Risk factors for severe and prolonged acute respiratory viral infections in young patients

Abstract

Acute respiratory infections remain one of the most common infectious diseases, which are mostly mild, and there is also a possibility of developing severe forms of the disease. The article considered the possibilities of early prediction of severe course of acute respiratory viral infection in young patients.

The aim – creation of a mathematical prognostic model of the duration of the course and severity of acute respiratory viral infection for use at the stages of hospitalization of young patients.

Material and methods. A study was conducted on 120 people (90+30) of young age (from 18 to 30 years old), of which 90 people were treated in the Infectious Diseases Department of the 301 VKG of the Ministry of Defense of the Russian Federation of Khabarovsk with a diagnosis of “acute respiratory viral infection” and 30 – conditionally healthy young people. The diagnosis of acute respiratory viral infection was established on the basis of epidemiological, clinical and laboratory data. The etiology of the disease was established by PCR.

Results and discussion. Statistical processing of the data obtained showed that out of 95 assessed clinical and laboratory parameters, only 15 were identified as significantly affecting the duration and severity of the disease (p<0.001). For the selected indicators, diagnostic values ​​were calculated and a mathematical model was built to predict the duration and severity of the course of the disease, which has a high level of reliability – 95%.

Conclusion. ROC analysis of the constructed “decision trees” showed their high prognostic value. The predictive quality of the constructed model has an average level. An AuROC value of 0.84 suggests that the simulated decision tree has an average predictive value. The diagnostic value of the selected indicators is average (AUC=0.84); sensitivity – high (88.2%), specificity (69.5%) – high. This combination of sensitivity and specificity of the logistic regression model allows us to recommend the use of the selected indicators in the early stages of predicting the duration and severity of an acute respiratory viral infection.

Keywords:acute respiratory viral infection; adult patients (male); logistic regression; decision tree

Funding. The study was not funded.

Conflict of interest. The authors report no conflict of interest.

Contribution. The concept and design of the study – Sizov D.A., Rukina N.Yu., Perminov N.V., Rychkova O.A., Kashuba E.A.; collection of material – Sizov D.A., Perminov N.V.; material processing, statistical data processing, writing the text of the article – Sizov D.A.,Rukina N.Yu., Perminov N.V., Rychkova O.A., Kashuba E.A.; editing – Kashuba E.A., Rychkova O.A.; approval of the final version of the article – Rychkova O.A., Kashuba E.A.; responsibility for the integrity of all parts of the article – Sizov D.A., Rychkova O.A.

For citation: Rychkova O.A., Kashuba E.A., Rukina N.Yu., Perminov N.V., Sizov D.A. Risk factors for severe and prolonged acute respiratory viral infections in young patients. Infektsionnye bolezni: novosti, mneniya, obuchenie [Infectious Diseases: News, Opinions, Training]. 2022; 11 (4): 56–63. DOI: https://doi.org/10.33029/2305-3496-2022-11-4-56-63

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CHIEF EDITOR
Aleksandr V. Gorelov
Academician of the Russian Academy of Sciences, MD, Head of Infection Diseases and Epidemiology Department of the Scientific and Educational Institute of Clinical Medicine named after N.A. Semashko ofRussian University of Medicine, Ministry of Health of the Russian Federation, Professor of the Department of Childhood Diseases, Clinical Institute of Children's Health named after N.F. Filatov, Sechenov First Moscow State Medical University, Ministry of Health of the Russian Federation, Deputy Director for Research, Central Research Institute of Epidemiology, Rospotrebnadzor (Moscow, Russian Federation)

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