Prognostic Value of Bedside Lung Utrasound Score in Patients With COVID-19

Li Ji; Chunyan Cao; Ying Gao; Wen Zhang; Yuji Xie; Yilian Duan; Shuangshuang Kong; Manjie You; Rong Ma; Lili Jiang; Jie Liu; Zhenxing Sun; Ziming Zhang; Jing Wang; Yali Yang; Qing Lv; Li Zhang; Yuman Li; Jinxiang Zhang; Mingxing Xie

Disclosures

Crit Care. 2020;24(700) 

In This Article

Abstract and Introduction

Abstract

Background: Bedside lung ultrasound (LUS) has emerged as a useful and non-invasive tool to detect lung involvement and monitor changes in patients with coronavirus disease 2019 (COVID-19). However, the clinical significance of the LUS score in patients with COVID-19 remains unknown. We aimed to investigate the prognostic value of the LUS score in patients with COVID-19.

Method: The LUS protocol consisted of 12 scanning zones and was performed in 280 consecutive patients with COVID-19. The LUS score based on B-lines, lung consolidation and pleural line abnormalities was evaluated.

Results: The median time from admission to LUS examinations was 7 days (interquartile range [IQR] 3–10). Patients in the highest LUS score group were more likely to have a lower lymphocyte percentage (LYM%); higher levels of D-dimer, C-reactive protein, hypersensitive troponin I and creatine kinase muscle-brain; more invasive mechanical ventilation therapy; higher incidence of ARDS; and higher mortality than patients in the lowest LUS score group. After a median follow-up of 14 days [IQR, 10–20 days], 37 patients developed ARDS, and 13 died. Patients with adverse outcomes presented a higher rate of bilateral involvement; more involved zones and B-lines, pleural line abnormalities and consolidation; and a higher LUS score than event-free survivors. The Cox models adding the LUS score as a continuous variable (hazard ratio [HR]: 1.05, 95% confidence intervals [CI] 1.02 ~ 1.08; P < 0.001; Akaike information criterion [AIC] = 272; C-index = 0.903) or as a categorical variable (HR 10.76, 95% CI 2.75 ~ 42.05; P = 0.001; AIC = 272; C-index = 0.902) were found to predict poor outcomes more accurately than the basic model (AIC = 286; C-index = 0.866). An LUS score cut-off > 12 predicted adverse outcomes with a specificity and sensitivity of 90.5% and 91.9%, respectively.

Conclusions: The LUS score devised by our group performs well at predicting adverse outcomes in patients with COVID-19 and is important for risk stratification in COVID-19 patients.

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