Quantitative electroencephalogram in term neonates under different sleep states.

Autor: Yuan I; Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia. Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA, 19104, USA. yuani@chop.edu., Georgostathi G; Vagelos Integrated Program in Energy Research, University of Pennsylvania, Philadelphia, PA, USA., Zhang B; Department of Biomedical and Health Informatics, Data Science and Biostatistics Unit, Children's Hospital of Philadelphia, Philadelphia, PA, USA., Hodges A; Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia. Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA, 19104, USA., Kurth CD; Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia. Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA, 19104, USA., Kirschen MP; Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia. Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA, 19104, USA., Huh JW; Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia. Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA, 19104, USA., Topjian AA; Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia. Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA, 19104, USA., Lang SS; Division of Neurosurgery, Children's Hospital of Philadelphia, Philadelphia, PA, USA.; Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Richter A; Vagelos Integrated Program in Energy Research, University of Pennsylvania, Philadelphia, PA, USA.; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA., Abend NS; Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia. Perelman School of Medicine, University of Pennsylvania, 3401 Civic Center Blvd., Philadelphia, PA, 19104, USA.; Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA., Massey SL; Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.; Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Jazyk: angličtina
Zdroj: Journal of clinical monitoring and computing [J Clin Monit Comput] 2024 Jun; Vol. 38 (3), pp. 591-602. Date of Electronic Publication: 2023 Oct 18.
DOI: 10.1007/s10877-023-01082-6
Abstrakt: 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.
(© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)
Databáze: MEDLINE
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