• Karina I Holguín-Andrade, Estefanía Murrieta-Peralta, Ana P Chischistz-Condey, Dania G Solís-Cano, Roberto Ríos-Muñoz, Mario Calva-Arcos, and Héctor Murrieta-González.
• Department of Radiology and Molecular Imaging, Centro Médico ABC, Mexico City, Mexico.
• Gac Med Mex. 2021 Jan 1; 157 (4): 391-396.

IntroductionBy the end 2019 there was an outbreak of pneumonia caused by a new coronavirus, a disease that was called coronavirus disease 2019 (COVID-19). Computed tomography (CT) has played an important role in the diagnosis of COVID-19 patients.ObjectiveTo demonstrate inter-observer variability with five scales proposed for measuring the extent of COVID-19 pneumonia on tomography.MethodsThirty five initial chest CT scans of patients who attended respiratory triage for suspected COVID-19 pneumonia were analyzed. Three radiologists classified the tomographic images according to the severity scales proposed by Yang (1), Yuan (2), Chun (3), Wang (4) and Instituto Nacional de Enfermedades Respiratorias-Chung-Pan (5). The percentage of agreement between the evaluators for each scale was calculated using the intra-class correlation index.ResultsIn most patients were five pulmonary lobes compromised (77.1% of the patients). Scales 1, 2, 4 and 5 showed an intra-class correlation > 0.91 (p < 0.0001), with agreement thus being almost perfect.ConclusionsScale 4 (proposed by Wang) showed the best inter-observer agreement, with a coefficient of 0.964 (p = 0.001).Copyright: © 2021 Permanyer.

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