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.

The role of a chest computed tomography severity score in coronavirus disease 2019 pneumonia / F. Salaffi, M. Carotti, M. Tardella, A. Borgheresi, A. Agostini, D. Minorati, D. Marotto, M. Di Carlo, M. Galli, A. Giovagnoni, P. Sarzi-Puttini. - In: MEDICINE. - ISSN 0025-7974. - 99:42(2020 Oct 16). [10.1097/MD.0000000000022433]

The role of a chest computed tomography severity score in coronavirus disease 2019 pneumonia

A. Agostini;P. Sarzi-Puttini
Ultimo
2020

Abstract

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.
acute respiratory disease; chest computed tomography; coronavirus disease 2019; outcomes; pneumonia; predictive score; risk factors;
Settore MED/16 - Reumatologia
16-ott-2020
Article (author)
File in questo prodotto:
File Dimensione Formato  
medi-99-e22433.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 558.87 kB
Formato Adobe PDF
558.87 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/801484
Citazioni
  • ???jsp.display-item.citation.pmc??? 15
  • Scopus 25
  • ???jsp.display-item.citation.isi??? 24
social impact