96 - A new EEG-derived automated bedside brain state trend correlates with encephalopathy grade in newborns with Hypoxic Ischemic Encephalopathy

Hypoxic ischemic encephalopathy (HIE) is one of the leading causes of long-term disability and death. Mild neonatal encephalopathy constitutes a large population and is the subject of debate regarding how to define and who to treat. Because of dynamic evolution, the need for prompt treatment decision highly depends on accurate, continuous biomarkers of brain health. A recently developed algorithm constructs a new measure of the brain state of the newborn (BSN) to an automated beside trend for real-time quantified interpretations of EEG in neonates.

Objective:

This study aimed to (1) compare and differentiate BSN between newborns with mild and moderate HIE and (2) examine the relationship between BSN and 2-year outcomes in neurodevelopmental disability.

Design/Methods:

This study was based on a single-center prospective cohort having ≥ 36-week gestation inborn infants with mild and moderate HIE diagnosed within 6 hours (h) of birth in a level III neonatal intensive care unit from 2018 to 2019.  We collected EEG data using eight electrodes at a rate of 256 Hz for 6 hours on the first day of life. All infants were followed with Bayley testing at two-years.

The measured 6-h raw EEG data were processed to quantify BSN using the automated online algorithm. Group-level BSN scores were compared between mild and moderate HIE infants using a two-sample t-test. We also evaluated the correlation between BSN and our previously published biomarkers, as well as with Total Sarnat Score (TSS).

Results:

Forty-six (46) infants were included, 18 with mild HIE, 6 progressed from mild-to-moderate, 19 moderate, and 3 severe HIE. Six-hour averaged BSN scores of mild and moderate HIE are significantly different (p< 0.015; Fig. 1(A)). BSN scores correlated positively with our previously found biomarkers, including delta-power (R=0.44, p< 0.007) and phase-amplitude coupling (PAC; R=0.53, p< 0.002). BSN scores also correlated negatively with TSS, indicating a lower BSN associated with a higher Sarnat clinical score (R=0.44, p< 0.007). Last, we report significant differences in BSN scores for the infants having two-year severe neurodevelopmental disability (p< 0.025; Fig. 1(B)).

Conclusion(s):

Our results support that BSN can be used for real-time monitoring of encephalopathy grade in HIE. BSN is also consistent with our previously identified biomarkers. Understanding the relationship between the evolving encephalopathy and BSN can lead to improved risk stratification for the evolution of the dynamic encephalopathy and future therapeutic interventions targeting mild HIE.