Ultrasound imaging of the lung (LUS) and associated tissues has demonstrated clinical utility in COVID-19 patients. The aim of the present study was to evaluate the possibilities of a portable pocket-sized ultrasound scanner in the evaluation of lung involvement in patients with COVID-19 pneumonia, in comparison with a high end ultrasound scanner. Statisical analysis will be performed with Stata for Windows V 16 (Stata corp, Texas College, TX). Power size estimation using Medcalc 19.3.1, (MedCalc Software Ltd, Ostenda, B) showed that hat 34 patients would be required for the comparison of the two methods using the Bland-Altman method assuming a mean difference in total score of 1±1, a false positive rate (α) of 0.05 and a false negative rate of 0.1 (β=0.9).
Coronavirus disease 2019 (COVID-19), caused by infection with severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2), emerged in China in December 2019 and quickly spread all
over the globe. The clinical features are fever, dyspnoea, dry cough, fatigue and diarrhoea
(1). Pharyngodynia, nasal congestion, rhinorrhoea and anosmia have also been reported .
Interstitial pneumonia is very common and a high percentage of patients (9-11%) develop
severe acute respiratory distress syndrome (ARDS) and require intensive care. Current
therapeutic strategy involves agents counteracting viral invasion and replication, and
inhibitors of cytokine-sustained inflammatory reactions. No specific antiviral therapy has
yet been identified.
Ultrasound imaging of the lung (LUS) and associated tissues has demonstrated clinical utility
in COVID-19 patients, due to the typical sonographic characteristics of affected lungs. It
provides indications for clinical decisions and the management of associated respiratory
failure and lung injury.
The aim of the present study was to evaluate the possibilities of a portable pocket-sized
ultrasound scanner in the evaluation of lung involvement in patients with COVID-19 pneumonia.
We will perform 34 LUS (lung ultrasound scan) evaluations on patients admitted to the COVID
Unit of Siena University Hospital with symptoms compatible with COVID-19, a positive
SARS-CoV-2 nasal-pharyngeal swab and radiological evidence of interstitial pneumonia.
The patients will be divided into three severity categories based on respiratory impairment:
Mild PaO2/FiO2 > 300 in room air or oxygen flow; Moderate PaO2/FiO2 between 150 and 300 in
room air or oxygen-therapy, CPAP, NIV or HFNC; Severe PaO2/FiO2 < 150 on oxygen-therapy,
CPAP, NIV, HFNC or mechanical ventilation.
The lung ultrasound scans will be performed on the same day with a standard ultrasound
scanner (GE Healthcare, Venue GO) and a pocket-sized ultrasound scanner (Butterfly Network
Inc., Butterfly iQ) for clinical purposes; lung preset will be used with both scanners. Up to
six regions of the chest will be identified: anterosuperior (A); anteroinferior (B);
lateralsuperior (C); lateralinferior (D); posterosuperior (E); posteroinferior (F). One of
four different aeration patterns will be recorded according to a specific scoring system: A =
0 points (normal aeration, presence of lung sliding with A lines or less than two isolated B
lines), B1 = 1 point (moderate loss of lung aeration, multiple well-defined B lines), B2 = 2
points (severe loss of lung aeration, multiple coalescent B lines), C = 3 points (lung
consolidation and tissue-like pattern). Pleural effusion and pneumothorax were also recorded.
A score of 0 was normal and 36 was the worst. Due to clinical conditions, the upper posterior
region (E) could not be explored in some patients, so the mean of the regions explored will
be calculated for the purposes of statistical analysis (total sum (0 to 36) divided by number
of regions explored (5 or 6 on each side).
Diagnostic Test: Butterfly
Standardized lung ultrasound scan with two different instruments
Other Name: GE Healthcare Venue GO
Inclusion Criteria:
- Admitted to hospital ward with a diagnosis of Covid-19 preumonia, confirmed by a
positive rtPCR swab and radiography
Exclusion Criteria:
- Unable/unwilling to cooperate
Azienda Ospedaliera Universitaria Senese
Siena, Si, Italy
Investigator: Sestini Piersante, MD
Contact: +390577586710
piersante.sestini@unisi.it
Piersante Sestini, MD
+393356247055
piersante.sestini@unisi.it
David Bennett, MD, Principal Investigator
Azienda Ospedaliera Universitaria Senese