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...
- Autores:
- Tipo de recurso:
- 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
- Rights
- License
- Restringido (Acceso a grupos específicos)
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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 |
_version_ |
1814167522212052992 |