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Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value
Object Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave t...
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Published in: | Neurological sciences 2023-12, Vol.44 (12), p.4247-4261 |
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container_end_page | 4261 |
container_issue | 12 |
container_start_page | 4247 |
container_title | Neurological sciences |
container_volume | 44 |
creator | Lanzone, J. Motolese, F. Ricci, L. Tecchio, F. Tombini, M. Zappasodi, F. Cruciani, A. Capone, F. Di Lazzaro, V. Assenza, G. |
description | Object
Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave the way for future research.
Methods
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the literature for papers that fitted our inclusion criteria. Rayyan QCRR was used to allow deduplication and collaborative blinded paper review. Due to multiple outcomes and non-homogeneous literature, a scoping review approach was used to address the topic.
Results
Or initial search (PubMed, Embase, Google scholar) yielded 3200 papers. After proper screening, we selected 71 papers that fitted our inclusion criteria and we developed a scoping review thar describes the current state of the art of qEEG in stroke. Notably, among selected papers 53 (74.3%) focused on spectral power; 11 (15.7%) focused on symmetry indexes, 17 (24.3%) on connectivity metrics, while 5 (7.1%) were about other metrics (e.g. detrended fluctuation analysis). Moreover, 42 (58.6%) studies were performed with standard 19 electrodes EEG caps and only a minority used high-definition EEG.
Conclusions
We systematically assessed major findings on qEEG and stroke, evidencing strengths and potential pitfalls of this promising branch of research. |
doi_str_mv | 10.1007/s10072-023-06981-9 |
format | article |
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Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave the way for future research.
Methods
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the literature for papers that fitted our inclusion criteria. Rayyan QCRR was used to allow deduplication and collaborative blinded paper review. Due to multiple outcomes and non-homogeneous literature, a scoping review approach was used to address the topic.
Results
Or initial search (PubMed, Embase, Google scholar) yielded 3200 papers. After proper screening, we selected 71 papers that fitted our inclusion criteria and we developed a scoping review thar describes the current state of the art of qEEG in stroke. Notably, among selected papers 53 (74.3%) focused on spectral power; 11 (15.7%) focused on symmetry indexes, 17 (24.3%) on connectivity metrics, while 5 (7.1%) were about other metrics (e.g. detrended fluctuation analysis). Moreover, 42 (58.6%) studies were performed with standard 19 electrodes EEG caps and only a minority used high-definition EEG.
Conclusions
We systematically assessed major findings on qEEG and stroke, evidencing strengths and potential pitfalls of this promising branch of research.</description><identifier>ISSN: 1590-1874</identifier><identifier>EISSN: 1590-3478</identifier><identifier>DOI: 10.1007/s10072-023-06981-9</identifier><identifier>PMID: 37542545</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>EEG ; Electroencephalography ; Medicine ; Medicine & Public Health ; Neurology ; Neuroradiology ; Neurosciences ; Neurosurgery ; Psychiatry ; Review Article ; Stroke ; Systematic review</subject><ispartof>Neurological sciences, 2023-12, Vol.44 (12), p.4247-4261</ispartof><rights>Fondazione Società Italiana di Neurologia 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2023. Fondazione Società Italiana di Neurologia.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-d5b43ffc9c39ed66c393d43e72b673ee27f98d9263de8260ee90429c716428063</citedby><cites>FETCH-LOGICAL-c375t-d5b43ffc9c39ed66c393d43e72b673ee27f98d9263de8260ee90429c716428063</cites><orcidid>0000-0001-7217-6281</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37542545$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lanzone, J.</creatorcontrib><creatorcontrib>Motolese, F.</creatorcontrib><creatorcontrib>Ricci, L.</creatorcontrib><creatorcontrib>Tecchio, F.</creatorcontrib><creatorcontrib>Tombini, M.</creatorcontrib><creatorcontrib>Zappasodi, F.</creatorcontrib><creatorcontrib>Cruciani, A.</creatorcontrib><creatorcontrib>Capone, F.</creatorcontrib><creatorcontrib>Di Lazzaro, V.</creatorcontrib><creatorcontrib>Assenza, G.</creatorcontrib><title>Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value</title><title>Neurological sciences</title><addtitle>Neurol Sci</addtitle><addtitle>Neurol Sci</addtitle><description>Object
Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave the way for future research.
Methods
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the literature for papers that fitted our inclusion criteria. Rayyan QCRR was used to allow deduplication and collaborative blinded paper review. Due to multiple outcomes and non-homogeneous literature, a scoping review approach was used to address the topic.
Results
Or initial search (PubMed, Embase, Google scholar) yielded 3200 papers. After proper screening, we selected 71 papers that fitted our inclusion criteria and we developed a scoping review thar describes the current state of the art of qEEG in stroke. Notably, among selected papers 53 (74.3%) focused on spectral power; 11 (15.7%) focused on symmetry indexes, 17 (24.3%) on connectivity metrics, while 5 (7.1%) were about other metrics (e.g. detrended fluctuation analysis). Moreover, 42 (58.6%) studies were performed with standard 19 electrodes EEG caps and only a minority used high-definition EEG.
