The predictive model allows physicians to make informed decisions about hospitalising at-risk infants. Credit: Gorodenkoff / Shutterstock.

A US-based team of researchers from Vanderbilt University Medical Center (VUMC) and the Rollins School of Public Health has developed a predictive model to identify newborns at risk of severe neonatal opioid withdrawal syndrome (NOWS) soon after their birth.

The model utilises electronic health record (EHR) data from nearly 33,991 births, incorporating various factors such as maternal opioid use disorder, maternal prescriptions, Apgar scores, and cigarette smoking.

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It marks an advancement in neonatal care by enabling physicians to design interventions for infants at risk of severe NOWS, a condition affecting infants exposed to opioids. The goal is to predict the need for pharmacotherapy in treating NOWS.

This research is said to be part of a broader initiative funded by the National Institute on Child Health and Human Development aimed at enhancing outcomes for pregnant women and also infants who are impacted by the opioid crisis.

Stephen Patrick, Rollins’ department of health policy and management chair and Children’s Healthcare of Atlanta’s practising neonatologist, spearheaded the study.

This trial added additional latest EHR data and risk predictors to create the clinical tool. It builds upon previous research for which the National Institute on Drug Abuse provided the fund.

By evaluating multiple factors, the predictive model allows physicians to make informed decisions about hospitalising at-risk infants or safely discharging those unlikely to require pharmacological treatment later.

This approach streamlines care and could potentially minimise hospital stays for newborns.

Patrick said: “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. 

“We also need far more tools to improve the care we deliver to opioid-exposed infants. This predictive model especially benefits rural communities that are disproportionately affected by NOWS.”