Lung Ultrasound for COVID-19 prognosis a unique experience on elderly patients

Abstract

Introduction: COVID-19 has been a challenging disease to manage at long term care facilities (LTCFs) and nursing homes (NHs). We present a unique experience in a medicalized-NH with elderly patients where we analyzed lung ultrasound (LUS) as a tool to predict the severity of the disease and death.

Methods: All patients admitted to the center were included, recording their background and the clinical features of the disease. We made a descriptive analysis and a multivariate analysis to identify variables linked to a severe disease and to mortality, specially focusing on the ability of LUS to predict clinical outcomes.

Results: We included 288 patients with a median age of 80 years old, 98 (34%) had a severe disease at admission, 38 (13.2%) died and 7 (2.4%) were transferred to the hospital. LUS was performed in 143 (49.7%) patients. We found a significant association between the presence of B lines or focal alteration and a severe disease (P<0.001 and P=0.006 respectively) or death (P=0.005 and P=0.001 respectively). The clinical variables linked to severity in the multivariable analysis were the elevation of RCP (OR=9.53; P=0.046; IC95% 1.03-87.51), the presence of crackles at lung auscultation (OR=10.63; P=0.018; IC95% 1.51-75.02) and focal alterations in LUS (OR=10.65; P=0.046; IC95% 1.04-108.99). If we focus on mortality we found, through the construction of the Cox regression model, that the main variables linked to it were a higher degree of dependence (OR=3.86; P=0.002; IC 95% 1.65 – 9.01) and the presence of B lines at day 1 in LUS (OR=6.06; P=0.019; IC 95% 1.12 – 32.81).

Conclusions: LUS is a useful, unharmful, reproducible and cheap tool that can be used in an outpatient environment in order to predict severity and death in COVID-19 patients and, surely, in other respiratory infections. We also propose an innovative way to manage a vulnerable population in a pandemic context.