Abstract
Background: Lung ultrasound can accurately detect pandemic coronavirus disease (COVID-19) pulmonary lesions. A lung ultrasound score (LUS) was developed to improve reproducibility of the technique.
Objectives: To evaluate the clinical value of LUS monitoring to guide COVID-19-associated acute respiratory distress syndrome (ARDS) management.
Methods: We conducted a single center, prospective observational study, including all patients admitted with COVID-19-associated ARDS between March and April 2020. A systematic daily LUS evaluation was performed.
Results: Thirty-three consecutive patients were included. LUS was significantly and negatively correlated to P aO2 /F IO2 . LUS increased significantly over time in non-survivors compared to survivors. LUS increased in 83% of ventilatory associated pneumonia (VAP) episodes, when compared to the previous LUS evaluation. LUS was not significantly higher in patients presenting post-extubation respiratory failure.
Conclusions: In conclusion, our study demonstrates that LUS variations are correlated to disease severity and progression, and LUS monitoring could contribute to the early diagnosis of VAPs.
Keywords: ARDS; COVID-19; Critical care; Pneumonia; Ultrasonography; Ventilator-associated pneumonia.
【저자키워드】 COVID-19, ARDS, Critical care, Pneumonia, Ultrasonography, Ventilator-Associated Pneumonia., 【초록키워드】 ARDS, Critical care, Respiratory failure, acute respiratory distress syndrome, prospective observational study, disease severity, Variation, lung, progression, observational study, early diagnosis, Survivors, management, Patient, disease, acute respiratory distress, pandemic coronavirus, Ultrasonography, Ventilator-associated pneumonia, respiratory distress, technique, syndrome, ventilatory, pulmonary lesions, single center, reproducibility, VAP, non-survivor, COVID-19-associated ARDS, IMPROVE, detect, evaluate, significantly, conducted, was performed, contribute, correlated, significantly higher, presenting, consecutive patient, 【제목키워드】 Pneumonia, Disease progression, MONITOR, detect,