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Quantitative EEG and prediction of outcome in neonatal encephalopathy: a review

Pediatric Research volume 96, pages 73–80 (2024)Cite this article

Abstract

Electroencephalogram (EEG) is an important biomarker for neonatal encephalopathy (NE) and has significant predictive value for brain injury and neurodevelopmental outcomes. Quantitative analysis of EEG involves the representation of complex EEG data in an objective, reproducible and scalable manner. Quantitative EEG (qEEG) can be derived from both a limited channel EEG (as available during amplitude integrated EEG) and multi-channel conventional EEG. It has the potential to enable bedside clinicians to monitor and evaluate details of cortical function without the necessity of continuous expert input. This is particularly useful in NE, a dynamic and evolving condition. In these infants, continuous, detailed evaluation of cortical function at the bedside is a valuable aide to management especially in the current era of therapeutic hypothermia and possible upcoming neuroprotective therapies. This review discusses the role of qEEG in newborns with NE and its use in informing monitoring and therapy, along with its ability to predict imaging changes and short and long-term neurodevelopmental outcomes.

Impact

  • Quantitative representation of EEG data brings the evaluation of continuous brain function, from the neurophysiology lab to the NICU bedside and has a potential role as a biomarker for neonatal encephalopathy.

  • Clinical and research applications of quantitative EEG in the newborn are rapidly evolving and a wider understanding of its utility is valuable.

  • This overview summarizes the role of quantitative EEG at different timepoints, its relevance to management and its predictive value for short- and long-term outcomes in neonatal encephalopathy.

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Author information

Authors and Affiliations

  1. Division of Newborn Medicine, Department of Pediatrics, Brigham and Women’s Hospital, Boston, MA, USA

    Sriya Roychaudhuri, Katie Hannon, Aisling A. Garvey & Mohamed El-Dib

  2. Harvard Medical School, Boston, MA, USA

    Sriya Roychaudhuri, Katie Hannon, John Sunwoo & Mohamed El-Dib

  3. Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA

    John Sunwoo

  4. INFANT Research Centre, Cork, Ireland

    Aisling A. Garvey

  5. Department of Paediatrics and Child Health, University College Cork, Cork, Ireland

    Aisling A. Garvey

  6. Department of Neonatology, Cork University Maternity Hospital, Cork, Ireland

    Aisling A. Garvey

Authors
  1. Sriya Roychaudhuri
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  2. Katie Hannon
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  3. John Sunwoo
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  4. Aisling A. Garvey
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  5. Mohamed El-Dib
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Contributions

Each of the authors listed have contributed significantly to this manuscript and met the Pediatric Research authorship requirements as elaborated below. Sriya Roychaudhuri: substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; drafting the article; final approval of the version to be published. Katie Hannon: drafting the article and final approval of the version to be published. John Sunwoo: substantial contributions to conception and design along with analysis and interpretation of previously published data; revising it critically for important intellectual content; and final approval of the version to be published. Aisling A. Garvey: drafting segments of the manuscript and revising it critically for important intellectual content; and final approval of the version to be published. Mohamed El-Dib: substantial contributions to conception and design, analysis and interpretation of data; drafting and revising the article critically for important intellectual content; final approval of the version to be published.

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Correspondence to Mohamed El-Dib.

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Roychaudhuri, S., Hannon, K., Sunwoo, J. et al. Quantitative EEG and prediction of outcome in neonatal encephalopathy: a review. Pediatr Res 96, 73–80 (2024). https://doi.org/10.1038/s41390-024-03138-y

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