New Tool Helps Identify Newborns at Risk for Opioid Withdrawal
By Ellie Pourbohloul
The U.S. opioid crisis has affected many populations, including pregnant women and infants. Neonatal opioid withdrawal syndrome (NOWS) is a drug withdrawal syndrome that impacts some opioid-exposed infants shortly after they are born. On average nationwide, one infant is diagnosed with NOWS every 15 minutes. The challenge pediatricians face is that not every infant exposed to opioids will develop NOWS, and there have not been tools available to identify low- or high-risk newborns, until now.
To address this gap, researchers from Vanderbilt University Medical Center and the Rollins School of Public Health came together to create a model to predict severe NOWS. They used electronic health record (EHR) data routinely collected at time of birth from 33,991 births.
What They Found
The predictive model incorporated multiple predictors beyond opioid exposure—such as maternal opioid use disorder diagnosis and cigarette smoking, Apgar score, and various maternal prescriptions—to accurately predict treatment of NOWS with pharmacotherapy.
This study built on previous work funded by the National Institute on Drug Abuse and led by Stephen Patrick, MD, chair of the Department of Health Policy and Management at Rollins and a practicing neonatologist at Children’s Healthcare of Atlanta. This study added more recent EHR data and additional risk predictors to develop a more robust clinical tool.
Why It Matters
This predictive model is a significant step forward relative to screening for chronic opioid exposure alone. It enables physicians to assess the likelihood of infants developing severe NOWS soon after birth using multiple factors. This allows physicians to tailor interventions and decide whether at-risk infants should continue to be hospitalized. It also allows for discharge of infants who are unlikely to return to the hospital for pharmacologic treatment later.
What the Experts Say
“The opioid crisis continues to have a substantial impact on mothers and infants nationwide, but especially in rural areas. We need a comprehensive approach that begins with making sure pregnant women can get into treatment,” says Patrick.
“We also need far more tools to improve care we deliver to opioid-exposed infants. This predictive model especially benefits rural communities that are disproportionately affected by NOWS. For instance, having a clear picture of risk factors based on multiple predictors could mean that babies can stay with their mothers if they’re low risk instead of being separated and transferred to a different hospital for a higher level of care.
“We might also be able to send low-risk infants home days earlier instead of watching them in the hospital. Our hope is that this tool, especially once tested, can help families and pediatricians in real time deliver more personal care.”
This research is part of a larger funded project from the National Institute on Child Health and Human Development that is focused on improving outcomes for pregnant women and infants affected by the opioid crisis.
