Model for predicting the risk of severe bronchial asthma in children

Objective: to develop a model for predicting the severe course of bronchial asthma (BA) in children.   Materials and methods. A comprehensive examination was conducted of 213 children aged 3 to 12 years suffering from atopic asthma (mild course was observed in 85.0 %, moderate — in 10.3 %, severe —...

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Bibliographic Details
Main Authors: O. E. Semernik, A. A. Lebedenko, E. B. Tyurina, M. V. Dudareva
Format: Article
Language:Russian
Published: Association of Paediatric Allergists and Immunologists of Russia (APAIR) 2023-08-01
Series:Аллергология и Иммунология в Педиатрии
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Online Access:https://adair.elpub.ru/jour/article/view/92
Description
Summary:Objective: to develop a model for predicting the severe course of bronchial asthma (BA) in children.   Materials and methods. A comprehensive examination was conducted of 213 children aged 3 to 12 years suffering from atopic asthma (mild course was observed in 85.0 %, moderate — in 10.3 %, severe — 4.7 %). A statistical analysis of clinical and laboratory parameters was performed using the logistic regression method, which allowed us to identify a number of factors that increase the probability of developing a more severe course of BA in children.   Results. A mathematical model for predicting the risk of severe bronchial asthma in children has been developed, including such factors as the child’s age, the degree of respiratory failure, the value of the peak expiratory rate, the duration of the disease, and the presence of an association of exacerbations of the disease with changes in the weather and physical activity. A computer program has also been developed that allows you to automatically calculate the amount of risk after entering the child’s data.   Conclusion. The use of this model makes it possible to predict the further course of BA with a high degree of confidence, and, consequently, to correct the basic therapy in time to prevent the development of complications in a sick child.
ISSN:2500-1175
2712-7958