| Controversies in Usefulness of EEG for Clinical Decision in Epilepsy: Pros. |
| Young-Min Shon, and Yeong In Kim |
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| Copyright © 2007 The Korean Society of Clinical Neurophysiology |
| This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium,
provided the original work is properly cited. |
| ABSTRACT |
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The EEG plays an important diagnostic role in epilepsy and provides supporting evidence of a seizure disorder as well as assisting with classification of seizures and epilepsy syndromes. There are a variety of electroclinical syndromes that are really defined by the EEG such as Lennox-Gastaut syndrome, benign rolandic epilepsy, childhood absence epilepsy, juvenile myoclonic epilepsy and also for localization purposes, it is vitally important especially for temporal lobe epilepsy. The sensitivity of first routine EEG in diagnosis of epilepsy has been known about 20-50%, but this proportion rises to 80-90% if sleep EEG and repetitive recording should be added. Convincing evidences suggest that the EEG may also provide useful prognostic information regarding seizure recurrence after a single unprovoked attack and following antiepileptic drug (AED) withdrawal.Moreover, patterns in the EEG make it possible to disclose an ictal feature of nonconvulsive status epilepticus, separate epileptic from other non-epileptic episodes and clarify the clues predictive of the cause of the encephalopathy (i.e., triphasic waves in metabolic encephalopathy).Therefore, regardless of its low sensitivity and other pitfalls, EEG should be considered not only in the situation of new onset episode such as a newly developed, unprovoked seizure or a condition manifesting decreased mentality from obscure origin, but also as a barometer of the long-term outcome following AED withdrawal. |
| Key words:
Electroencephalogram (EEG), usefulness, diagnostic, predictive value |
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