Прогнозування ризику розвитку розладів аутистичного спектра в дітей з епілептичними енцефалопатіями

Abstract

Predicting the risk of developing autism spectrum disorders (ASD) in children with epileptic encephalopathies (EE) is an important task, which makes it possible to identify the most significant risk factors and develop ways of their modification. Purpose - to develop a model for predicting the risk of developing ASD in young children with EE. Materials and methods. 75 children aged 0-3 years with the onset of epileptic seizures in the first year of life, clinical manifestations of EE were examined. The most informative clinical, neurophysiological, and neuroimaging indicators for predicting the risk of clinical manifestations of ASD were determined: age of onset of epileptic seizures, index of spike-wave activity during NREM sleep, frequency and amplitude of alpha rhythm, frequency and amplitude of epileptiform activity, fractional anisotropy and mean diffusion coefficient in the Broca’s center, fractional anisotropy in the Wernicke center and knee of the corpus callosum. The multiple linear regression method was used to predict the risk of developing ASD symptoms. Results. A model for predicting the risk of developing clinical manifestations of ASD in children with EE has been developed. It was established that the risk of developing clinical manifestations of ASD increases with a decrease in the age of onset of epileptic seizures, decrease in the frequency and amplitude of the alpha rhythm according to electroencephalography (EEG) data, increase of the index of spike-wave activity, frequency and amplitude of epileptiform activity, increase in the index of fractional anisotropy in the anterior part of the arcuate tract, decrease in the average diffusion coefficient in the area of the Broca’s center, fractional anisotropy in the Wernicke center and the knee of the corpus callosum according to magnetic resonance tractography. Conclusions. A regression model for predicting the risk of clinical manifestations of ASD in children with EE was developed with an average error of approximation of 13.2% and a coefficient of determination of 0.74, which is recommended for use in clinical practice in order to form groups of children at high risk of ASD. Such children require further dynamic monitoring and early intervention by specialists of a multidisciplinary team for timely identification and correction of ASD symptoms The research was carried out in accordance with the principles of the Helsinki Declaration. The study protocol was approved by the Local Ethics Committee of the participating institution. The informed consent of the patient was obtained for conducting the studies. No conflict of interests was declared by the author.