Is lung ultrasound score a useful tool to monitoring and handling moderate and severe COVID-19 patients in the general ward? An observational pilot study

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Abstract

Lung ultrasound is a well-established diagnostic tool in acute respiratory failure, and it has been shown to be particularly suited for the management of COVID-19-associated respiratory failure. We present exploratory analyses on the diagnostic and prognostic performance of lung ultrasound score (LUS) in general ward patients with moderate-to-severe COVID-19 pneumonia receiving O2 supplementation and/or noninvasive ventilation. From March 10 through May 1, 2020, 103 lung ultrasound exams were performed by our Forward Intensive Care Team (FICT) on 26 patients (18 males and 8 females), aged 62 (54 – 76) and with a Body Mass Index (BMI) of 30.9 (28.7 – 31.5), a median 6 (5 – 9) days after admission to the COVID-19 medical unit of the University Hospital of Parma, Italy. All patients underwent chest computed tomography (CT) the day of admission. The initial LUS was 16 (11 – 21), which did not significantly correlate with initial CT scans, probably due to rapid progression of the disease and time between CT scan on admission and first FICT evaluation; conversely, LUS was significantly correlated with PaO2/FiO2 ratio throughout patient follow-up [R = − 4.82 (− 6.84 to − 2.80; p < 0.001)]. The area under the receiving operating characteristics curve of LUS for the diagnosis of moderate-severe disease (PaO2/FiO2 ratio ≤ 200 mmHg) was 0.73, with an optimal cutoff value of 11 (positive predictive value: 0.98; negative predictive value: 0.29). Patients who eventually needed invasive ventilation and/or died during admission had significantly higher LUS throughout their stay.

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Baciarello, M., Bonetti, A., Vetrugno, L., Saturno, F., Nouvenne, A., Bellini, V., … Bignami, E. (2022). Is lung ultrasound score a useful tool to monitoring and handling moderate and severe COVID-19 patients in the general ward? An observational pilot study. Journal of Clinical Monitoring and Computing, 36(3), 785–793. https://doi.org/10.1007/s10877-021-00709-w

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