Improving the Prediction of Stillbirth

The Riley Fund

Improving the Prediction of Stillbirth led by Dr. Robert Silver at The University of Utah School of Medicine is working to develop prediction tools to identify stillbirth risks later in pregnancy when early delivery is an option and is funded by The Riley Fund for Stillbirth Research at R Baby Foundation.  To read more about The Riley Fund, please visit here.

Stillbirth happens when babies die before they are born, which can take place either early or late in pregnancy. This catastrophic complication occurs in more than 1 in 200 births in the United States, and is especially tragic when it happens late in pregnancy to otherwise healthy babies, as is usually the case when a cord accident occurs. It is one of the most emotionally traumatic health events, and yet has such high potential for prevention. Despite its alarming frequency and devastating nature, little progress has been made in our ability to predict and prevent stillbirth. Indeed, the stillbirth rate in the United States has remained relatively stable over the past decade, and the modest reductions we have achieved still lag behind those of other high-income countries. Because of this, it is critical that we prioritize the prediction and prevention of this tragic complication in our research endeavors.

So far, the only option to prevent stillbirth has been to identify fetuses at high risk of stillbirth and then attempt delivery before it occurs, since neonates can be resuscitated and intervened upon more proactively than a fetus can. This approach, while intuitive, has had limited success, primarily because our ability to predict stillbirth has been so poor. Our suboptimal prediction of stillbirth has led to delivering many low-risk babies too early (causing unnecessary prematurity-related neonatal complications) while still missing too many stillbirths. These neonatal complications associated with early delivery, which are most severe when delivered before 34 weeks gestation, have caused obstetricians to increasingly avoid attempting to prevent stillbirth with early delivery in all but the most obvious cases.

However, neonatal complications decrease with each additional week in pregnancy, such that the window from 34-38 weeks of pregnancy represents a potential opportunity wherein an accurate assessment of stillbirth risk could potentially push obstetricians to recommend delivery.

The problem is that thus far we have not had a way to confidently quantify the stillbirth risk in this way. This “early delivery approach” can only have an impact on the rate of stillbirth if it can be accurately predicted. Therefore, our goal is to develop tools by which the risk of fetal death can be better quantified during the time in pregnancy (34-38 weeks) when the option of early delivery could be offered as a preventive measure.

This study will work toward improving the prediction of stillbirth with a goal is to generate a comprehensive risk prediction model by studying and integrating critical information from three unique but readily available sources: maternal blood, ultrasound and maternal characteristics.