OBJECTIVE: There are numerous distinctive benign electroencephalographic (EEG) patterns which are morphologically epileptiform but are non-epileptic. The aim of this study was to determine the prevalence of different benign epileptiform variants (BEVs) among subjects who underwent routine EEG recordings in a large EEG laboratory over 35 years. METHODS: We retrospectively studied the prevalence of BEVs among 35,249 individuals who underwent outpatient EEG recordings at London Health Sciences Centre in London, Ontario, Canada between January 1, 1972 and December 31, 2007. The definitions of the Committee on Terminology of the International Federation of Societies for EEG and Clinical Neurophysiology (IFSECN) were used to delineate epileptiform patterns (Chatrian et al. A glossary of terms most commonly used by clinical electroencephlographers. Electroenceph Clin Neurophysiol 1974;37:538-48) and the descriptions of Klass and Westmoreland [Klass DW, Westmoreland BF. Nonepileptogenic epileptiform electroenephalographic activity. Ann Neurol 1985;18:627-35] were used to categorize the BEVs. RESULTS: BEVs were identified in 1183 out of 35,249 subjects (3.4%). The distribution of individual BEVs were as follows: benign sporadic sleep spikes 1.85%, wicket waves 0.03%, 14 and 6 Hz positive spikes 0.52%, 6 Hz spike-and-waves 1.02%, rhythmic temporal theta bursts of drowsiness 0.12%, and subclinical rhythmic electrographic discharge of adults in 0.07%. CONCLUSION: The prevalence of six types of BEVs was relatively low among the Canadian subjects when compared to the reports from other countries. SIGNIFICANCE: BEVs are relatively uncommon incidental EEG findings. Unlike focal epileptic spikes and generalized spike-and-waves, BEVs do not predict the occurrence of epilepsy. Accurate identification of the BEVs can avoid misdiagnosis and unnecessary investigations.
OBJECTIVE: There are numerous distinctive benign electroencephalographic (EEG) patterns which are morphologically epileptiform but are non-epileptic. The aim of this study was to determine the prevalence of different benign epileptiform variants (BEVs) among subjects who underwent routine EEG recordings in a large EEG laboratory over 35 years. METHODS: We retrospectively studied the prevalence of BEVs among 35,249 individuals who underwent outpatient EEG recordings at London Health Sciences Centre in London, Ontario, Canada between January 1, 1972 and December 31, 2007. The definitions of the Committee on Terminology of the International Federation of Societies for EEG and Clinical Neurophysiology (IFSECN) were used to delineate epileptiform patterns (Chatrian et al. A glossary of terms most commonly used by clinical electroencephlographers. Electroenceph Clin Neurophysiol 1974;37:538-48) and the descriptions of Klass and Westmoreland [Klass DW, Westmoreland BF. Nonepileptogenic epileptiform electroenephalographic activity. Ann Neurol 1985;18:627-35] were used to categorize the BEVs. RESULTS: BEVs were identified in 1183 out of 35,249 subjects (3.4%). The distribution of individual BEVs were as follows: benign sporadic sleep spikes 1.85%, wicket waves 0.03%, 14 and 6 Hz positive spikes 0.52%, 6 Hz spike-and-waves 1.02%, rhythmic temporal theta bursts of drowsiness 0.12%, and subclinical rhythmic electrographic discharge of adults in 0.07%. CONCLUSION: The prevalence of six types of BEVs was relatively low among the Canadian subjects when compared to the reports from other countries. SIGNIFICANCE: BEVs are relatively uncommon incidental EEG findings. Unlike focal epileptic spikes and generalized spike-and-waves, BEVs do not predict the occurrence of epilepsy. Accurate identification of the BEVs can avoid misdiagnosis and unnecessary investigations.
Authors: Hannah Purtell; Sameer C Dhamne; Sarika Gurnani; Elizabeth Bainbridge; Meera E Modi; Stephen H T Lammers; Chloe E Super; Mustafa Q Hameed; Ervin L Johnson; Mustafa Sahin; Alexander Rotenberg Journal: Epilepsy Behav Date: 2018-11-03 Impact factor: 2.937
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Authors: Andras Attila Horvath; Emoke Anna Csernus; Sara Lality; Rafal M Kaminski; Anita Kamondi Journal: Front Neurosci Date: 2020-10-15 Impact factor: 4.677