MUSC clinical trial tests new approach to treat opioid-dependent babies

CHARLESTON, S.C. (WCSC) - At least one newborn is diagnosed every 24 minutes in the U.S. with Neonatal Opioid Withdrawal Syndrome (NOWS), according to The National Institutes of Health.

That’s why 26 U.S. hospitals, including MUSC, recently wrapped up a clinical trial that tested a new way to care for babies born physically dependent on opioids.

MUSC Pediatrician and Medical Director of the NICU Dr. Julie Ross says on average, they see one or more babies a week with NOWS.

Ross describes the symptoms of a baby experiencing opioid withdrawal as “very irritable, a lot of crying, and that they can be very difficult to console and have difficulty feeding.”

The new approach that the trial tested is called Eat, Sleep, Console (ESC) and over 13,000 infants were enrolled.

Staff members at each hospital involved in the trial were trained to use the new approach during a 3-month transition period, according to the New England Journal of Medicine

The ESC approach results showed the babies were ready to go home about a week earlier and were 63% less likely to get medication than babies who were treated using the older approach, the Finnegan Neonatal Abstinence Scoring Tool.

ESC focuses less on medication and more on things like skin-to-skin contact, swaddling and rocking.

“One of the big advantages of the Eat, Sleep, Console approach is the empowerment is places on families to really be active participants in their baby’s care,” Ross said. “It empowers them to provide the first-line treatment and be an engaged part of the medical team and helping to support their babies.

Ross says having a standardized approach for babies with NOWS is crucial.

“The initial clinical data looks very promising,” she said. “A subpopulation of these infants will continue to be followed long-term to look at both infant and family well-being for a longer period of time, as well as infant development.”

The trial lasted over two years, and MUSC continues to care for babies with the ESC approach.

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