnancy based on late ultrasound or on the date of the last menstrual period. Once babies are born, it’s measured using the Ballard score, a number based on physical and neuromuscular indications. None of these measures, however, estimates gestational age as reliably as early ultrasound. Our hope, using the Ki approach, was to find ways to improve gestational age estimates based on late ultrasound and birth metrics.
By collating ultrasound and non-ultrasound data from multiple datasets, we were able to estimate gestational age and preterm birth rates for 2,564 newborns. Our analysis of the data showed that taking additional ultrasound measurements—not just crown-rump length but also, for example, femur length and head circumference—improved gestational age estimates based on ultrasounds performed later in pregnancy. Early findings suggest that physical and neuromuscular measurements—for example, measuring the veins in the lenses of a baby’s eyes—can also be used to estimate gestational age.
At the population level, accurately estimating preterm birth rates and how they vary geographically will help policymakers identify where interventions are needed and evaluate their impact. At the individual patient level, better models for gestational age will help healthcare workers to take steps to help premature babies stay alive and healthy.