<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04433000</url>
  </required_header>
  <id_info>
    <org_study_id>USCovid</org_study_id>
    <nct_id>NCT04433000</nct_id>
  </id_info>
  <brief_title>Reliability of a Pocket Sized Ultrasound Scanner in the Evaluation Covid-19 Pneumonia</brief_title>
  <acronym>USCovid</acronym>
  <official_title>Comparison Between a Pocket Sized and a High End Ultrasound Scanner in the Evaluation of Lung Involvement in Patients With Covid-19 Pneumonia</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Siena</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University of Siena</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Ultrasound imaging of the lung (LUS) and associated tissues has demonstrated clinical utility&#xD;
      in COVID-19 patients. The aim of the present study was to evaluate the possibilities of a&#xD;
      portable pocket-sized ultrasound scanner in the evaluation of lung involvement in patients&#xD;
      with COVID-19 pneumonia, in comparison with a high end ultrasound scanner.&#xD;
&#xD;
      Statisical analysis will be performed with Stata for Windows V 16 (Stata corp, Texas College,&#xD;
      TX). Power size estimation using Medcalc 19.3.1, (MedCalc Software Ltd, Ostenda, B) showed&#xD;
      that hat 34 patients would be required for the comparison of the two methods using the&#xD;
      Bland-Altman method assuming a mean difference in total score of 1±1, a false positive rate&#xD;
      (α) of 0.05 and a false negative rate of 0.1 (β=0.9).&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Coronavirus disease 2019 (COVID-19), caused by infection with severe acute respiratory&#xD;
      syndrome coronavirus 2 (SARS-CoV-2), emerged in China in December 2019 and quickly spread all&#xD;
      over the globe. The clinical features are fever, dyspnoea, dry cough, fatigue and diarrhoea&#xD;
      (1). Pharyngodynia, nasal congestion, rhinorrhoea and anosmia have also been reported .&#xD;
      Interstitial pneumonia is very common and a high percentage of patients (9-11%) develop&#xD;
      severe acute respiratory distress syndrome (ARDS) and require intensive care. Current&#xD;
      therapeutic strategy involves agents counteracting viral invasion and replication, and&#xD;
      inhibitors of cytokine-sustained inflammatory reactions. No specific antiviral therapy has&#xD;
      yet been identified.&#xD;
&#xD;
      Ultrasound imaging of the lung (LUS) and associated tissues has demonstrated clinical utility&#xD;
      in COVID-19 patients, due to the typical sonographic characteristics of affected lungs. It&#xD;
      provides indications for clinical decisions and the management of associated respiratory&#xD;
      failure and lung injury.&#xD;
&#xD;
      The aim of the present study was to evaluate the possibilities of a portable pocket-sized&#xD;
      ultrasound scanner in the evaluation of lung involvement in patients with COVID-19 pneumonia.&#xD;
&#xD;
      We will perform 34 LUS (lung ultrasound scan) evaluations on patients admitted to the COVID&#xD;
      Unit of Siena University Hospital with symptoms compatible with COVID-19, a positive&#xD;
      SARS-CoV-2 nasal-pharyngeal swab and radiological evidence of interstitial pneumonia.&#xD;
&#xD;
      The patients will be divided into three severity categories based on respiratory impairment:&#xD;
      Mild PaO2/FiO2 &gt; 300 in room air or oxygen flow; Moderate PaO2/FiO2 between 150 and 300 in&#xD;
      room air or oxygen-therapy, CPAP, NIV or HFNC; Severe PaO2/FiO2 &lt; 150 on oxygen-therapy,&#xD;
      CPAP, NIV, HFNC or mechanical ventilation.&#xD;
&#xD;
      The lung ultrasound scans will be performed on the same day with a standard ultrasound&#xD;
      scanner (GE Healthcare, Venue GO) and a pocket-sized ultrasound scanner (Butterfly Network&#xD;
      Inc., Butterfly iQ) for clinical purposes; lung preset will be used with both scanners. Up to&#xD;
      six regions of the chest will be identified: anterosuperior (A); anteroinferior (B);&#xD;
      lateralsuperior (C); lateralinferior (D); posterosuperior (E); posteroinferior (F). One of&#xD;
      four different aeration patterns will be recorded according to a specific scoring system: A =&#xD;
      0 points (normal aeration, presence of lung sliding with A lines or less than two isolated B&#xD;
      lines), B1 = 1 point (moderate loss of lung aeration, multiple well-defined B lines), B2 = 2&#xD;
      points (severe loss of lung aeration, multiple coalescent B lines), C = 3 points (lung&#xD;
      consolidation and tissue-like pattern). Pleural effusion and pneumothorax were also recorded.&#xD;
      A score of 0 was normal and 36 was the worst. Due to clinical conditions, the upper posterior&#xD;
      region (E) could not be explored in some patients, so the mean of the regions explored will&#xD;
      be calculated for the purposes of statistical analysis (total sum (0 to 36) divided by number&#xD;
      of regions explored (5 or 6 on each side).&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">March 15, 2020</start_date>
