Chest Computed Tomography findings associated with severity and mortality in patients with COVID-19

Autor: Jheferson Contreras-Grande, Vanessa Pineda-Borja, Hubertino Díaz, Renzo J.C. Calderon-Anyosa, Bertha Rodríguez, María Morón
Jazyk: Spanish; Castilian
Rok vydání: 2021
Předmět:
Zdroj: Revista Peruana de Medicina Experimental y Salud Pública, Vol 38, Iss 2, Pp 206-13 (2021)
Druh dokumentu: article
ISSN: 1726-4634
1726-4642
DOI: 10.17843/rpmesp.2021.382.6562
Popis: Objectives: To determine chest CT findings associated with severity and mortality in patients with COVID-19 from the Hospital Nacional Edgardo Rebagliati Martins (HNERM) and propose cut-off values for a tomographic severity score (TSS). Materials and Methods: A retrospective cohort study was conducted in 254 patients with COVID-19 who underwent chest CT as part of their initial evaluation at the emergency room; they were classified according to clinical severity. Main tomographic findings were described. A multivariate analysis with logistic regression was carried out to determine association with clinical severity, the Cox model was used to evaluate mortality, and ROC curves were elaborated to assess cutoff values for the TSS. Results: CT findings associated with clinical severity were the following: diffuse pattern (OR: 3.23, 95% CI: 1.46-7.14), crazy-paving pattern (OR: 2.48; 95% CI: 1.08-5.68), and high TSS value (OR: 1.73; 95% CI: 1.49-2.02). The crazy-paving pattern (HR: 1.78; 95% CI: 1.03-3.06) and a high TSS value (HR: 1.33; 95% CI: 1.20-1.48) were found to be associated with mortality. A value of 7 in the TSS showed a sensibility of 94.4% and a specificity of 100% for moderate disease, and a value of 13 showed a sensibility of 84.9% and a specificity of 70.6% for severe disease. Conclusions: The diffuse pattern is associated with higher clinical severity. The crazy-paving pattern and a high TSS value are associated with higher clinical severity and mortality. We propose TSS cutoff values of 7 and 13 for moderate and severe disease, respectively.
Databáze: Directory of Open Access Journals
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