Analysis of the relationship between comorbid diseases and the severity of COVID-19 in children

The aim of the study was to analyze the relationship between comorbid diseases and the severity of COVID-19 in children to develop a stratified approach to the management of pediatric patients. The study methods included a comprehensive analysis of data from 370 children with confirmed COVID-19, divided into a main group of 273 children with comorbid conditions and a control group of 97 children without comorbidities. Clinical methods for assessing the severity of the course, laboratory diagnostics of inflammatory markers, the pSOFA scale for assessing multiple organ failure, statistical analysis using logistic regression and machine learning algorithms were used. The results showed that the comorbidity structure was characterized by the predominance of anemia in 49.5% of patients and immunodeficiency states in 11.4% of children with significant age differences. Severe and extremely severe forms of COVID-19 accounted for 49.8% of cases in the comorbidity group versus a significantly lower proportion in the control group. A direct correlation was established between the levels of C-reactive protein and ferritin with the severity of the disease. Anemia reached a maximum frequency of 65.7% in the age group of 0—3 years, while immunodeficiency states prevailed in adolescents aged 14—18 years with a frequency of 47.8%. The developed mathematical models based on the pSOFA scale and logistic regression demonstrated high prognostic significance for assessing the risk of an unfavorable course of COVID-19 in children with comorbid conditions, which justifies the need for a personalized approach to the diagnosis and treatment of this category of patients.

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