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Estimating COVID-19 Pneumonia Extent and Severity From Chest Computed Tomography.
Carvalho, Alysson Roncally Silva; Guimarães, Alan; Garcia, Thiego de Souza Oliveira; Madeira Werberich, Gabriel; Ceotto, Victor Fraga; Bozza, Fernando Augusto; Rodrigues, Rosana Souza; Pinto, Joana Sofia F; Schmitt, Willian Rebouças; Zin, Walter Araujo; França, Manuela.
Afiliación
  • Carvalho ARS; Cardiovascular R&D Centre (UnIC), Department of Surgery and Physiology, Faculty of Medicine, University of Porto, Porto, Portugal.
  • Guimarães A; Laboratory of Pulmonary Engineering, Biomedical Engineering Program, Alberto Luiz Coimbra Institute of Post-Graduation and Research in Engineering, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
  • Garcia TSO; Laboratory of Respiration Physiology, Carlos Chagas Filho Institute of Biophysics, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
  • Madeira Werberich G; Laboratory of Pulmonary Engineering, Biomedical Engineering Program, Alberto Luiz Coimbra Institute of Post-Graduation and Research in Engineering, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
  • Ceotto VF; Medical Faculty, Universidade Estácio de Sá, Rio de Janeiro, Brazil.
  • Bozza FA; Department of Radiology, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
  • Rodrigues RS; Hospital Niteroi D'Or, Niterói, Brazil.
  • Pinto JSF; D'Or Institute for Research and Education, Rio de Janeiro, Brazil.
  • Schmitt WR; National Institute of Infectious Disease, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
  • Zin WA; Department of Radiology, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
  • França M; D'Or Institute for Research and Education, Rio de Janeiro, Brazil.
Front Physiol ; 12: 617657, 2021.
Article en En | MEDLINE | ID: mdl-33658944
BACKGROUND: COVID-19 pneumonia extension is assessed by computed tomography (CT) with the ratio between the volume of abnormal pulmonary opacities (PO) and CT-estimated lung volume (CTLV). CT-estimated lung weight (CTLW) also correlates with pneumonia severity. However, both CTLV and CTLW depend on demographic and anthropometric variables. PURPOSES: To estimate the extent and severity of COVID-19 pneumonia adjusting the volume and weight of abnormal PO to the predicted CTLV (pCTLV) and CTLW (pCTLW), respectively, and to evaluate their possible association with clinical and radiological outcomes. METHODS: Chest CT from 103 COVID-19 and 86 healthy subjects were examined retrospectively. In controls, predictive equations for estimating pCTLV and pCTLW were assessed. COVID-19 pneumonia extent and severity were then defined as the ratio between the volume and the weight of abnormal PO expressed as a percentage of the pCTLV and pCTLW, respectively. A ROC analysis was used to test differential diagnosis ability of the proposed method in COVID-19 and controls. The degree of pneumonia extent and severity was assessed with Z-scores relative to the average volume and weight of PO in controls. Accordingly, COVID-19 patients were classified as with limited, moderate and diffuse pneumonia extent and as with mild, moderate and severe pneumonia severity. RESULTS: In controls, CTLV could be predicted by sex and height (adjusted R 2 = 0.57; P < 0.001) while CTLW by age, sex, and height (adjusted R 2 = 0.6; P < 0.001). The cutoff of 20% (AUC = 0.91, 95%CI 0.88-0.93) for pneumonia extent and of 50% (AUC = 0.91, 95%CI 0.89-0.92) for pneumonia severity were obtained. Pneumonia extent were better correlated when expressed as a percentage of the pCTLV and pCTLW (r = 0.85, P < 0.001), respectively. COVID-19 patients with diffuse and severe pneumonia at admission presented significantly higher CRP concentration, intra-hospital mortality, ICU stay and ventilatory support necessity, than those with moderate and limited/mild pneumonia. Moreover, pneumonia severity, but not extent, was positively and moderately correlated with age (r = 0.46) and CRP concentration (r = 0.44). CONCLUSION: The proposed estimation of COVID-19 pneumonia extent and severity might be useful for clinical and radiological patient stratification.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Physiol Año: 2021 Tipo del documento: Article País de afiliación: Portugal Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Physiol Año: 2021 Tipo del documento: Article País de afiliación: Portugal Pais de publicación: Suiza