Quantitative EEG features for the prediction of short-term neuromotor development outcome in premature neonates - Yuanyuan Shan; Lin Zhang; Peng Zhang; Yan Xu; Jun Wang; Mingshu Yang; Guoqiang Cheng (Scientific Reports)
Abstract The objective of this study was to identify relevant quantitative parameters to distinguish premature infants with presence of brain injury from conventional electroencephalography (EEG) and predict short-term neuromotor developmental outcomes. This is a prospective cohort study of newborns at 34 weeks’ gestation or earlier. Multichannel EEG recordings were performed within 24 h after birth. The total power (TP), absolute and relative band power (ABP and RBP), alpha/theta ratio (ATR), alpha/delta + theta ratio (ADTR), 95% spectral edge frequency (SEF), approximate entropy (ApEn), coherence and brain symmetry index (BSI) were calculated using the Auto-Neo-EEG signal processing system. Neonates were divided into two groups: with and without brain injury, and clinical outcomes of general movements (GMs) assessment at three months were available for analysis. This study comprised 43 and 65 premature neonates with and without brain injury, respectively. Premature neonates with brain injury had significantly lower TP, ABP-δ, ABP-α, RBP-δ and coherence than those without brain injury (all p values < 0.05). The area under curve (AUC) of TP, ABP-δ, ABP-α, RBP-δ and coherence for predicting brain injury was 0.749, 0.830, 0.721, 0.799 and 0.743, respectively. Preterm infants with brain injury had significantly lower GMs optimality scores (15.6 ± 6.7) than those without brain injury (28.4 ± 8.3) (P = 0.019). For 43 preterm infants with brain injury, TP (P = 0.023) and ABP-δ (P = 0.030) were positively correlated with GMs optimality scores; while coherence (P = 0.039) was the opposite. Compared with those without brain injury, preterm infants with brain injury tended to have reduced spectral power, accompanied by impaired brain network connectivity, and delayed short-term motor development. Automated quantitative EEG (qEEG) analysis provides predictive value for the occurrence of brain injury and outcomes in preterm neonates, among which ABP-δ presented the best predictive performance.