Characterizing electroencephalogram dynamics during sedation withdrawal: Insights into cortical recovery following
Mathieu Dhoisne1,2, Philippe Derambure1,2, Arnaud Delval1,2
1Department of Clinical Neurophysiology, Lille University Hospital, Lille, France.
Objective:
Characterize electroencephalogram (EEG) dynamics during propofol withdrawal in patients with generalized convulsive status epilepticus (GCSE) and explore their association with functional outcomes.
Methods:
We conducted a retrospective cohort study of adult patients with GCSE who received continuous EEG monitoring and propofol sedation. EEG data were analyzed during two predefined periods: during sedation (0.5-1.5 mg/kg/h) and 4 h after complete sedation withdrawal. Preprocessed EEG signals underwent spectral and complexity analyses, including relative spectral power across frequency bands, alpha-delta ratio, median frequency (MF), spectral edge frequency 85% (SEF85), and sample entropy. Principal component analysis was applied to EEG trajectory vectors for dimensionality reduction; hierarchical clustering was used to identify distinct evolution patterns during sedation withdrawal. Associations between EEG patterns, SE duration, and clinical outcomes were assessed.
Results:
Twenty-one patients were included. At the population level, EEG features shifted toward faster and more complex activity after sedation withdrawal, with decreased delta power, increased theta, alpha, and beta power, and greater signal complexity. Clustering analysis identified two distinct EEG trajectories: one subgroup (24%) showed marked recovery of cortical dynamics with significant increases in frequency metrics and entropy, while the other (76%) demonstrated minimal changes, with persistent delta-band dominance and low complexity. Longer SE duration was significantly associated with the minimal-change group (p = 0.007). No significant differences in functional outcomes were observed between groups.
Significance:
EEG dynamics during propofol withdrawal in patients with GCSE evolve along distinct trajectories. Two distinct EEG trajectories emerged: one toward normalization and another with persistently slow, low-complexity patterns. The majority of patients did not normalize their EEG after sedation withdrawal. Notably, patients with prolonged GCSE were overrepresented in the group lacking EEG recovery. However, these trajectories could not be correlated with functional prognosis. These findings underscore the potential of early EEG trajectories as markers of cerebral recovery.
Plain Language Summary:
We studied how brain activity changes after stopping the sedative propofol in adults treated for severe, long-lasting seizures. Most patients showed little improvement in their brain activity after sedation was stopped, while a smaller group showed signs of recovery. Patients whose seizures lasted longer were more likely to have little or no improvement in their brain activity patterns. These early brain activity patterns did not predict long-term functional outcomes but may help identify how the brain is recovering after severe seizures.
