Diagnostic prediction of COVID-19 based on clinical and radiological findings in a relatively low COVID-19 prevalence area

Background: Distinguishing coronavirus disease 2019 (COVID-19) pneumonia from other lung diseases is often difficult, especially in a highly comorbid patient population in a low prevalence region. We aimed to distinguish clinical data and computed tomography (CT) images between COVID-19 and other lung diseases in an advanced care hospital. Methods: We assessed clinical characteristics, laboratory data, and chest CT images of patients with COVID-19 and non-COVID-19 patients who were suspected of having COVID-19 between February 20 and May 21, 2020, at the University of Tokyo Hospital. Results: Typical appearance for COVID-19 on CT images were found in 24 of 29 COVID-19 cases and 21 of 168 non-COVID-19 cases, according to the Radiological Society of North America Expert Consensus Statement (for predicting COVID-19, sensitivity 0.828, specificity 0.875, positive predictive value 0.533, negative predictive value 0.967). When we focused on cases with typical CT images, loss of taste or smell, and close contact with COVID-19 patients were exclusive characteristics for the COVID-19 cases. Among laboratory data, high fibrinogen (P < 0.01) and low white blood cell count (P < 0.01) were good predictors for COVID-19 with typical CT images in multivariate analysis. Conclusions: In a relatively low prevalence region, CT screening has high sensitivity to COVID-19 in patients with suspected symptoms. When chest CT findings are typical for COVID-19, close contact, loss of taste or smell, lower white blood cell count, and higher fibrinogen are good predictors for COVID-19. (C) 2021 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.