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The role of a chest computed tomography severity score in coronavirus disease 2019 pneumonia
The chest computed tomography (CT) characteristics of coronavirus disease 2019 (COVID-19) are important for diagnostic and prognostic purposes. The aim of this study was to investigate chest CT findings in COVID-19 patients in order to determine the optimal cut-off value of a CT severity score that...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571935/ https://www.ncbi.nlm.nih.gov/pubmed/33080676 http://dx.doi.org/10.1097/MD.0000000000022433 |
Sumario: | The chest computed tomography (CT) characteristics of coronavirus disease 2019 (COVID-19) are important for diagnostic and prognostic purposes. The aim of this study was to investigate chest CT findings in COVID-19 patients in order to determine the optimal cut-off value of a CT severity score that can be considered a potential prognostic indicator of a severe/critical outcome. The CT findings were evaluated by means of a severity score that included the extent (0–4 grading scale) and nature (0–4 grading scale) of CT abnormalities. The images were evaluated at 3 levels bilaterally. A receiver operating characteristics (ROC) curve was used to identify the optimal score (Youden's index) predicting severe/critical COVID-19. The study involved 165 COVID-19 patients (131 men [79.4%] and 34 women [20.6%] with a mean age of 61.5 ± 12.5 years), of whom 30 (18.2%) had severe/critical disease and 135 (81.8%) mild/typical disease. The most frequent CT finding was bilateral predominantly subpleural and basilar airspace changes, with more extensive ground-glass opacities than consolidation. CT findings of consolidation, a crazy-paving pattern, linear opacities, air bronchogram, and extrapulmonary lesions correlated with severe/critical COVID-19. The mean CT severity score was 63.95 in the severe/critical group, and 35.62 in the mild/typical group (P < .001). ROC curve analysis showed that a CT severity score of 38 predicted the development of severe/critical symptoms. A CT severity score can help the risk stratification of COVID-19 patients. |
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