Literature DB >> 21940184

A diagnostic algorithm for the evaluation of early onset genetic-metabolic epileptic encephalopathies.

Mario Mastrangelo1, Andrea Celato, Vincenzo Leuzzi.   

Abstract

Early onset epileptic encephalopathies represent a struggling challenge in neurological clinical practice, mostly in infants and very young children, partly due to an unclear and still debated cathegorization. In this scenario genetic and metabolic epileptic encephalopathies play a central role, with new entries still needing an arrangement. In this Paper we present a brief overview on genes, metabolic disorders and syndromes picturing the pathogenesis of genetic and metabolic epileptic encephalopathies with onset under one year of age. These forms will be classified, according to a combined clinical and genetic-metabolic criterion, into two main groups including seizures as prominent/unique symptom and seizures associated with a syndromic phenotype. Starting from this classification we suggest a possible simplified diagnostic algorithm, discussing main decision making nodes in practical patients management. The aim of the proposed algorithm is to guide through metabolic and molecular-genetic work up and to clarify "where" and "what" to search in biochemical, electroencephalographic and neuroimaging investigations.
Copyright © 2011 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21940184     DOI: 10.1016/j.ejpn.2011.07.015

Source DB:  PubMed          Journal:  Eur J Paediatr Neurol        ISSN: 1090-3798            Impact factor:   3.140


  13 in total

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Review 5.  Contemporary scope of inborn errors of metabolism involving epilepsy or seizures.

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Review 6.  The hidden genetics of epilepsy-a clinically important new paradigm.

Authors:  Rhys H Thomas; Samuel F Berkovic
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7.  Electroclinical Features of Early-Onset Epileptic Encephalopathies in Congenital Disorders of Glycosylation (CDGs).

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Review 9.  Epileptic Encephalopathy in Childhood: A Stepwise Approach for Identification of Underlying Genetic Causes.

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