Conclusions
We systematically assessed major findings on qEEG and stroke, evidencing strengths and potential pitfalls of this promising branch of research.</description><subject>EEG</subject><subject>Electroencephalography</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Neurology</subject><subject>Neuroradiology</subject><subject>Neurosciences</subject><subject>Neurosurgery</subject><subject>Psychiatry</subject><subject>Review Article</subject><subject>Stroke</subject><subject>Systematic review</subject><issn>1590-1874</issn><issn>1590-3478</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kU2LFDEQhoMo7rr6BzxIwIuX1nx1OvEmy7gKCyLoOWTS1WPW7mRN0rPsv7fGGRU8eEkVqafequQl5Dlnrzljw5t6OEXHhOyYtoZ39gE5571lnVSDeXjKuRnUGXlS6w1jjCsuH5MzOfRK9Ko_J-3z6lOLzbe4B7qAr2uBSvNE2zegmLaYdnSzuaIx0dpK_g5vqaf1vjZYsCkgs49wR3OiYY4pBj_TkEuBGat46dNIb0vepVwP9N7PKzwljyY_V3h2ihfk6_vNl8sP3fWnq4-X7667gAu2buy3Sk5TsEFaGLXGIEclYRBbPUgAMUzWjFZoOYIRmgFYpoQNA9dKGKblBXl11MUFfqz4FrfEGmCefYK8VieM0lYY_EZEX_6D3uS1JNwOKWOZ7fteIiWOVCi51gKTuy1x8eXeceYObrijJw49cb88cRabXpyk1-0C45-W3yYgII9AxVLaQfk7-z-yPwFIT5eB</recordid><startdate>20231201</startdate><enddate>20231201</enddate><creator>Lanzone, J.</creator><creator>Motolese, F.</creator><creator>Ricci, L.</creator><creator>Tecchio, F.</creator><creator>Tombini, M.</creator><creator>Zappasodi, F.</creator><creator>Cruciani, A.</creator><creator>Capone, F.</creator><creator>Di Lazzaro, V.</creator><creator>Assenza, G.</creator><general>Springer International Publishing</general><general>Springer Nature B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>K9-</scope><scope>K9.</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-7217-6281</orcidid></search><sort><creationdate>20231201</creationdate><title>Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value</title><author>Lanzone, J. ; Motolese, F. ; Ricci, L. ; Tecchio, F. ; Tombini, M. ; Zappasodi, F. ; Cruciani, A. ; Capone, F. ; Di Lazzaro, V. ; Assenza, G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-d5b43ffc9c39ed66c393d43e72b673ee27f98d9263de8260ee90429c716428063</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>EEG</topic><topic>Electroencephalography</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Neurology</topic><topic>Neuroradiology</topic><topic>Neurosciences</topic><topic>Neurosurgery</topic><topic>Psychiatry</topic><topic>Review Article</topic><topic>Stroke</topic><topic>Systematic review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lanzone, J.</creatorcontrib><creatorcontrib>Motolese, F.</creatorcontrib><creatorcontrib>Ricci, L.</creatorcontrib><creatorcontrib>Tecchio, F.</creatorcontrib><creatorcontrib>Tombini, M.</creatorcontrib><creatorcontrib>Zappasodi, F.</creatorcontrib><creatorcontrib>Cruciani, A.</creatorcontrib><creatorcontrib>Capone, F.</creatorcontrib><creatorcontrib>Di Lazzaro, V.</creatorcontrib><creatorcontrib>Assenza, G.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Psychology Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Neurological sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lanzone, J.</au><au>Motolese, F.</au><au>Ricci, L.</au><au>Tecchio, F.</au><au>Tombini, M.</au><au>Zappasodi, F.</au><au>Cruciani, A.</au><au>Capone, F.</au><au>Di Lazzaro, V.</au><au>Assenza, G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value</atitle><jtitle>Neurological sciences</jtitle><stitle>Neurol Sci</stitle><addtitle>Neurol Sci</addtitle><date>2023-12-01</date><risdate>2023</risdate><volume>44</volume><issue>12</issue><spage>4247</spage><epage>4261</epage><pages>4247-4261</pages><issn>1590-1874</issn><eissn>1590-3478</eissn><abstract>Object
Quantitative electroencephalography (qEEG) has shown promising results as a predictor of clinical impairment in stroke. We systematically reviewed published papers that focus on qEEG metrics in the resting EEG of patients with mono-hemispheric stroke, to summarize current knowledge and pave the way for future research.
Methods
Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched the literature for papers that fitted our inclusion criteria. Rayyan QCRR was used to allow deduplication and collaborative blinded paper review. Due to multiple outcomes and non-homogeneous literature, a scoping review approach was used to address the topic.
Results
Or initial search (PubMed, Embase, Google scholar) yielded 3200 papers. After proper screening, we selected 71 papers that fitted our inclusion criteria and we developed a scoping review thar describes the current state of the art of qEEG in stroke. Notably, among selected papers 53 (74.3%) focused on spectral power; 11 (15.7%) focused on symmetry indexes, 17 (24.3%) on connectivity metrics, while 5 (7.1%) were about other metrics (e.g. detrended fluctuation analysis). Moreover, 42 (58.6%) studies were performed with standard 19 electrodes EEG caps and only a minority used high-definition EEG.
Conclusions
We systematically assessed major findings on qEEG and stroke, evidencing strengths and potential pitfalls of this promising branch of research.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>37542545</pmid><doi>10.1007/s10072-023-06981-9</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-7217-6281</orcidid></addata></record> |
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subjects | EEG Electroencephalography Medicine Medicine & Public Health Neurology Neuroradiology Neurosciences Neurosurgery Psychiatry Review Article Stroke Systematic review |
title | Quantitative measures of the resting EEG in stroke: a systematic review on clinical correlation and prognostic value |
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