BACKGROUND: The characteristics of the electroencephalogram (EEG) during anesthesia in children are poorly described. An understanding of the EEG during anesthesia may help explain and predict the performance of EEG-derived depth of anesthesia monitors in children. This study aims to describe the association between age and some basic characteristics of the EEG during nonstandardized anesthesia in children and infants. METHODS: Sixty-four children aged 9 days to 12 years were enrolled in this observational physiological study. Anesthesia was given at the discretion of the anesthetist. EEG was recorded from after induction to emergence using a BRM2 brain monitor ''BrainZ Instruments, Auckland, New Zealand'' in parietal and frontal montages. For comparison, 90% spectral edge frequency (SEF-90) and power were determined at three points (equilibrium during anesthesia, when the volatile agent was discontinued and at emergence), and children were divided into three age groups (0-6 months, 6-24 months and 2-12 years). RESULTS: Fifty-seven children had artifact-free EEG data. From equilibrium to emergence the mean forehead power decreased substantially in children aged 2-12 years (3171-153 microV(2), P < 0.001) and 6-24 months (756-140 microV(2), P < 0.001) but no difference was found in infants aged 0-6 months (93-63 microV(2), P = 0.4). From equilibrium to emergence mean forehead spectral edge frequency increased in children aged 2-12 years (10.8-13.7 Hz, P = 0.01) but no change was found in children aged 6-24 months (12.7-12.7 Hz, P = 0.9) or 0-6 months (9.45-7.26 Hz, P = 0.08). Throughout emergence, infants demonstrated a discontinuous EEG pattern with intermittent bursts separated with low amplitude. CONCLUSIONS: During anesthesia, the EEG in infants is fundamentally different from the EEG in older children. This study supports the need for specific infant-derived algorithms if EEG-derived anesthesia depth monitors are to be used in infants.
BACKGROUND: The characteristics of the electroencephalogram (EEG) during anesthesia in children are poorly described. An understanding of the EEG during anesthesia may help explain and predict the performance of EEG-derived depth of anesthesia monitors in children. This study aims to describe the association between age and some basic characteristics of the EEG during nonstandardized anesthesia in children and infants. METHODS: Sixty-four children aged 9 days to 12 years were enrolled in this observational physiological study. Anesthesia was given at the discretion of the anesthetist. EEG was recorded from after induction to emergence using a BRM2 brain monitor ''BrainZ Instruments, Auckland, New Zealand'' in parietal and frontal montages. For comparison, 90% spectral edge frequency (SEF-90) and power were determined at three points (equilibrium during anesthesia, when the volatile agent was discontinued and at emergence), and children were divided into three age groups (0-6 months, 6-24 months and 2-12 years). RESULTS: Fifty-seven children had artifact-free EEG data. From equilibrium to emergence the mean forehead power decreased substantially in children aged 2-12 years (3171-153 microV(2), P < 0.001) and 6-24 months (756-140 microV(2), P < 0.001) but no difference was found in infants aged 0-6 months (93-63 microV(2), P = 0.4). From equilibrium to emergence mean forehead spectral edge frequency increased in children aged 2-12 years (10.8-13.7 Hz, P = 0.01) but no change was found in children aged 6-24 months (12.7-12.7 Hz, P = 0.9) or 0-6 months (9.45-7.26 Hz, P = 0.08). Throughout emergence, infants demonstrated a discontinuous EEG pattern with intermittent bursts separated with low amplitude. CONCLUSIONS: During anesthesia, the EEG in infants is fundamentally different from the EEG in older children. This study supports the need for specific infant-derived algorithms if EEG-derived anesthesia depth monitors are to be used in infants.
Authors: O Akeju; K J Pavone; J A Thum; P G Firth; M B Westover; M Puglia; E S Shank; E N Brown; P L Purdon Journal: Br J Anaesth Date: 2015-07 Impact factor: 9.166
Authors: Laura Cornelissen; Carolina Donado; Johanna M Lee; Norah E Liang; Ian Mills; Andrea Tou; Aykut Bilge; Charles B Berde Journal: Eur J Anaesthesiol Date: 2018-01 Impact factor: 4.330
Authors: Lisanne J Stolwijk; Lauren C Weeke; Linda S de Vries; Maud Y A van Herwaarden; David C van der Zee; Desiree B M van der Werff; Manon J N L Benders; Mona Toet; Petra M A Lemmers Journal: PLoS One Date: 2017-08-31 Impact factor: 3.240