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Serial EEG recordings within a Recife-based follow-up cohort (MERG-PC) were analyzed to track background rhythms and epileptiform activity, using latent class analysis. Results describe abnormal background activity in all evaluated children, identify distinct epileptiform evolution trajectories, and link trajectory groups to structural abnormalities and differing epilepsy burdens.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/longitudinal-evolution-of-electroencephalogram-eeg-findings-over-five-years-of-follow-up-in-children-with-zika-related-microcephaly/445362/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/longitudinal-evolution-of-electroencephalogram-eeg-findings-over-five-years-of-follow-up-in-children-with-zika-related-microcephaly/445362.png","ImageObject",300,407,{"name":92,"@type":93},"moss~","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-04","2026-09-29",true,{"@type":102,"interactionType":103,"userInteractionCount":81},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the study’s main objective regarding EEG in children with Zika-related microcephaly?","Question",{"text":112,"@type":113},"To assess the longitudinal evolution of EEG findings in children with ZRM and to evaluate associations between EEG patterns and clinical and neuroimaging characteristics.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were EEG changes over time analyzed in this research?",{"text":117,"@type":113},"Serial EEG recordings were collected across specified age windows, and latent class analysis was used to identify patterns in the evolution of epileptiform activity over time.",{"name":119,"@type":110,"acceptedAnswer":120},"What EEG patterns were found to change over time, and what trajectories were identified?",{"text":121,"@type":113},"Epileptiform activity changed over time in 79.2% of children. Three trajectories were identified: (i) multifocal epileptiform activity over time, (ii) no discharges/focal activity evolving to focal/multifocal activity, and (iii) focal/multifocal activity evolving to epileptic encephalopathy patterns.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},445362,1790982748,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":81,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":41,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144},962090895452,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","Europe PMC unders uthManuscripts Europe M eC und Author Manuscripts  \n| Europe PMC Funders Group\u003Cbr>Author Manuscript\u003Cbr>Seizure. Author manuscript; available in PMC 2026 January 06. |\n| --- |\n| Published in final edited form as:\u003Cbr>Seizure. 2023 August 01; 110: 28–41. doi:10.1016/j.seizure.2023.05.019 .\u003Cbr>Longitudinal evolution of electroencephalogram (EEG): Findings over five years of follow-up in children with Zika-related microcephaly from the Microcephaly Epidemic Research Group Pediatric Cohort (2015–2020)\u003Cbr>Maria Durce C.G. Carvalhoa,b,* , Ricardo A.A. Ximenesa,b, Luciana P.A. Andrade-Valençaa,b, Ulisses R. Montarroyosa, George Tadeu Nunes Dinizc, Laura C. Rodriguesd, Elizabeth B. Brickleyd, Sophie H. Eickmannb, Thalia V. B. de Araujob, Celina M.T. Martellic, Paula F.S. da Silvaa, Demócrito de B. Miranda-Filhoa, on behalf of the Microcephaly Epidemic Research Group (MERG)\u003Cbr>a University of Pernambuco, Recife Brazil.\u003Cbr>b Federal University of Pernambuco, Recife, Brazil.\u003Cbr>cAggeu Magalhães Institute. Fiocruz-PE, Recife Brazil\u003Cbr>dLondon School of Hygiene & Tropical Medicine, London, United Kingdom.\u003Cbr>Abstract\u003Cbr>Objective: To assess the longitudinal evolution ofEEG findings in children with Zika relatedmicrocephaly (ZRM) and to evaluate the associations of these patterns with the children’s clinical and neuroimaging characteristics.\u003Cbr>Methods: As part of the follow-up ofthe Microcephaly Epidemic Research Group Pediatric Cohort (MERG-PC) in Recife, Brazil, we performed serial EEG recordings in a subgroup of children with ZRM to evaluate changes in background rhythms and epileptiform activity (EA) .\u003Cbr>Latent class analysis was used to identify patterns in the evolution of EA over time; clinical and neuroimaging findings were compared across the identified groups.\u003Cbr>Results: Out of the 72 children with ZRM who were evaluated during 190 EEGs/videoEEGs, all participants presented with abnormal background activity, 37.5% presented with an alpha-theta rhythmic activity, and 25% presented with sleep spindles, which were less commonly observed in children with epilepsy. EA changed over time in 79.2% of children, and three distinct trajectories were identified: (i) multifocal EA over time,(ii) no discharges/focal EA evolving to focal/multifocal EA, and (iii) focal/multifocal EA evolving to epileptic encephalopathy patterns (e.g., hypsarrhythmia or continuous EA in sleep). The multifocal EA over time trajectory was associated with periventricular and thalamus/basal ganglia calcifications, brainstem and corpus\u003Cbr>This work is licensed under a BY 4.0 International license.This is an open access article under the CC BY-NC-ND license ([http://](http://)[ ](http://)[creativecommons.org/licenses/by-nc-nd/4.0/](creativecommons.org/licenses/by-nc-nd/4.0/)).\u003Cbr>*Corresponding author at: Arnóbio Marques st, 310, Santo Amaro Recife PE CEP 50100-130, Oswaldo Cruz Hospital, Neurology. [mdurce2@gmail.com](mdurce2@gmail.com) (M.D.C.G. Carvalho).\u003Cbr>Declaration of Competing Interest\u003Cbr>None of the authors has any conflicts of interest to disclose |\n\nEurope PMC unders uthManuscripts Europe M eC und Author Manuscripts  \nCarvalho et al. Page 2  \ncallosum atrophy and had less focal epilepsy, whereas the children in the trajectory which evolved to epileptic encephalopathy patterns had more frequently focal epilepsy.  \nKeywords  \nElectroencephalogram; EEG; Zika; Microcephaly; Epilepsy  \n1 Introduction  \nFollowing the emergence of an epidemic of microcephaly associated with intrauterine Zika virus (ZIKV) infections in northeast Brazil, the Congenital Zika Syndrome (CZS) clinical phenotype has been characterized since 2016 [1,2,3,4,5,6,7,8,9, 10] . Children with Zika-related microcephaly (ZRM) may present with structural abnormalities that include diffuse atrophy of the brain, cerebellum and brainstem, calcifications, and malformations of cortical development [3, 11, 12] .  \nEpilepsy is a common finding in children with ZRM [2, 13, 14] . Previous ","cbCaivHIrheJARrD","https://ap.wps.com/l/cbCaivHIrheJARrD","pdf",3323050,"English","# Abstract\n## Objective\n## Methods\n## Results\n# Introduction\n## Background on ZRM and EEG\n## Knowledge gap\n## Study aims\n# Materials and methods\n## Study participants","[{\"question\":\"What is the study’s main objective regarding EEG in children with Zika-related microcephaly?\",\"answer\":\"To assess the longitudinal evolution of EEG findings in children with ZRM and to evaluate associations between EEG patterns and clinical and neuroimaging characteristics.\"},{\"question\":\"How were EEG changes over time analyzed in this research?\",\"answer\":\"Serial EEG recordings were collected across specified age windows, and latent class analysis was used to identify patterns in the evolution of epileptiform activity over time.\"},{\"question\":\"What EEG patterns were found to change over time, and what trajectories were identified?\",\"answer\":\"Epileptiform activity changed over time in 79.2% of children. Three trajectories were identified: (i) multifocal epileptiform activity over time, (ii) no discharges/focal activity evolving to focal/multifocal activity, and (iii) focal/multifocal activity evolving to epileptic encephalopathy patterns.\"}]","Longitudinal evolution of electroencephalogram (EEG) - Findings over five years of follow-up in children with Zika-related microcephaly | PDF",1790711724,76]