INTRODUCTION: By 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. OBJECTIVE: To demonstrate inter-observer variability with five scales proposed for measuring the extent of COVID-19 pneumonia on tomography. METHODS: Thirty 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. RESULTS: In 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. CONCLUSIONS: Scale 4 (proposed by Wang) showed the best inter-observer agreement, with a coefficient of 0.964 (p = 0.001).
Inter-observer variability with five computed tomography severity scales for COVID-19 pneumonia assessment