Electroencephalographic Evaluation in Fibromyalgia: A Systematic Review.

IF 1.6 4区医学 Q3 CLINICAL NEUROLOGY

Clinical EEG and Neuroscience Pub Date : 2024-01-01 Epub Date: 2021-03-17 DOI:10.1177/1550059421997128

Géssika Araújo de Melo, Marcela Laís Lima Holmes Madruga, Nelson Torro

{"title":"Electroencephalographic Evaluation in Fibromyalgia: A Systematic Review.","authors":"Géssika Araújo de Melo, Marcela Laís Lima Holmes Madruga, Nelson Torro","doi":"10.1177/1550059421997128","DOIUrl":null,"url":null,"abstract":"Introduction. The evaluation of individuals with fibromyalgia is challenging. Electroencephalography is a promising resource for identifying physiological biomarkers in fibromyalgia, contributing to its diagnosis. Objective. To review studies involving the use of electroencephalography to evaluate individuals with fibromyalgia. Method. A systematic review of studies published in the PubMed, Lilacs, and SciELO databases from 2001 to 2020 was conducted. The keywords used were electroencephalogram, electroencephalography, and fibromyalgia. The database search complied with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria. Results. A total of 136 articles were identified after a database search using the keywords \"fibromyalgia\" AND \"electroencephalography\", and 131 articles were found using the keywords \"fibromyalgia\" AND \"electroencephalogram\" (EEG). In the end, 20 articles remained after applying the exclusion criteria. The data was organized into subcategories related to the form of use, protocols, electroencephalographic findings in patients with fibromyalgia, and the EEG analysis method. Conclusion. Electroencephalography is a promising method for identifying and characterizing biomarkers for fibromyalgia.","PeriodicalId":10682,"journal":{"name":"Clinical EEG and Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1550059421997128","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical EEG and Neuroscience","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/1550059421997128","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/3/17 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}

引用次数: 4

Abstract

Introduction. The evaluation of individuals with fibromyalgia is challenging. Electroencephalography is a promising resource for identifying physiological biomarkers in fibromyalgia, contributing to its diagnosis. Objective. To review studies involving the use of electroencephalography to evaluate individuals with fibromyalgia. Method. A systematic review of studies published in the PubMed, Lilacs, and SciELO databases from 2001 to 2020 was conducted. The keywords used were electroencephalogram, electroencephalography, and fibromyalgia. The database search complied with the preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria. Results. A total of 136 articles were identified after a database search using the keywords "fibromyalgia" AND "electroencephalography", and 131 articles were found using the keywords "fibromyalgia" AND "electroencephalogram" (EEG). In the end, 20 articles remained after applying the exclusion criteria. The data was organized into subcategories related to the form of use, protocols, electroencephalographic findings in patients with fibromyalgia, and the EEG analysis method. Conclusion. Electroencephalography is a promising method for identifying and characterizing biomarkers for fibromyalgia.

查看原文本刊更多论文

纤维肌痛的脑电图评价:系统综述。

介绍。对纤维肌痛患者的评估是具有挑战性的。脑电图是识别纤维肌痛生理生物标志物的一种有前途的资源，有助于其诊断。目标。回顾涉及使用脑电图评估纤维肌痛个体的研究。方法。对2001年至2020年在PubMed、Lilacs和SciELO数据库中发表的研究进行了系统回顾。关键词为脑电图、脑电图、纤维肌痛。数据库检索符合系统评价和荟萃分析(PRISMA)标准的首选报告项目。结果。以“纤维肌痛”和“脑电图”为关键词检索数据库，共检索到136篇文章;以“纤维肌痛”和“脑电图”为关键词检索到131篇文章。应用排除标准后，最终剩下20篇文章。数据被组织成与使用形式、方案、纤维肌痛患者的脑电图结果和脑电图分析方法相关的亚类。结论。脑电图是一种很有前途的方法来识别和表征纤维肌痛的生物标志物。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Clinical EEG and Neuroscience 医学-临床神经学

CiteScore

5.20

自引率

5.00%

发文量

审稿时长

>12 weeks

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.