EEG - A Valuable Biomarker of Brain Injury in Preterm Infants

Elena Pavlidis1, Rhodri O Lloyd, Geraldine B Boylan

  • 1Neonatal Brain Research Group, Irish Centre for Fetal and Neonatal Translational Research (INFANT), and Department of Paediatrics and Child Health, University College Cork, Cork, Ireland.

Insights

Electroencephalography (EEG) monitoring helps detect brain function abnormalities in preterm infants. This review details EEG patterns linked to common brain injuries, aiding in adverse outcome prediction.

Area of Science:

  • Neuroscience
  • Neonatology
  • Medical Imaging

Background:

  • Increasing survival rates of very and extremely preterm infants necessitate better brain function monitoring.
  • Developmental brain injuries are common in preterm infants, impacting long-term outcomes.
  • Standardized characterization of EEG patterns in this population is crucial.

Purpose of the Study:

  • To review the role of electroencephalography (EEG) in monitoring preterm infant brain function abnormalities.
  • To describe EEG features associated with common neonatal brain injuries.
  • To identify key EEG biomarkers for predicting adverse outcomes.

Main Methods:

  • Literature review focusing on EEG findings in preterm infants.
  • Analysis of EEG patterns related to intraventricular hemorrhage, periventricular leukomalacia, and perinatal asphyxia.
  • Compilation of characteristic EEG biomarkers and waveform examples.

Main Results:

  • Common EEG abnormalities in preterm infants include seizures, sharp waves, and suppression patterns.
  • Specific EEG waveforms like delta brush and asymmetries indicate brain injury.
  • Distinct EEG patterns are associated with intraventricular hemorrhage, periventricular leukomalacia, and perinatal asphyxia.

Conclusions:

  • EEG is a vital tool for assessing brain function and detecting injuries in preterm infants.
  • Recognizing specific EEG biomarkers aids in the early identification of adverse outcomes.
  • This review provides a comprehensive resource on EEG patterns for developmental neuroscience professionals.

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