  <completion_date type="Anticipated">June 10, 2020</completion_date>
  <primary_completion_date type="Actual">June 10, 2020</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Only</observational_model>
    <time_perspective>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Bland-Altman estimate of bias and Limits of Agreement (LoA) of patient mean scores obtained with the two instruments</measure>
    <time_frame>1 day</time_frame>
    <description>The more widely accepted measure of agreement beteen two instruments. Bland JM, Altman DG (1986) Statistical method for assessing agreement between two methods of clinical measurement. The Lancet i:307-310</description>
  </primary_outcome>
  <enrollment type="Anticipated">34</enrollment>
  <condition>Covid-19 Pneumonia</condition>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Butterfly</intervention_name>
    <description>Standardized lung ultrasound scan with two different instruments</description>
    <other_name>GE Healthcare Venue GO</other_name>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Patients admitted to hospital ward with a diagnosis of Covid-19 preumonia, confirmed by a&#xD;
        positive rtPCR swab and radiography&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Admitted to hospital ward with a diagnosis of Covid-19 preumonia, confirmed by a&#xD;
             positive rtPCR swab and radiography&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Unable/unwilling to cooperate&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>David Bennett, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Azienda Ospedaliera Universitaria Senese</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Piersante Sestini, MD</last_name>
    <phone>+393356247055</phone>
    <email>piersante.sestini@unisi.it</email>
  </overall_contact>
  <location>
    <facility>
      <name>Azienda Ospedaliera Universitaria Senese</name>
      <address>
        <city>Siena</city>
        <state>Si</state>
        <zip>53100</zip>
        <country>Italy</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Sestini Piersante, MD</last_name>
      <phone>+390577586710</phone>
      <email>piersante.sestini@unisi.it</email>
    </contact>
  </location>
  <location_countries>
    <country>Italy</country>
  </location_countries>
  <verification_date>June 2020</verification_date>
  <study_first_submitted>June 12, 2020</study_first_submitted>
  <study_first_submitted_qc>June 13, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 16, 2020</study_first_posted>
  <last_update_submitted>June 13, 2020</last_update_submitted>
  <last_update_submitted_qc>June 13, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">June 16, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Siena</investigator_affiliation>
    <investigator_full_name>Piersante Sestini</investigator_full_name>
    <investigator_title>Associate professor of respiratory diseases</investigator_title>
  </responsible_party>
  <keyword>Covid-19</keyword>
  <keyword>pneumonia</keyword>
  <keyword>lung ultrasound</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>COVID-19</mesh_term>
    <mesh_term>Pneumonia</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>The whole anonymized dataset could be shared</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_time_frame>from the month of July, for one year</ipd_time_frame>
    <ipd_access_criteria>on request by email</ipd_access_criteria>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04433000
org study id: USCovid
nct id: NCT04433000
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
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).
observational model: Case-Only
time perspective: Retrospective
measure: Bland-Altman estimate of bias and Limits of Agreement (LoA) of patient mean scores obtained with the two instruments
time frame: 1 day
description: The more widely accepted measure of agreement beteen two instruments. Bland JM, Altman DG (1986) Statistical method for assessing agreement between two methods of clinical measurement. The Lancet i:307-310
intervention type: Diagnostic Test
intervention name: Butterfly
description: Standardized lung ultrasound scan with two different instruments
other name: GE Healthcare Venue GO
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: No
last name: David Bennett, MD
role: Principal Investigator
affiliation: Azienda Ospedaliera Universitaria Senese
last name: Piersante Sestini, MD
phone: +393356247055
email: piersante.sestini@unisi.it
facility: 
status: Recruiting
contact: 
country: Italy
responsible party type: Principal Investigator
investigator affiliation: University of Siena
investigator full name: Piersante Sestini
investigator title: Associate professor of respiratory diseases
mesh term: COVID-19
mesh term: Pneumonia
sharing ipd: Yes
ipd description: The whole anonymized dataset could be shared
ipd info type: Study Protocol
ipd time frame: from the month of July, for one year
ipd access criteria: on request by email