Posted on by Lawrence Tabak, D.D.S., Ph.D.
It’s been estimated that every 18 minutes in the United States, a newborn baby starts life with painful withdrawals from exposure to opioids in the womb. It’s called neonatal opioid withdrawal syndrome (NOWS), and it makes for a challenging start in life. These infants may show an array of withdrawal symptoms, including tremors, extreme irritability, and problems eating and sleeping.
Many of these infants experience long, difficult hospital stays to help them manage their withdrawal symptoms. But because hospital staff have no established evidence-based treatment standards to rely on, there is substantial variation in NOWS treatment around the country. There also are many open questions about the safest and most-effective way to support these babies and their families.
But answers are coming. The New England Journal of Medicine just published clinical trial results that evaluated care for infants with NOWS and which offer some much needed—and rather encouraging—data for families and practitioners . The data are from the Eating, Sleeping, Consoling for Neonatal Opioid Withdrawal (ESC-NOW) trial, led by Leslie W. Young, The University of Vermont’s Larner College of Medicine, Burlington, and her colleagues Lori Devlin and Stephanie Merhar.
The ESC-NOW study is supported through the Advancing Clinical Trials in Neonatal Opioid Withdrawal (ACT NOW) Collaborative. ACT NOW is an essential part of the NIH Helping to End Addiction Long-term (HEAL) Initiative, an aggressive effort to speed scientific solutions to stem the national opioid public health crisis and improve lives.
The latest study puts to the test two different approaches to care for newborns with NOWS. The first approach relies on the Finnegan Neonatal Abstinence Scoring Tool. For almost 50 years, doctors primarily assessed NOWS using this tool. It is based on a scoring system of 21 signs of withdrawal, including disturbances in a baby’s nervous system, metabolism, breathing, digestion, and more. However, there have been concerns that this scoring tool has led to an overreliance on treating babies with opioid medications, including morphine and methadone.
The other approach is known as Eat, Sleep, Console (ESC) care . First proposed in 2014, ESC care has been adopted in many hospitals around the world. Rather than focusing on a long list of physical signs of withdrawal, this approach relies on a simpler functional assessment of whether an infant can eat, sleep, and be consoled. It emphasizes treatments other than medication, such as skin-to-skin contact, breastfeeding, and care from their mothers or other caregivers in a calm and nurturing environment.
The ESC care approach places an emphasis on the use of supportive interventions and aims to empower families in the care and nurturing of their infants. While smaller quality improvement studies of ESC have been compelling, the question at issue is whether the Eat, Sleep, Console care approach can reduce the time until infants with NOWS are medically ready to go home from the hospital in a wide variety of hospital settings—and, most importantly, whether it can do so safely.
To find out, the ESC-NOW team enrolled 1,305 infants with NOWS who were born after at least 36 weeks gestation. The study’s young participants were largely representative of infants with NOWS in the U.S., although non-Hispanic Black and Hispanic infants were slightly overrepresented. The babies were born at one of 26 U.S. hospitals, and each hospital was randomly assigned to transition from usual care using the Finnegan tool to the ESC care approach at a designated time.
Each hospital had a three-month transition period between the usual care and the ESC to allow clinical teams time to train on the new approach. The trial primarily aimed to understand if there was a significant difference in how long newborns with NOWS spent in the hospital before being medically ready for discharge between those receiving usual care versus those receiving ESC care. Researchers also assessed infants for safety, tracking both safety events that occurred during the hospital stay and events that occurred after the baby left the hospital, such as non-accidental trauma or death during an infant’s first three months.
The reported results reflect 837 of the 1,305 infants, who met the study definition of being medically ready for discharge. Infants who were discharged before meeting the study criteria, which were informed by the 2012 American Academy of Pediatrics recommendations for monitoring of infants with NOWS, were not included in the primary analysis.
Among the 837 infants, those who received ESC care were medically ready for discharge significantly sooner than those who received usual care. On average, they were medically ready to go home after about eight days compared to almost 15 days for the usual care group.
