Lung Ultrasound Score: A Potential Prediction Tool In Covid 19

1. Background:During the COVID-19 pandemic, adequate management of available resources may be key to overcoming the excess of seriously ill patients and saving lives. Creating tools to assess disease severity is one of the most important aspects for reducing the burden on emergency departments. Lung ultrasound has high accuracy for diagnosis of pulmonary diseases; however, there are no prospective studies demonstrating that lung ultrasound can predict outcomes in COVID-19. We hypothesized that Lung Ultrasound Score (LUSS) at hospital admission would be able to predict the outcomes of patients with COVID-19.2. Methods:Prospective cohort study conducted from 14 March through 6 May 2020 in the Emergency Department (ED) of an urban, academic, level I trauma center. This 2,200-bed hospital has been designated exclusive for COVID-19 patients for the duration of the pandemic. Patients aged 18 years and older and admitted to the ED with confirmed COVID-19 were considered eligible. Emergency physicians performed lung ultrasounds and calculated LUSS, which was tested for correlation with outcomes.3. Results: Primary endpoint was death from any cause. Secondary endpoints were ICU admission and endotracheal intubation for respiratory failure. Among 180 patients with confirmed COVID-19 who were enrolled (mean age, 60 years; 105 male), the average LUSS was 18.7 ± 6.8. LUSS correlated with findings on chest CT and was able to predict the estimated extent of parenchymal involvement (mean LUSS with < 50% involvement on chest CT, 15±6.7 vs. 21±6.0 with >50% involvement, p<0.001), death (AUC 0.71, OR 1.13, 95%CI 1.07 to 1.21; p < 0.001), endotracheal intubation (AUC 0.75, OR 1.17, 95%CI 1.09 to 1.26; p < 0.001), and ICU admission (AUC: 0.71, OR 1.14, 95%CI 1.07 to 1.21; p < 0.001). 4. Conclusion:LUSS was a good predictor of death, ICU admission, and endotracheal intubation in COVID-19 patients. 5. Trial RegistrationThis protocol was approved by the local Ethics Committee number 3.990.817 (CAAE: 30417520.0.0000.0068).