Predictive Models of Neurodevelopmental Outcomes after Neonatal Hypoxic-Ischemic Encephalopathy.

OBJECTIVES: To develop predictive models for death or neurodevelopmental impairment (NDI) after neonatal hypoxic-ischemic encephalopathy (HIE) from data readily available at the time of NICU admission ("early") or discharge ("cumulative"). METHODS: In this retrospective cohort analysis, we used data from the Children's Hospitals Neonatal Consortium Database (2010-2016). Infants born at >= 35 weeks' gestation and treated with therapeutic hypothermia for HIE at 11 participating sites were included; infants without Bayley Scales of Infant Development scores documented after 11 months of age were excluded. The primary outcome was death or NDI. Multivariable models were generated with 80% of the cohort; validation was performed in the remaining 20%. RESULTS: The primary outcome occurred in 242 of 486 infants; 180 died and 62 infants surviving to follow-up had NDI. HIE severity, epinephrine administration in the delivery room, and respiratory support and fraction of inspired oxygen of 0.21 at admission were significant in the early model. Severity of EEG findings was combined with HIE severity for the cumulative model, and additional significant variables included the use of steroids for blood pressure management and significant brain injury on MRI. Discovery models revealed areas under the curve of 0.852 for the early model and of 0.861 for the cumulative model, and both models performed well in the validation cohort (goodness-of-fit chi(2): P = .24 and .06, respectively). CONCLUSIONS: Establishing reliable predictive models will enable clinicians to more accurately evaluate HIE severity and may allow for more targeted early therapies for those at highest risk of death or NDI. In this study, we use data from the CHND to generate models of clinical data to predict death or disability after HIE.