Many fewer infants in the ESC care group were treated with opioids compared to the usual care group (19.5 percent versus 52.0 percent). In more good news for ESC care, there was no difference in safety outcomes through the first three months despite the shorter hospital stays and reduced opioid treatment in the hospital. Infants who were cared for using the ESC care approach were no more likely to visit the doctor’s office, emergency room, or hospital after being discharged from the hospital.
More long-term study is needed to evaluate these children over months and years as they continue to develop and grow. Many of the infants in this study will be evaluated for the first two years of life to assess the long-term impact of ESC care on development and other outcomes. These findings offer encouraging early evidence that the ESC care approach is safe and effective. Although there was some variability in the outcomes, this study also shows that this approach can work well across diverse hospitals and communities.
The ESC-NOW trial is just one portion of the NIH Heal Initiative’s ACT NOW program, focused on gathering scientific evidence on how to care for babies with NOWS. Other studies are evaluating how to safely wean babies who do receive treatment with medication off opioids more quickly. The ACT NOW Longitudinal Study also will enroll at least 200 babies with prenatal opioid exposure and another 100 who were not exposed to better understand the long-term implications of early opioid exposure.
I’ve been anxious to see the results of the ESC-NOW study for a few months. It’s been worth the wait. The results show that we’re headed in the right direction with learning how best to treat NOWS and help to improve the lives of these young children and their families in the months and years ahead.
 Eat, Sleep, Console Approach versus usual care for neonatal opioid withdrawal. Young LW, Ounpraseuth ST, Merhar SL, Newman S, Snowden JN, Devlin LA, et al. NEJM, 2023 Apr 30 [Published online ahead of print]
 An initiative to improve the quality of care of infants with neonatal abstinence syndrome. Grossman MR, Berkwitt AK, Osborn RR, Xu Y, Esserman DA, Shapiro ED, Bizzarro MJ. Pediatrics. 2017 Jun;139(6):e20163360.
SAMHSA’s National Helpline (Substance Abuse and Mental Health Services Administration, Rockville, MD)
“Eat, Sleep, Console” reduces hospital stay and need for medication among opioid-exposed infants, NIH news release, May 1, 2023
Leslie Young (The University of Vermont, Larner College of Medicine, Burlington)
NIH Support: The Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Center for Advancing Translational Sciences; Office of the Director
Posted on by Dr. Francis Collins
Back in April 2003, when the international Human Genome Project successfully completed the first reference sequence of the human DNA blueprint, we were thrilled to have achieved that feat in just 13 years. Sure, the U.S. contribution to that first human reference sequence cost an estimated $400 million, but we knew (or at least we hoped) that the costs would come down quickly, and the speed would accelerate. How far we’ve come since then! A new study shows that whole genome sequencing—combined with artificial intelligence (AI)—can now be used to diagnose genetic diseases in seriously ill babies in less than 24 hours.
Take a moment to absorb this. I would submit that there is no other technology in the history of planet Earth that has experienced this degree of progress in speed and affordability. And, at the same time, DNA sequence technology has achieved spectacularly high levels of accuracy. The time-honored adage that you can only get two out of three for “faster, better, and cheaper” has been broken—all three have been dramatically enhanced by the advances of the last 16 years.
Rapid diagnosis is critical for infants born with mysterious conditions because it enables them to receive potentially life-saving interventions as soon as possible after birth. In a study in Science Translational Medicine, NIH-funded researchers describe development of a highly automated, genome-sequencing pipeline that’s capable of routinely delivering a diagnosis to anxious parents and health-care professionals dramatically earlier than typically has been possible .
While the cost of rapid DNA sequencing continues to fall, challenges remain in utilizing this valuable tool to make quick diagnostic decisions. In most clinical settings, the wait for whole-genome sequencing results still runs more than two weeks. Attempts to obtain faster results also have been labor intensive, requiring dedicated teams of experts to sift through the data, one sample at a time.
In the new study, a research team led by Stephen Kingsmore, Rady Children’s Institute for Genomic Medicine, San Diego, CA, describes a streamlined approach that accelerates every step in the process, making it possible to obtain whole-genome test results in a median time of about 20 hours and with much less manual labor. They propose that the system could deliver answers for 30 patients per week using a single genome sequencing instrument.
