无意识
异丙酚
脑电图
医学
麻醉
连贯性(哲学赌博策略)
听力学
精神科
物理
量子力学
作者
Johanna M. Lee,Oluwaseun Akeju,Kristina Terzakis,Kara J. Pavone,Hao Deng,Timothy T. Houle,Paul G. Firth,Erik S. Shank,Emery N. Brown,Patrick L. Purdon
出处
期刊:Anesthesiology
[Ovid Technologies (Wolters Kluwer)]
日期:2017-08-01
卷期号:127 (2): 293-306
被引量:59
标识
DOI:10.1097/aln.0000000000001717
摘要
Abstract Background In adults, frontal electroencephalogram patterns observed during propofol-induced unconsciousness consist of slow oscillations (0.1 to 1 Hz) and coherent alpha oscillations (8 to 13 Hz). Given that the nervous system undergoes significant changes during development, anesthesia-induced electroencephalogram oscillations in children may differ from those observed in adults. Therefore, we investigated age-related changes in frontal electroencephalogram power spectra and coherence during propofol-induced unconsciousness. Methods We analyzed electroencephalogram data recorded during propofol-induced unconsciousness in patients between 0 and 21 yr of age (n = 97), using multitaper spectral and coherence methods. We characterized power and coherence as a function of age using multiple linear regression analysis and within four age groups: 4 months to 1 yr old (n = 4), greater than 1 to 7 yr old (n = 16), greater than 7 to 14 yr old (n = 30), and greater than 14 to 21 yr old (n = 47). Results Total electroencephalogram power (0.1 to 40 Hz) peaked at approximately 8 yr old and subsequently declined with increasing age. For patients greater than 1 yr old, the propofol-induced electroencephalogram structure was qualitatively similar regardless of age, featuring slow and coherent alpha oscillations. For patients under 1 yr of age, frontal alpha oscillations were not coherent. Conclusions Neurodevelopmental processes that occur throughout childhood, including thalamocortical development, may underlie age-dependent changes in electroencephalogram power and coherence during anesthesia. These age-dependent anesthesia-induced electroencephalogram oscillations suggest a more principled approach to monitoring brain states in pediatric patients.
科研通智能强力驱动
Strongly Powered by AbleSci AI