EEG at onset and MRI predict long-term clinical outcome in Aicardi syndrome

Autor: Silvia Masnada, Enrico Alfei, Manuela Formica, Roberto Previtali, Patrizia Accorsi, Filippo Arrigoni, Paolo Bonanni, Renato Borgatti, Francesca Darra, Carlo Fusco, Valentina De Giorgis, Lucio Giordano, Francesca La Briola, Simona Orcesi, Elisa Osanni, Cecilia Parazzini, Lorenzo Pinelli, Erika Rebessi, Romina Romaniello, Antonino Romeo, Carlotta Spagnoli, Christian Uebler, Costanza Varesio, Maurizio Viri, Claudio Zucca, Anna Pichiecchio, Pierangelo Veggiotti
Rok vydání: 2022
Předmět:
Zdroj: Clinical Neurophysiology. 142:112-124
ISSN: 1388-2457
Popis: Descriptions of electroencephalographic (EEG) patterns in Aicardi syndrome (AIC) have to date referred to small cohorts of up to six cases and indicated severe derangement of electrical activity in all cases. The present study was conducted to describe the long-term EEG evolution in a larger AIC cohort, followed for up to 23 years, and identify possible early predictors of the clinical and EEG outcomes.In a retrospective study, two experienced clinical neurophysiologists systematically reviewed all EEG traces recorded in 12 AIC cases throughout their follow-up, from epilepsy onset to the present. Clinical outcome was assessed with standardized clinical outcome scales.Analysis of the data revealed two distinct AIC phenotypes. In addition to the "classical severe phenotype" already described in the literature, we identified a new "mild phenotype". The two phenotypes show completely different EEG features at onset of epilepsy and during its evolution, which correspond to different clinical outcomes.Data from our long-term EEG and clinical-neuroradiological study allowed us to describe two different phenotypes of AIC, with different imaging severity and, in particular, different EEG at onset, which tend to remain constant over time.Together, these findings might help to predict long-term clinical outcomes.
Databáze: OpenAIRE
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