{"title":"The Value of Long-term Video EEG Monitoring to Diagnose and Track Childhood Epilepsy.","authors":"Mahmood Mohammadi, Reza Shervin Badv, Zahra Rezaei, Mahmoodreza Ashrafi, Fatemeh Naeemi","doi":"10.22037/ijcn.v18i1.43012","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Long-term video-EEG monitoring (LTM) is a new technique to assess and track fluctuations, classify seizures, identify epileptic syndromes, and determine the number of seizures and epilepsy-simulating disorders. The present study aims to evaluate the concordance of traditional EEG and LTM in assessing childhood epilepsy.</p><p><strong>Materials & methods: </strong>This cross-sectional before-after study was performed on 120 children with epilepsy who were referred to the Epilepsy Monitoring Unit (EMU) at the Children's Medical Center between September 2021 and September 2022 and were monitored for at least eight hours in this unit. The source of the study information collection was the patients' recorded files. A neurologist reviewed the primary EEGs, and two experts blindly reviewed and interpreted the patients' LTMs under a clinical neurophysiologist's supervision.</p><p><strong>Results: </strong>The diagnoses changed after employing LTM in most children with epilepsy. Based on the diagnostic agreement analysis between EEG and LTM, the coefficient value for LTM was calculated at -0.37 (p= 0.229), showing that LTM has significantly expanded patients' diagnoses and care plans.</p><p><strong>Conclusion: </strong>The use of LTM improves the diagnosis, classification, and monitoring of epilepsy in affected children and can be a reliable supplement to EEG in some instances.</p>","PeriodicalId":14537,"journal":{"name":"Iranian Journal of Child Neurology","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10874508/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Iranian Journal of Child Neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22037/ijcn.v18i1.43012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/18 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: Long-term video-EEG monitoring (LTM) is a new technique to assess and track fluctuations, classify seizures, identify epileptic syndromes, and determine the number of seizures and epilepsy-simulating disorders. The present study aims to evaluate the concordance of traditional EEG and LTM in assessing childhood epilepsy.
Materials & methods: This cross-sectional before-after study was performed on 120 children with epilepsy who were referred to the Epilepsy Monitoring Unit (EMU) at the Children's Medical Center between September 2021 and September 2022 and were monitored for at least eight hours in this unit. The source of the study information collection was the patients' recorded files. A neurologist reviewed the primary EEGs, and two experts blindly reviewed and interpreted the patients' LTMs under a clinical neurophysiologist's supervision.
Results: The diagnoses changed after employing LTM in most children with epilepsy. Based on the diagnostic agreement analysis between EEG and LTM, the coefficient value for LTM was calculated at -0.37 (p= 0.229), showing that LTM has significantly expanded patients' diagnoses and care plans.
Conclusion: The use of LTM improves the diagnosis, classification, and monitoring of epilepsy in affected children and can be a reliable supplement to EEG in some instances.