{"title":"Age-dependent Electroencephalogram Characteristics During Different Levels of Anesthetic Depth.","authors":"Feixiang Li, Yaoyao Dang, Xuan Zhang, Huimin Chen, Yuechun Lu, Yonghao Yu","doi":"10.1177/15500594221142680","DOIUrl":null,"url":null,"abstract":"<p><p><b>Objective</b> The monitoring of anesthetic depth based on electroencephalogram derivation is not currently adjusted for age. Here we analyze the influence of age factors on electroencephalogram characteristics. <b>Methods</b> Frontal electroencephalogram recordings were obtained from 80 adults during routine clinical anesthesia. The characteristics of electroencephalogram with age and anesthesia were observed during four kinds of anesthesia. <b>Results</b> The slow wave power, δ power, Bispectral Index (BIS) and approximate entropy can be used to distinguish different states of anesthesia (P < 0.05). In the deep and very deep anesthesia states, δ power decreased with age (P < 0.0001). In the very deep anesthesia state, θ power decreased with age (P < 0.05). In the deep and very deep anesthesia states, α power decreased with age (P = 0.0002). In the light and deep anesthesia states, β power decreased with age (P = 0.003). In the deep anesthesia state, γ power decreased with age (P = 0.002). In the very deep anesthesia state, permutation entropy increased significantly with age (P = 0.0001). In the very deep anesthesia state, BIS value increased with age (P = 0.006). The slow wave power, approximate entropy, and sample entropy did not show age-dependent changes. <b>Conclusions</b> The influence of age should be considered when using BIS and δ power to monitor the depth of anesthesia, while the influence of age should not be considered when using slow wave power and approximate entropy to monitor the depth of anesthesia.</p>","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":" ","pages":"651-656"},"PeriodicalIF":1.6000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical EEG and Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15500594221142680","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/12/12 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Objective The monitoring of anesthetic depth based on electroencephalogram derivation is not currently adjusted for age. Here we analyze the influence of age factors on electroencephalogram characteristics. Methods Frontal electroencephalogram recordings were obtained from 80 adults during routine clinical anesthesia. The characteristics of electroencephalogram with age and anesthesia were observed during four kinds of anesthesia. Results The slow wave power, δ power, Bispectral Index (BIS) and approximate entropy can be used to distinguish different states of anesthesia (P < 0.05). In the deep and very deep anesthesia states, δ power decreased with age (P < 0.0001). In the very deep anesthesia state, θ power decreased with age (P < 0.05). In the deep and very deep anesthesia states, α power decreased with age (P = 0.0002). In the light and deep anesthesia states, β power decreased with age (P = 0.003). In the deep anesthesia state, γ power decreased with age (P = 0.002). In the very deep anesthesia state, permutation entropy increased significantly with age (P = 0.0001). In the very deep anesthesia state, BIS value increased with age (P = 0.006). The slow wave power, approximate entropy, and sample entropy did not show age-dependent changes. Conclusions The influence of age should be considered when using BIS and δ power to monitor the depth of anesthesia, while the influence of age should not be considered when using slow wave power and approximate entropy to monitor the depth of anesthesia.
期刊介绍:
Clinical EEG and Neuroscience conveys clinically relevant research and development in electroencephalography and neuroscience. Original articles on any aspect of clinical neurophysiology or related work in allied fields are invited for publication.