Abstract
Objectives: Prognostication of bronchial asthma severity in children by means of two-parameter regression models building.
 Methods: A clinical study of 70 children with bronchial asthma diagnosis of 6 to 18 years old was done.142 factors were analyzed and a degree of relationship among them was revealed. Single-factor regression models were used during preliminary experimental data processing.
 Results: The correlation connection between the value observed and the factors under research was revealed. The method of two-parameter linear models with a fair accuracy was developed.
 Conclusion: The suggested method of approximate two-parameter linear regression models can be used for preliminary analysis of medical research data where the value observed depends on a big number of loosely connected factors.
Highlights
Bronchial asthma (BA) is a heterogeneous inflammatory respiratory disease with more than 300 million people currently affected [1, 2]
We propose a method of two-parameter linear models on the basis of pair wise regression models and estimate their error
The result of allergen affecting significantly depends on the allergen dose and type, its exposure time and child's frailty [27, 29].Asthma progress is more frequently observed in children suffering from atopic dermatitis or allergic rhinitis [30,31,32]
Summary
Bronchial asthma (BA) is a heterogeneous inflammatory respiratory disease with more than 300 million people currently affected [1, 2]. If children with an undiagnosed BA get a long and improper treatment, preventive and therapy measures are placed on too late and it affects the quality of life of both a patient and their family[18,19]. Detection of patients with a high risk of disease progressing allows to use individual therapy and observation methods and helps to provide reliable control of asthma. Numerous clinical studies of uncontrolled asthma course prove the necessity of analyzing the factors causing strong forms of asthma [20,21,22,23].To increase the study quality, analyzing requires improving both the models themselves and methods of their building. Linear regression models area common method of severity of bronchial asthma diagnosis. Refinement of the results is possible by using regression models containing two or more factors. The complexity and laboriousness of linear multivariate models building result to the fact that the model data are used less often in the initial evaluation and analysis of data
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