Here’s how it works: Instead of manually preparing blood samples, his team used special microbeads to isolate DNA much more rapidly with very little labor. The approach reduced the time for sample preparation from 10 hours to less than three. Then, using a state-of-the-art DNA sequencer, they sequence those samples to obtain good quality whole genome data in just 15.5 hours.
The next potentially time-consuming challenge is making sense of all that data. To speed up the analysis, Kingsmore’s team took advantage of a machine-learning system called MOON. The automated platform sifts through all the data using artificial intelligence to search for potentially disease-causing variants.
The researchers paired MOON with a clinical language processing system, which allowed them to extract relevant information from the child’s electronic health records within seconds. Teaming that patient-specific information with data on more than 13,000 known genetic diseases in the scientific literature, the machine-learning system could pick out a likely disease-causing mutation out of 4.5 million potential variants in an impressive 5 minutes or less!
To put the system to the test, the researchers first evaluated its ability to reach a correct diagnosis in a sample of 101 children with 105 previously diagnosed genetic diseases. In nearly every case, the automated diagnosis matched the opinions reached previously via the more lengthy and laborious manual interpretation of experts.
Next, the researchers tested the automated system in assisting diagnosis of seven seriously ill infants in the intensive care unit, and three previously diagnosed infants. They showed that their automated system could reach a diagnosis in less than 20 hours. That’s compared to the fastest manual approach, which typically took about 48 hours. The automated system also required about 90 percent less manpower.
The system nailed a rapid diagnosis for 3 of 7 infants without returning any false-positive results. Those diagnoses were made with an average time savings of more than 22 hours. In each case, the early diagnosis immediately influenced the treatment those children received. That’s key given that, for young children suffering from serious and unexplained symptoms such as seizures, metabolic abnormalities, or immunodeficiencies, time is of the essence.
Of course, artificial intelligence may never replace doctors and other healthcare providers. Kingsmore notes that 106 years after the invention of the autopilot, two pilots are still required to fly a commercial aircraft. Likewise, health care decisions based on genome interpretation also will continue to require the expertise of skilled physicians.
Still, such a rapid automated system will prove incredibly useful. For instance, this system can provide immediate provisional diagnosis, allowing the experts to focus their attention on more difficult unsolved cases or other needs. It may also prove useful in re-evaluating the evidence in the many cases in which manual interpretation by experts fails to provide an answer.
The automated system may also be useful for periodically reanalyzing data in the many cases that remain unsolved. Keeping up with such reanalysis is a particular challenge considering that researchers continue to discover hundreds of disease-associated genes and thousands of variants each and every year. The hope is that in the years ahead, the combination of whole genome sequencing, artificial intelligence, and expert care will make all the difference in the lives of many more seriously ill babies and their families.
 Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation. Clark MM, Hildreth A, Batalov S, Ding Y, Chowdhury S, Watkins K, Ellsworth K, Camp B, Kint CI, Yacoubian C, Farnaes L, Bainbridge MN, Beebe C, Braun JJA, Bray M, Carroll J, Cakici JA, Caylor SA, Clarke C, Creed MP, Friedman J, Frith A, Gain R, Gaughran M, George S, Gilmer S, Gleeson J, Gore J, Grunenwald H, Hovey RL, Janes ML, Lin K, McDonagh PD, McBride K, Mulrooney P, Nahas S, Oh D, Oriol A, Puckett L, Rady Z, Reese MG, Ryu J, Salz L, Sanford E, Stewart L, Sweeney N, Tokita M, Van Der Kraan L, White S, Wigby K, Williams B, Wong T, Wright MS, Yamada C, Schols P, Reynders J, Hall K, Dimmock D, Veeraraghavan N, Defay T, Kingsmore SF. Sci Transl Med. 2019 Apr 24;11(489).
DNA Sequencing Fact Sheet (National Human Genome Research Institute/NIH)
Genomics and Medicine (NHGRI/NIH)
Genetic and Rare Disease Information Center (National Center for Advancing Translational Sciences/NIH)
Stephen Kingsmore (Rady Children’s Institute for Genomic Medicine, San Diego, CA)
NIH Support: National Institute of Child Health and Human Development; National Human Genome Research Institute; National Center for Advancing Translational Sciences