Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database

Objective To assess interrater agreement based on majority voting in visual scoring of neonatal seizures. Methods An online platform was designed based on a multicentre seizure EEG-database. Consensus decision based on ‘majority voting’ and interrater agreement was estimated using Fleiss’ Kappa. The...

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Fecha de publicación:
2017
Institución:
Universidad del Rosario
Repositorio:
Repositorio EdocUR - U. Rosario
Idioma:
eng
OAI Identifier:
oai:repository.urosario.edu.co:10336/25886
Acceso en línea:
https://doi.org/10.1016/j.clinph.2017.06.250
https://repository.urosario.edu.co/handle/10336/25886
Palabra clave:
Electrographic seizuresInterrater agreement
Neonatal multichannel EEG
Consensus agreement
Seizure detection algorithms
Neoguard
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oai_identifier_str oai:repository.urosario.edu.co:10336/25886
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling f60e027f-e1b4-4950-90e1-a87b38199290-1d91ac08f-25ec-4d13-8363-eafcb342b237-100e98a12-b91d-41fa-bda9-a90a09246209-120d7a0a6-e291-4678-a9e0-dcea19ef16a9-18e13b2c2-45ac-4870-9908-573a59c749f2-1ac11dc6c-f78e-4f39-833d-ff2bea71169e-18ee55992-3ecd-4596-be87-7b0965be3d03-14a7d9080-7cd0-43bf-af01-7b1fa194e805-1fe4568d9-dfc2-480b-924e-911cb041f317-114139512-1c2b88cc8-bb49-4caf-acc4-b0320c87d672-1373c77e3-5093-43fd-831b-0db88cefa50d-155320cda-97a5-498e-9555-cec06026ceda-12020-08-06T16:20:08Z2020-08-06T16:20:08Z2017Objective To assess interrater agreement based on majority voting in visual scoring of neonatal seizures. Methods An online platform was designed based on a multicentre seizure EEG-database. Consensus decision based on ‘majority voting’ and interrater agreement was estimated using Fleiss’ Kappa. The influences of different factors on agreement were determined. Results 1919 Events extracted from 280 h EEG of 71 neonates were reviewed by 4 raters. Majority voting was applied to assign a seizure/non-seizure classification. 44% of events were classified with high, 36% with moderate, and 20% with poor agreement, resulting in a Kappa value of 0.39. 68% of events were labelled as seizures, and in 46%, all raters were convinced about electrographic seizures. The most common seizure duration was <30 s. Raters agreed best for seizures lasting 60–120 s. There was a significant difference in electrographic characteristics of seizures versus dubious events, with seizures having longer duration, higher power and amplitude. Conclusions There is a wide variability in identifying rhythmic ictal and non-ictal EEG events, and only the most robust ictal patterns are consistently agreed upon. Database composition and electrographic characteristics are important factors that influence interrater agreement. Significance The use of well-described databases and input of different experts will improve neonatal EEG interpretation and help to develop uniform seizure definitions, useful for evidence-based studies of seizure recognition and managementapplication/pdfhttps://doi.org/10.1016/j.clinph.2017.06.250ISSN: 1388-2457https://repository.urosario.edu.co/handle/10336/25886engInternational Federation of Clinical NeurophysiologyElsevier1745No. 91737Clinical Neurophysiology, Electroencephalography and Clinical Neurophysiology - Electromyography and Motor ControlVol. 128Clinical Neurophysiology, ISSN: 1388-2457, Vol.128, No.9 (September 2017); pp.1737-1745https://www.sciencedirect.com/science/article/abs/pii/S1388245717304777Restringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecClinical Neurophysiology, Electroencephalography and Clinical Neurophysiology - Electromyography and Motor Controlinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURElectrographic seizuresInterrater agreementNeonatal multichannel EEGConsensus agreementSeizure detection algorithmsNeoguardInterrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG databaseAcuerdo entre evaluadores en la puntuación visual de las convulsiones neonatales basadas en la votación mayoritaria en un sistema basado en la web: la base de datos Neoguard EEGarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Dereymaeker, AnneleenAnsari, Amir H.Jansen, KatrienJ.Cherian, PerumpillichiraVervisch, JanGovaert, PaulWispelaereg, LeenDeDielman, CharlotteMatic, VladimirCaicedo Dorado, AlexanderDe Vosk, MaartenVan Huffel, SabineNaulaers, Gunnar10336/25886oai:repository.urosario.edu.co:10336/258862021-06-03 00:50:20.131https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co
dc.title.spa.fl_str_mv Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
