Phase synchronization in electroencephalographic recordings prognosticates outcome in paediatric coma

Area of Science:

• Neuroscience
• Paediatric Critical Care
• Biomedical Engineering

Background:

• Brain injury is a leading cause of death and disability in children.
• Accurate outcome prediction is crucial for timely interventions but lacks a clinical model.
• Physiological signal variability, seen in heart rate, may apply to brain signals.

Purpose of the Study:

• To investigate the correlation between brain signal variability and patient outcomes after paediatric brain injury.
• To determine if electroencephalographic (EEG) phase synchrony variability can predict prognosis in children.

Main Methods:

• Retrospective analysis of scalp EEGs from children (1 month–17 years) in coma (GCS <8) post-brain injury (2000-2010).
• EEG phase synchrony evaluated using Hilbert transform; variability calculated.
• Patient outcome assessed via Paediatric Performance Category Score (PCPC) at discharge, dichotomized to good (1-3) or poor (4-6).

Main Results:

• Children with poor outcomes exhibited higher synchrony magnitude (R index) compared to those with good outcomes.
• Poor outcome group showed lower spatial complexity of synchrony patterns.
• Lower temporal variability of synchrony index values at 15 Hz was observed in children with poor outcomes.

Conclusions:

• EEG phase synchrony variability is a potential biomarker for predicting outcomes in paediatric brain injury.
• Reduced brain signal variability correlates with poorer prognosis after TBI, cardiac arrest, or stroke in children.
• This finding may inform the development of novel clinical models for early risk stratification.