Development of a model for the differential diagnosis of community-acquired bacterial pneumonia and viral lung injury in hospitalized adult patients

Author:

Kupriushina O. A.1ORCID,Strelkova D. A.1ORCID,Yasneva A. S.1ORCID,Rachina S. A.1ORCID,Avdeev S. N.1ORCID,Vlasenko A. E.2ORCID,Fedina L. V.3ORCID,Ivanova O. V.4ORCID,Kaledina I. V.5ORCID,Ananicheva N. A.5ORCID

Affiliation:

1. I. M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenovskiy University)

2. Samara State Medical University» of the Ministry of Healthcare of the Russian Federation

3. City Clinical Hospital named after S. S. Yudin; Russian Medical Academy of Continuous Professional Education

4. Branch No. 4 of the Federal State Institution "1586 Military Clinical Hospital" of the Ministry of Defense of the Russian Federation

5. City Clinical Hospital named after S. S. Yudin

Abstract

Relevance. During and after the COVID-19 pandemic, viruses have become a more common cause of pulmonary infections in adults; therefore, the distinction between viral lung injury and community-acquired bacterial pneumonia is of increasing importance. Aim. Development of a model for differentiating community-acquired bacterial pneumonia and viral lung injury, including COVID-19. Materials and methods. This retrospective case–control study included 300 adult patients with viral lung injury and 100 adult patients with community-acquired bacterial pneumonia. Clinical, laboratory, and instrumental data were analyzed, significant factors were selected by which the samples differed, and a model was developed using logistic regression to distinguish between community-acquired bacterial pneumonia and viral lung damage, including COVID-19. Results. The developed model included the following parameters: total protein level, neutrophil/lymphocyte index, heart rate, unilateral infiltration on CT or chest x-ray, vasopressor prescription in the first 24 h of hospitalization, altered level of consciousness, chills, and fatigue. The model had the following characteristics: AUC = 0.94 (0.92–0.96), AUC_PR = 0.84 (0.76 to 0.92), prediction accuracy — 90%, sensitivity — 76%, specificity — 95%, positive predictive value — 83 %. Conclusion. The use of this model can facilitate the differential diagnosis of community-acquired bacterial pneumonia and viral lung injury, including COVID-19, in adults in general wards and intensive care units.

Publisher

Publishing House OKI

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