Quantitative electroencephalogram in term neonates under different sleep states

• Published in: Journal of clinical monitoring and computing Vol. 38; no. 3; pp. 591 - 602
• Main Authors: Yuan, Ian, Georgostathi, Georgia, Zhang, Bingqing, Hodges, Ashley, Kurth, C. Dean, Kirschen, Matthew P., Huh, Jimmy W., Topjian, Alexis A., Lang, Shih-shan, Richter, Adam, Abend, Nicholas S., Massey, Shavonne L.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01-06-2024; Springer Nature B.V
• Subjects: Anesthesia; Anesthesiology; Brain - physiology; Coherence; Consciousness; Consciousness - physiology; Critical Care Medicine; Electroencephalography; Electroencephalography - methods; Entropy; Female; Health Sciences; Humans; Infant, Newborn; Intensive; Male; Medicine; Medicine & Public Health; Original Research; ROC Curve; Signal Processing, Computer-Assisted; Sleep; Sleep - physiology; Statistics for Life Sciences; Wakefulness; Wakefulness - physiology; Neonatal sleep; Quantitative EEG; Neonatal EEG; EEG
• ISSN: 1387-1307; 1573-2614
• DOI: 10.1007/s10877-023-01082-6

Electroencephalogram (EEG) can be used to assess depth of consciousness, but interpreting EEG can be challenging, especially in neonates whose EEG undergo rapid changes during the perinatal course. EEG can be processed into quantitative EEG (QEEG), but limited data exist on the range of QEEG for normal term neonates during wakefulness and sleep, baseline information that would be useful to determine changes during sedation or anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identified the ones best at discriminating between the three states. Normal neonatal EEG from 37 to 46 weeks were analyzed and classified as awake, quiet sleep, or active sleep. After processing and artifact removal, total power, power ratio, coherence, entropy, and spectral edge frequency (SEF) 50 and 90 were calculated. Descriptive statistics were used to summarize the QEEG in each of the three states. Receiver operating characteristic (ROC) curves were used to assess discriminatory ability of QEEG. 30 neonates were analyzed. QEEG were different between awake
vs
asleep states, but similar between active
vs
quiet sleep states. Entropy beta, delta2 power %, coherence delta2, and SEF50 were best at discriminating awake
vs
active sleep. Entropy beta had the highest AUC-ROC ≥ 0.84. Entropy beta, entropy delta1, theta power %, and SEF50 were best at discriminating awake
vs
quiet sleep. All had AUC-ROC ≥ 0.78. In active sleep
vs
quiet sleep, theta power % had highest AUC-ROC > 0.69, lower than the other comparisons. We determined the QEEG range in healthy neonates in different states of consciousness. Entropy beta and SEF50 were best at discriminating between awake and sleep states. QEEG were not as good at discriminating between quiet and active sleep. In the future, QEEG with high discriminatory power can be combined to further improve ability to differentiate between states of consciousness.