Inventory reference ISSN 1812-7231 Klin.inform.telemed. Volume 14, Issue 15, 2019, Pages 35-45
Author(s) O. Yu. Mayorov1, 2, E. A. Mikhailova1, O. Ya. Mikhalchuk1, 2, M. L. Kochina2, I. V. Redka2, A. B. Prognimak2, T. N. Matkovskaya1, D. A. Mitelev1
1State Institution "Institute for Children and Adolescents Health Protection of the National Academy of Medical Sciences of Ukraine", Kharkiv
2Kharkiv Medical Academy of Postgraduate Education of the Ministry of Health of Ukraine
Article title Criteria ("markers") of depression in teenagers based on the estimation of the state of neurodynamics by methods of nonlinear analysis of EEG and correlation with the CDRS-R scale
Introduction. The issue of prevention, diagnosis, and treatment of various types of depression in children and adolescents is relevant. The study is aimed at finding objective informative biological "markers" that reflect changes characteristic of depression, among which the leading role belongs to the assessment of the indicators of central nervous system activity.
Community sample. Research Methods. 1. We examined 52 depressed patients (35 girls (12,7 ± 1,2) years and 17 boys (14,0 ± 1,3) years. 2. CDRS-R scale estimates of depression. 3. EEG record. 4. EEG analysis — NeuroResearcher® InnovationSuite qEEG system (Mi&T Institute, Ukraine). Kolmogorov–Sinai entropy (eKS) was calculated. 5. Statistical analysis. The statistical difference between the two averages was determined by non-parametric methods (STATISTICA 13.3, Microsoft Excel 2019 software).
Results. A range of eKS values was established in the symmetrical brain regions of depressed adolescents in both sexes during a resting state and intellectual stress. There is no statistically significant difference in average eKS values between resting state and intellectual stress, which may indicate a decrease in patient's adaptability. The statistically significant gender differences in the eKS values were determined: boys had a higher eKS values than girls. A higher eKS values in adolescent boys might indicate their higher adaptive ability in comparison with girls of the same age. A standardized indicator ‘the severity of signs of depression' (SSD) is proposed. The relationship between some depression symptoms from the CDRS-R scale and the neurodynamics state assessment based on eKS were revealed. EEG leads associated with certain depression symptoms were identified.
Conclusion. The identification of relationship between eKS values and depression symptoms can contribute to a more accurate diagnosis, targeted therapy choice, and treatment effectiveness evaluation.
Keywords Depression, qEEG, Nonlinear analysis, Kolmogorov–Sinai entropy
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