A Retrospective Study on Correlations Between EEG Signals (N20, Spectral Entropy, and Alpha Variability) and...

Area of Science:

• Neuroscience
• Clinical Neurology
• Biomedical Engineering

Background:

• Traumatic brain injury (TBI) poses significant challenges in predicting patient outcomes.
• Early and accurate prognostic indicators are crucial for effective clinical management of TBI patients.

Purpose of the Study:

• To investigate the correlation between electroencephalography (EEG) signals and somatosensory evoked potential (SSEP) parameters with clinical outcomes in TBI patients.
• To identify reliable biomarkers for predicting prognosis in TBI.

Main Methods:

• 174 TBI patients were analyzed, assessing quantitative EEG parameters (spectral entropy, alpha variability, relative beta energy) and SSEP N20 amplitude within 7-14 days post-onset.
• Patients were categorized into good and poor prognosis groups based on Glasgow Outcome Scale (GOS) scores at six months.

Main Results:

• A significant correlation was observed between Synek EEG grading and 6-month GOS scores (ρ = -0.709, p < 0.001).
• Good prognosis TBI patients exhibited higher N20 amplitudes, spectral entropy, and alpha variability, with lower relative beta energy compared to poor prognosis patients.
• SSEP N20 amplitude showed the highest predictive performance, with a threshold of >1.975 μV accurately predicting good outcomes (93.3% sensitivity, 94.1% specificity).

Conclusions:

• SSEP N20 amplitude serves as a reliable and sensitive predictor for TBI prognosis.
• These findings offer valuable insights for clinical decision-making and management strategies in TBI care.