April 3, 2023

CHOP Researchers Develop First-Of-Its-Kind Prediction Model for Newborn Seizures

Article published by NewsWise

Researchers from the Neuroscience Center at Children’s Hospital of Philadelphia (CHOP) have developed a prediction model that determines which newborn babies are likely to experience seizures in the Neonatal Intensive Care Unit (NICU). This model could be incorporated into routine care to help the clinical team decide which babies will need electroencephalograms (EEGs) and which babies can be safely managed in the Neonatal Care Unit without monitoring through EEGs. This would allow families and providers to care for babies without intrusive and unnecessary procedures. The findings were published by The Lancet Digital Health.

Neonatal seizures are a common neurological issue in newborn babies. In particular, approximately 30% of newborn babies with temporary lack of oxygen to the brain (known as hypoxic-ischemic encephalopathy, or HIE) will have seizures. Most of these seizures can only be detected through EEG monitoring and not simply through clinical observation, an important lesson that has shaped the management of babies with seizures in the last two decades. Newborns with HIE are at an increased risk for neurobehavioral problems and epilepsy later in life, and detecting and treating seizures is important to reduce seizure-induced injury, thereby improving outcomes for newborns with early seizures.

Current guidelines suggest that newborns with HIE undergo four to five days of EEG monitoring to detect seizures. However, this approach is not always feasible, as many of these babies receive care in NICUs that do not have access to continuous EEG (CEEG). Even NICUs in large healthcare networks often only have limited EEG resources, especially as the interpretation of EEG readings is time intensive for the entire care team, including physicians and technologists.

Predicting which newborns will experience seizures is complex, and prior attempts to predict future seizures using clinical and EEG data have not yielded highly accurate results. To help address these issues, researchers at CHOP used data from a recently developed EEG reporting form that is used for all EEGs to build prediction models using machine learning methods.

“In this study, we used data from the EEGs of more than 1,000 newborns to build models to predict neonatal seizures,” first study author Jillian McKee, MD, PhD, a pediatric epilepsy fellow in the Division of Neurology and the Pediatric Epilepsy Program at CHOP. “This data helped us optimize which newborns should receive EEG monitoring in the NICU.”