For a study, researchers sought to determine the predictive accuracy of a longitudinal study of amplitude-integrated electroencephalography (aEEG) background activity in newborns with hypoxic-ischemic encephalopathy (HIE) undergoing therapeutic hypothermia.

The single-center observational study recruited 149 newborns for derivation and 55 neonates for validation in a tertiary neonatal critical care unit with moderate-severe HIE and gestational age more or equal to 35 weeks. Over 84 hours of therapeutic hypothermia and rewarming, single-channel aEEG background pattern, sleep-wake cycle, and seizure activity were recorded and evaluated for each 6-hour interval. The Bayley Scales of Infant Development, Second Edition, was used to measure the neurodevelopmental outcomes. A favorable result was defined as a Mental Development Index (MDI) score and a Psychomotor Development Index (PDI) score of more or equal to 70, whereas an unfavorable outcome was defined as either an MDI or a PDI score of less than 70 or death. The area under the receiver operating characteristic curve (AUC) was computed using regression modeling for the longitudinal study of frequently obtained data.

Longitudinal aEEG background analysis combined with sleep-wake cycle score demonstrated a stronger predictive value (AUC, 0.90; 95% CI, 0.85-0.95) than individual aEEG values at any time. Furthermore, the model worked admirably in the independent validation cohort (AUC, 0.87; 95% CI, 0.62-1.00). At 48 hours, the reclassification rate of the model compared to the traditional analysis of aEEG background was 18% (24 patients); 14% (18 patients) were successfully categorized. The findings were utilized to create an easy-to-use online outcome prediction tool.

Longitudinal aEEG background activity and sleep-wake cycle study is a useful and accurate prognostic technique.