Use of predictive programs to identify children from risk group of recurrent respiratory infections |
Wednesday, 26 November 2014 | ||||||
Maiorov R.V., Derbenev D.P. Abstract. Acute respiratory diseases are the most common conditions in adults and children. Recurrent respiratory infections contribute to disturbance of physical and neuropsychic development, encourage development of chronic somatic diseases, and require considerable material resources. The mentioned above conditions the need for developing new methods of early identification of children at risk to be assigned to the follow-up group of recurrent respiratory infection children. The aim of the study was to justify the use of predictive screening programs of children at risk to be assigned to the follow-up group of recurrent respiratory infection children and the group of children with high risk of primary immunodeficiency requiring in-depth immunoassay. Methodology. Sociological method, statistical method, case follow-up and descriptive method. Results. The developed methodology and computer program for predictive assessment of risk to assign children to the follow-up group of recurrent respiratory infection children and the group of children with high risk of primary immunodeficiency helped identify risk factors for recurrent respiratory diseases in children as well as evaluate their impact on incidence of respiratory diseases, depending on age of the child. Scope of application – practical health care. Conclusions. The study identified risk factors of recurrent respiratory diseases in children and evaluated their impact on disease incidence depending on age. The developed techniques of predictive assessment of risk to assign a child to the follow-up group of recurrent respiratory infection children and the group of children with high risk of primary immunodeficiency and the developed on their basis computer programs can be used to identify cohort of children that require preventive measures. Keywords: recurrent respiratory diseases in children; risk factors of respiratory infections; computer program of predictive risk evaluation; grouping children for follow-up.
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