Electroencephalography and Anesthetic Depth in Children Under 2 Years of Age: A Prospective Observational Study.

Abstract

Background: Processed electroencephalogram (EEG) indices are widely used to monitor anesthetic depth. However, their reliability in children under 2 years of age remains questionable. During anesthesia maintenance in this age group, processed EEG indices frequently exhibit unexpectedly elevated values that exceed the intended target range.

Aim: This study aimed to identify EEG spectral parameters associated with false positive elevations in processed EEG indices and investigate their differences from true positive elevations during emergence.

Methods: This prospective observational study included 50 children aged 4-24 months undergoing general anesthesia. Bispectral index (BIS), patient state index (PSi), and raw EEG were continuously recorded throughout anesthesia. False positive was defined as elevated processed EEG indices when end-tidal sevoflurane concentration was maintained at 0.7-1.3 minimum alveolar concentration, with heart rate and mean blood pressure between 80% and 120% of baseline values. We analyzed EEG power spectra and band power values during periods of false positives and compared them with those of true positives during emergence. Bonferroni-corrected p < 0.05 was considered significant.

Results: False positives in processed EEG indices were observed in 35 (70%) of the children during anesthesia maintenance, occupying 28% of the maintenance phase. These false positives were associated with decreased power in delta (269-174 dB) and theta (115-97 dB) bands, but widespread increases in alpha and beta bands, resulting in elevated spectral edge frequency (19-22 Hz). Notably, EEG band power during false positives significantly differed from those observed during emergence (delta: 52 dB, theta: 38 dB) (all p < 0.001).

Conclusions: Processed EEG indices may exhibit unexpectedly elevated values during anesthesia maintenance in children under 2 years of age. Quantitative assessments derived from raw EEG data may improve the evaluation of anesthetic depth in this population.