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Quantitative electroencephalogram in term neonates under different sleep states

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Abstract

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.

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Datasets in csv format are available upon reasonable request.

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Funding

None of the authors received funding or have disclosures related to this manuscript.

Author information

Authors and Affiliations

  1. 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

    Ian Yuan, Ashley Hodges, C. Dean Kurth, Matthew P. Kirschen, Jimmy W. Huh, Alexis A. Topjian & Nicholas S. Abend

  2. Vagelos Integrated Program in Energy Research, University of Pennsylvania, Philadelphia, PA, USA

    Georgia Georgostathi & Adam Richter

  3. Department of Biomedical and Health Informatics, Data Science and Biostatistics Unit, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Bingqing Zhang

  4. Division of Neurosurgery, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Shih-shan Lang

  5. Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Shih-shan Lang, Nicholas S. Abend & Shavonne L. Massey

  6. Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Adam Richter

  7. Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Nicholas S. Abend & Shavonne L. Massey

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  1. Ian Yuan
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  2. Georgia Georgostathi
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Contributions

IY, CDK, JH, MPK, AAT, SSC, NSA, SLM were involved with the conception and design of the study. IY, GG, BZ, ASH, AR, SLM were involved with data retrieval and analysis. All authors were involved in interpretation of the data, drafting, revising the manuscript, and approved the final version of the manuscript.

Corresponding author

Correspondence to Ian Yuan.

Ethics declarations

Competing interest

(1) Ian Yuan received a research grant and speaker honorarium from Masimo Corp; (2) Matthew Kirschen received NIH funding to his institution; (3) Nicholas Abend received royalty from textbooks. None of the above were related to this study. The other authors have no relevant financial or non-financial interests to disclose.

Ethical approval

The Institutional Review Board determined the study was exempt from review.

Statement of human rights

All procedures performed in this study involving human participants were approved by and in accordance with the ethical standards of the Institutional Review Board of the Children’s Hospital of Philadelphia (Number: IRB 19-016180) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Statement on the welfare of animals

Not applicable.

Informed consent

Informed consent was not obtained, as this retrospective study did not involve identifiable patient information and the Institutional Review Board exempted the study from requiring informed consent. “A waiver of HIPAA authorization per 45 CFR 164.512(i)(2)(ii) is granted for accessing identifiable information from the medical records.”

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Results from this manuscript have been presented in abstract format at Society of Technology in Anesthesia annual conference 2022.

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Yuan, I., Georgostathi, G., Zhang, B. et al. Quantitative electroencephalogram in term neonates under different sleep states. J Clin Monit Comput (2023). https://doi.org/10.1007/s10877-023-01082-6

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  • DOI: https://doi.org/10.1007/s10877-023-01082-6

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