PERSONALIZED APPROACH IN THE DIAGNOSTICS AND TREATMENT OF SYMPTOMATIC EPILEPSY WITH DÉJÀ VU SEIZURES

Abstract


The phenomenon of déjà vu (DV) is of interest, occurring in 97% of healthy individuals, while DV can be a manifestation of a number of pathologies, such as Charles Bonnet syndrome, depression, schizophrenia, or temporal lobe epilepsy. Most cases of DV type epiphenomena are associated with hippocampal sclerosis, while up to 90% of patients with mesial temporal sclerosis are drug resistant. Despite the success of pharmacotherapy, the frequency of «uncontrolled» epilepsy in industrialized countries that adhere to modern standards of treatment is from 30 to 40%, and this percentage is higher among patients with symptomatic and cryptogenic forms than among patients with idiopathic epilepsy (respectively: 40% and 26%). In turn, when studying the DV phenomenon and choosing a therapy strategy, it is necessary to establish its origin, determine its clinical significance (whether it is initially pathological or not), and the need for treatment. During the analysis of exome data, a search was made for substitutions in genes associated with arteriovenous malformations, both with autosomal dominant and autosomal recessive types of inheritance. The genes KRIT1, RASA1, IL6, FAM58A, GLML, EPHB4, CCM2, and ELMO2 were analyzed especially carefully. The analysis of genetic data is of great importance in the aspect of preventing cerebrovascular accidents, at the same time, in order to obtain reliable and significant results, in addition to time and financial costs, examination of relatives is also required. Meanwhile, this fact does not mean that every patient needs to conduct a genetic study. The paper presents detailed instructions for supplementing anamnestic information, as well as the results of personalized instrumental and laboratory diagnostics, which made it possible to carry out timely correction of therapy and achieve a prolonged positive effect.

About the authors

V. E. Khomutov

I. V. Kolesnikova

E. N. Mingazova

Yu. A. Bespyatykh

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