Abstract
Objective. To create a prognostic algorithm of emotional disorders development in pubertal age children based on markers of dopamine system dysfunction and depending on body mass index and pubertal periods.Materials and methods. In the cross-sectional study Depression SelfRatingScale (DSRC) was used in 120 children aged from 11.6 to 17.9 years (the 2nd — 5th Tanner’s puberty stages). to establish depression risk (total DSRC score) and depressive symptoms (no depression; one depressive episode; presence of depression). Patients were stratified into groups BMI SDS: group 1 — children with normal weight, group 2 —those with simple obesity and group 3 — morbidly obese. All children were further divided into subgroups by gender and sexual development stage according to Tanner. Patients of 2 and 3 Tanner puberty stage were combined into early puberty (EP) subgroup, those of stage 4 and 5 — into late puberty (LP) subgroup Enzyme-linked immunosorbent assay (ELISA) was uses to identify blood dopamine (D) concentration in 88 patients. Two children with maximum and minimum D values were excluded from the study.D level quartiles were as follows: 1st—low concentration (< 10.9 pg/ml); 2nd — moderately decreased concentration (10.9—16.17 pg/ml); 3rd — moderately increased levels (16.17—19.3 pg/ml); 4th — high concentration (> 19.3 pg/ml). Statistical analysis was performed with SPSS Statistics 21 using Spearman’s nonparametric correlations (r), mathematical modeling method (logistic polynomial regression) (p < 0.05).Results and discussion. In the general group of children of LP age, the values of D and the indicators of emotional status formed a model with a statistically significant estimate (p = 0.016) to predict the probability of dopamine dysfunction. For example, a LP age patient with the presence of depression will have moderately decreased D concentration with 33.3 % probability, moderately elevated — with 16.7 %, and high D levels — with 50 % probability. In the subgroup of pubertal adolescent children with obesity, the values of the D ranges and the indicators of emotional status formed a model with a reliable statistical estimate (p = 0.05) to assess the probability of dopamine system dysfunction. For example, an obese adolescent with depression will have moderately reduced blood D level with 50 % probability; moderately elevated D — with 33.3 % and high D level in — 16.7 %. Based on these two models, we created the prognostic algorithm for diagnosing of dopamine system dysfunction in adolescents. It could be used as a tool for further scientific research in studying mechanisms of morbid obesity development in children.Conclusions. We developed prognostic math models with good statistical significance.It could be used to evaluate the effect of dopamine concentration ranges on the likelihood of depression presence, its single episode presence or its absence in adolescent children with obesity (p = 0.05) and in LP age patients (p = 0.016) regardless from body weight. Based on the developed mathematical models, we created the algorithm for diagnosing dopamine system dysfunction using BMI, puberty stage, and emotional status characteristics in adolescents.
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