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American Journal of Respiratory and Critical Care Medicine ; 203(9), 2021.
Article in English | EMBASE | ID: covidwho-1277626

ABSTRACT

RATIONALE During the COVID-19 pandemic, creating tools to assess disease severity is one of the most important aspects of reducing the burden on emergency departments. Lung ultrasound has a high accuracy for the diagnosis of pulmonary diseases;however, there are few prospective studies demonstrating that lung ultrasound can predict outcomes in COVID-19 patients. We hypothesized that lung ultrasound score (LUS) at hospital admission could predict outcomes of COVID-19 patients. METHODS This is a prospective cohort study conducted from 14 March through 6 May 2020 in the emergency department (ED) of an urban, academic, level I trauma center. 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 LUS, which was tested for correlation with outcomes. This protocol was approved by the local Ethics Committee number 3.990.817 (CAAE: 30417520.0.0000.0068). RESULTS The primary endpoint was death from any cause. The 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 LUS was 18.7 ± 6.8. LUS correlated with findings from chest CT and could predict the estimated extent of parenchymal involvement (mean LUS with < 50% involvement on chest CT, 15±6.7 vs. 21±6.0 with >50% involvement, p<0.001), death (AUC 0.72, OR 1.13, 95% CI 1.07 to 1.21;p < 0.001), endotracheal intubation (AUC 0.76, 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). CONCLUSION In this study, LUS was a good predictor of death, ICU admission, and endotracheal intubation in patients with COVID-19 admitted in ED. The study provides support for further research, ideally combining clinical, laboratory, and imaging parameters, to estimate the risk of poor outcomes from COVID-19 infection.

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