Predictors of severe community-acquired pneumonia associated with coronavirus infection
Aim of the study. To determine the predictors of severe community-acquired pneumonia associated with coronavirus infection. Materials and methods. To achieve the aim and solve the problems, an open, prospective observational study was conducted: from January 2021 to February 2022, 102 patients wi...
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| Format: | Article |
| Language: | English |
| Published: |
Zaporizhzhia State Medical and Pharmaceutical University
2024-12-01
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| Series: | Сучасні медичні технології |
| Subjects: | |
| Online Access: | https://medtech.mphu.edu.ua/article/view/301780/309626 |
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| Summary: | Aim of the study. To determine the predictors of severe community-acquired pneumonia associated with coronavirus infection.
Materials and methods. To achieve the aim and solve the problems, an open, prospective observational study was conducted: from January 2021 to February 2022, 102 patients with community-acquired pneumonia (CAP) aged 40 to 65 years with a positive test for SARS-CoV-2 were observed in the outpatient department of the Kherson City Clinical Hospital named after Athanasius and Olga Tropinin of the Kherson City Council. Determination of interleukin-6, interleukin-10, and high-sensitivity C-reactive protein (hs-CRP) was performed in blood plasma by enzyme-linked immunosorbent assay using standardized kits: “hs-CRP-ELISA-Best”, “IL-6-ELISA-Best”, “IL-10-ELISA-Best” in accordance with the attached instructions.
Results. The analysis of univariate logistic regression models showed that such indicators as patient age, heart rate and SpO2 were not important in the occurrence of severe CAP. Indicators such as vital capacity of the lung, blood glucose, C-reactive protein, IL-6 and IL-6 / IL-10 ratio were predictors of severe CAP according to the results of logistic regression analysis. Blood glucose, IL-6, and the IL-6 / IL-10 ratio lost their prognostic power in multivariable logistic regression models of severe CAP. According to the results of multivariate regression analysis, the predictors of severe CAP were the volume of lung lesions on computed tomography (CT) and the level of hs-CRP. Multivariate logistic regression analysis showed that independent predictors of severe CAP were the volume of lung lesion more than 20 % on CT (OR = 1.28, 95 % CI OR 1.11–1.48), and the level of hs-C-reactive protein >13.50 mg/L (OR = 2.22, 95 % CI OR 1.50–3.31). In terms of predicting the development of severe CAP, hs-CRP has an advantage over the standard model (AUC = 0.92 vs AUC = 0.72, p < 0.05).
Conclusions. According to multivariate logistic regression analysis, the following independent predictors were most significant for the occurrence of severe community-acquired pneumonia associated with coronavirus infection: lung lesion volume on CT and high hs-CRP. These indicators also had the largest areas under the ROC curve among those analyzed. Determining the level of C-reactive protein by a highly sensitive method is important for patients with moderate pneumonia associated with coronavirus infection to assess the risk of severe disease. |
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| ISSN: | 2072-9367 |