Eeg Patterns In Metabolic Diseases: Diagnostic Significance and Clinical Utility

OBJECTIVE:The aim of this study is to elucidate the diagnostic implications by rigorously correlating the electroencephalographic patterns of subjects diagnosed with metabolic disorders to the underlying metabolic disease taxonomy, associated EEG manifestations,radiological findings, and clinical symptomatology.

METHOD:Within the temporal confines of January 2012 to January 2023, a retrospective analysis was undertaken, encompassing EEG datasets, seizure semiological characterizations, clinical symptomatologies,and radiological findings of pediatric subjects unequivocally diagnosed with metabolic anomalies in our institution.

RESULTS:A comprehensive review of 310 EEG datasets was executed. Lysosomal storage pathologies constituted the predominant metabolic disorder group at 56.2%,followed by perturbations in amino acid metabolism at 16.3%.The most pervasive EEG anomaly was the disruption of foundational neural activity, evident in 73.9% of cases.An intricate review of the EEG datasets of subjects with lysosomal storage disorders unveiled not only foundational rhythmic abnormalities but also, in cohorts with clinical and radiological manifestations, a salient presence of diminished amplitude coupled with electro-decremental/attenuation epochs(p=0.009). In subjects with amino acid metabolic disruptions, an escalation in clinical severity corresponded with an emergence of burst-suppression epochs (p=0.002).A juxtaposition of EEG findings with radiological data indicated a pronounced neural slowing in EEG tracings of subjects manifesting white matter degeneration(p=0.02).Furthermore, during metabolic crises, EEG datasets exhibited pronounced neural disorganization, amplified delta wave propagation,and generalized suppression patterns(p=0.001).

CONCLUSION:The data procured from this investigation underscores the pivotal role of a meticulous EEG analysis,positing that when conjoined with the distinctive findings expounded within our research, invaluable insights into metabolic aberrations in subjects diagnosed with epileptic syndromes can be extrapolated.