dc.title.TranslatedTitle.spa.fl_str_mv Acuerdo entre evaluadores en la puntuación visual de las convulsiones neonatales basadas en la votación mayoritaria en un sistema basado en la web: la base de datos Neoguard EEG
title Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
spellingShingle Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
Electrographic seizuresInterrater agreement
Neonatal multichannel EEG
Consensus agreement
Seizure detection algorithms
Neoguard
title_short Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
title_full Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
title_fullStr Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
title_full_unstemmed Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
title_sort Interrater agreement in visual scoring of neonatal seizures based on majority voting on a web-based system: The Neoguard EEG database
dc.subject.keyword.spa.fl_str_mv Electrographic seizuresInterrater agreement
Neonatal multichannel EEG
Consensus agreement
Seizure detection algorithms
Neoguard
topic Electrographic seizuresInterrater agreement
Neonatal multichannel EEG
Consensus agreement
Seizure detection algorithms
Neoguard
description Objective To assess interrater agreement based on majority voting in visual scoring of neonatal seizures. Methods An online platform was designed based on a multicentre seizure EEG-database. Consensus decision based on ‘majority voting’ and interrater agreement was estimated using Fleiss’ Kappa. The influences of different factors on agreement were determined. Results 1919 Events extracted from 280 h EEG of 71 neonates were reviewed by 4 raters. Majority voting was applied to assign a seizure/non-seizure classification. 44% of events were classified with high, 36% with moderate, and 20% with poor agreement, resulting in a Kappa value of 0.39. 68% of events were labelled as seizures, and in 46%, all raters were convinced about electrographic seizures. The most common seizure duration was <30 s. Raters agreed best for seizures lasting 60–120 s. There was a significant difference in electrographic characteristics of seizures versus dubious events, with seizures having longer duration, higher power and amplitude. Conclusions There is a wide variability in identifying rhythmic ictal and non-ictal EEG events, and only the most robust ictal patterns are consistently agreed upon. Database composition and electrographic characteristics are important factors that influence interrater agreement. Significance The use of well-described databases and input of different experts will improve neonatal EEG interpretation and help to develop uniform seizure definitions, useful for evidence-based studies of seizure recognition and management
publishDate 2017
dc.date.created.spa.fl_str_mv 2017
dc.date.accessioned.none.fl_str_mv 2020-08-06T16:20:08Z
dc.date.available.none.fl_str_mv 2020-08-06T16:20:08Z
dc.type.eng.fl_str_mv article
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.spa.spa.fl_str_mv Artículo
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1016/j.clinph.2017.06.250
dc.identifier.issn.none.fl_str_mv ISSN: 1388-2457
dc.identifier.uri.none.fl_str_mv https://repository.urosario.edu.co/handle/10336/25886
url https://doi.org/10.1016/j.clinph.2017.06.250
https://repository.urosario.edu.co/handle/10336/25886
identifier_str_mv ISSN: 1388-2457
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationEndPage.none.fl_str_mv 1745
dc.relation.citationIssue.none.fl_str_mv No. 9
dc.relation.citationStartPage.none.fl_str_mv 1737
dc.relation.citationTitle.none.fl_str_mv Clinical Neurophysiology, Electroencephalography and Clinical Neurophysiology - Electromyography and Motor Control
dc.relation.citationVolume.none.fl_str_mv Vol. 128
dc.relation.ispartof.spa.fl_str_mv Clinical Neurophysiology, ISSN: 1388-2457, Vol.128, No.9 (September 2017); pp.1737-1745
dc.relation.uri.spa.fl_str_mv https://www.sciencedirect.com/science/article/abs/pii/S1388245717304777
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.acceso.spa.fl_str_mv Restringido (Acceso a grupos específicos)
rights_invalid_str_mv Restringido (Acceso a grupos específicos)
http://purl.org/coar/access_right/c_16ec
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv International Federation of Clinical Neurophysiology
Elsevier
dc.source.spa.fl_str_mv Clinical Neurophysiology, Electroencephalography and Clinical Neurophysiology - Electromyography and Motor Control
institution Universidad del Rosario
dc.source.instname.none.fl_str_mv instname:Universidad del Rosario
dc.source.reponame.none.fl_str_mv reponame:Repositorio Institucional EdocUR
repository.name.fl_str_mv Repositorio institucional EdocUR
repository.mail.fl_str_mv edocur@urosario.edu.co
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