Abstract
Background: Although chest computed tomography (CT) is the gold standard for diagnosing the majority of lung conditions, its use in screening patients for coronavirus disease 2019(COVID-19) pneumonia is not recommended. Lung ultrasound (LUS) is an alternative modality. To investigate the characteristics and diagnostic accuracy (DA) of bedside ultrasound for lung lesions in patients with COVID-19 and to determine the factors influencing the DA of lung ultrasound (LUS).Methods: A total of 330 patients with COVID-19 admitted to the hospital between February and March 2020 were retrospectively recruited. The imaging characteristics of LUS and computed tomography (CT) scans were analysed and summarized. DA was calculated using a chest CT scan as the reference standard. Furthermore, a binary logistic regression analysis was conducted to investigate the factors influencing the DA of LUS for interstitial syndrome. Results: The ultrasound findings of COVID-19 patients presented mainly as B lines (195/330, 59.1%), unsmooth or interrupted pleural lines (118/330, 35.8%), consolidation lesions (74/330, 22.4%), and pleural effusion (11/330, 3.33%). Compared with the chest CT scan, the DA of LUS for interstitial syndrome, consolidation, pleural effusion, and pleural thickening were 0.821, 0.927, 0.988, and 0.863, respectively. The diagnostic coincidence rate of LUS and chest CT in the mild, common, severe, and critical groups were 93%, 68.6%, 100%, and 100%, respectively. According to the results of the binary logistic regression, sex, disease duration, experience of the doctor, and involved lobes were independent predictors of the DA for interstitial syndrome.Conclusions: LUS had good diagnostic performance for diagnosing COVID-19 pneumonia, and showed a relatively low DA for interstitial syndrome. Female sex, doctors with less experience, long disease duration, and lesions limited to the upper or lower lobes may decrease the DA.