The prognostication of development of respiratory tract bacterial diseases for children of early age

Abstract

The purpose of this study was definition of influence of the modified factors in development of acute pneumonia in children of early age and development of the method of prognostication of disease development.Materials and methods. 89 children of early age with acute bronchopulmonary pathology whose average age was 1.3 ± 0.2 years (47 children with acute bacterial bronchitis and 42 children with acute community-acquired pneumonia) were examined. Also we tested the level of 25-hydroxyvitamin D (25(OH)D), hBPI, cathelicidin LL-37, lactoferrin in blood serum with the help of immunoenzymometric analysis. The significant factors that are most associated with the development of acute pneumonia were revealed using factor analysis. For prognostication of probability of development of an acute pneumonia the equation of logistic regression was used. Determination of quality of the received model of prognostication was conducted by means of the ROC analysis and index of AUC. For assessment of the discriminating ability of model the Gini index was calculated.Results. By results of conducted factor analysis 5 significant factors determining the main part of predictors of development of an acute pneumonia in children of early age, patients with acute inflammatory bronchopulmonary pathology were allocated. The conducted correlation analysis of variables revealed existence of interrelations between prenatal, anamnestic and immune factors which entered further mathematical model of probability of development of an acute pneumonia in children of early age. The statistical importance of the created model was confirmed by Omnibus Test, the diagnostic information content was estimated according to a ROC curve that confirmed high quality of model.Conclusion. On the basis of the conducted factor analysis the most priority predictors of development of an acute pneumonia in children of early age with acute bronchopulmonary pathology who were further included to the mathematical prognostic model of probability of development of the specified disease were allocated.