aEEG as an early predictor of brain injury and prognosis in neonates with hypoxic-ischemic encephalopathy.

Objective: This study aims to evaluate the independent risk factors associated with neonatal hypoxic-ischemic encephalopathy (HIE) using amplitude-integrated electroencephalography (aEEG), specifically exploring the relationship between aEEG scores, clinical manifestations, neurodevelopmental assessments, and neuron-specific enolase (NSE) levels with adverse outcomes in HIE.

Methods: A retrospective analysis was performed on clinical data from 224 neonates diagnosed with HIE who were admitted between January 2022 and May 2024. Infants were grouped by HIE severity: mild, moderate, and severe. A control group of 100 healthy neonates was also included. All infants underwent aEEG monitoring, and clinical data (including Apgar and Neonatal Behavioral Neurological Assessment (NBNA) scores), as well as NSE levels, were collected. The correlations of aEEG scores, Apgar score, NBNA score, and NSE level, with HIE severity were analyzed using Pearson or Spearman correlation analyses. The independent risk factors for adverse outcomes within six months in the neonates with HIE were identified using univariate and multivariate Cox regression analysis.

Results: HIE infants had significantly lower aEEG scores compared to the control group (P < 0.001). As the severity of HIE increased, aEEG scores and NBNA scores decreased notably (P < 0.001), while NSE levels increased (P < 0.001). aEEG scores were negatively correlated with HIE severity and NSE level, positively correlated with Apgar and NBNA scores. Both univariate and multivariate Cox regression analyses identified the severe HIE condition, amniotic fluid contamination, low aEEG scores, low Apgar scores, and high NSE levels as independent risk factors for adverse prognosis.

Conclusion: aEEG is a valuable tool in early diagnosis, severity assessment, and prognosis prediction of neonatal HIE. The integration of aEEG with other biomarkers such as Apgar scores, NBNA scores, and NSE levels could further improve diagnostic accuracy and enhance clinical management.