Use of the complex of models of regression for analysis of the factors that determine the severity of bronchial asthma

Abstract

Background: According to an International Study of Asthma and Allergies in Childhood (ISAAC), the prevalence of asthma in children of 6-7 years old has increased by 10%, and at the age of 13-14 years by 16% over the last decade. Determining the factors that are keys to the occurrence of the disease and its severity is important in explaining the pathogenesis of bronchial asthma. Methods: Analyzed 142 indicators of clinical and paraclinical examination of 70 children with asthma. To select factors that could be significant in the formation of severe asthma, applied the method of logistic regression with step-by-step inclusion of predictors. Both quantitative and qualitative characteristics were selected. Each qualitative attribute was coded “1” if the child had this characteristic, or “0” if this characteristic had not been established. The formation of a severe asthma course was accepted according to (1) and the absence of a severe asthma flow formation as (0). Results: Analyzed the model of paired regression, the boundary value of thymic stromal lymphopoietin was established, exceeding which indicates the high probability of the presence of severe bronchial asthma. Increasing the value of thymic stromal lymphopoietin by 10 pg/mL suggests an increase in the likelihood of severe asthma by 10%. Conclusions: A complex of steam regression models has been developed to determine the factors characterizing the severity of bronchial asthma. The risk of developing severe bronchial asthma in children has been determined and 15 factors have been identified that affect severe asthma.