<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/NCT04450368</url>
  </required_header>
  <id_info>
    <org_study_id>20-30080</org_study_id>
    <nct_id>NCT04450368</nct_id>
  </id_info>
  <brief_title>Clinical Feasibility of a Non-invasive Wearable Acoustic Device for Measuring Air Trapping in COPD</brief_title>
  <official_title>Clinical Feasibility of a Non-invasive Wearable Acoustic Device for Measuring Air Trapping in COPD</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Respira Labs, Inc</agency>
      <agency_class>Industry</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Palo Alto Medical Foundation</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Respira Labs, Inc</source>
  <oversight_info>
    <has_dmc>Yes</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>
      This is a pilot observational study during which the investigators will conduct a&#xD;
      longitudinal assessment of air trapping (with up to 2 visits) in 40 patients with COPD and&#xD;
      variable degrees of air trapping and 20 healthy controls using ARIA. The investigators will&#xD;
      characterize the clinical phenotype of the subjects by administering health and symptom-based&#xD;
      questionnaires and obtaining lung function testing at rest and during exertion, and will then&#xD;
      correlate and validate the ARIA-based indices with those of the more traditional physiologic&#xD;
      measures of static and dynamic air trapping.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Chronic Obstructive Pulmonary Disease (COPD) is the fourth leading cause of hospitalization&#xD;
      in the United States. Exacerbations, a worsening or &quot;flare up&quot; of symptoms cause most COPD&#xD;
      hospitalizations. Early detection of lung function deterioration would facilitate early&#xD;
      intervention and help prevent hospitalizations, since most exacerbations can be treated with&#xD;
      changes of inhalers and/or oral medications. Air trapping, defined as an abnormal increase in&#xD;
      the volume of air remaining in the lungs after exhalation, is a common finding in all forms&#xD;
      of COPD. Air trapping has been shown to increase during exacerbations and decrease when&#xD;
      exacerbations resolve. Moreover, increasing recent evidence indicates that air trapping is an&#xD;
      earlier harbinger of deteriorating lung function than spirometric changes. Recent research&#xD;
      shows that lung air trapping can be measured by low-frequency ultrasound (1-40 kHz). Thus,&#xD;
      acoustic monitoring of air trapping could provide clinicians with a non-invasive tool to when&#xD;
      medical intervention is needed to avoid unnecessary ER visits and hospitalizations. The&#xD;
      investigators have developed a low-cost, non-invasive, acoustic-based wearable device, Sylvee&#xD;
      that is capable of continuous monitoring of lung resonance. The device has machine-learning&#xD;
      algorithms that can detect minor changes in lung resonance, which our preliminary results&#xD;
      suggest corresponds to changes in air trapping. The overall objective of this pilot project&#xD;
      is to validate Sylvee's algorithms in a cohort of 60 patients with COPD and variable degree&#xD;
      of air trapping. Ultimately, Sylvee will allow physicians to remotely monitor their patients'&#xD;
      lung function and adjust their medications to reduce healthcare costs and improve patients'&#xD;
      quality of life.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Terminated</overall_status>
  <why_stopped>
    Site failed to hit recruitment targets&#xD;
  </why_stopped>
  <start_date type="Actual">March 1, 2022</start_date>
  <completion_date type="Actual">June 1, 2023</completion_date>
  <primary_completion_date type="Actual">May 30, 2023</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Other</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Change and variability fo acoustic resonance</measure>
    <time_frame>4 hours</time_frame>
    <description>The change and variability of acoustic resonance features before, during, and after all pulmonary tests, including those where dynamic hyperinflation will be tested: metronome-paced IC, 6-minute walk test and cardio-pulmonary exercise [every session]. Acoustic features will be extracted from the measurements with an active acoustic sensor worn on the chest, establishing a baseline before and after all tests. Acoustic resonance changes and their rate of change will be recorded.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Correlation between acoustic resonance measurements with clinical testing</measure>
    <time_frame>2 hours</time_frame>
    <description>The correlation between acoustic resonance measurements and other measurements from pulmonary function tests and wearable devices (respiratory rate, heart rate and oxygen saturation with 80% accuracy rate) before, during (every minute) and after all tests [every session]. Acoustic features will be extracted from the measurements with active acoustic sensors worn on the chest. Other measurements will be measured using medical graded devices such as pulse-oximeters and wearables.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Correlation between acoustic resonance and symptoms</measure>
    <time_frame>1 hour</time_frame>
    <description>The correlation between acoustic resonance measurements and patient symptoms and vitals before, during and after all pulmonary function tests, including those where dynamic hyperinflation will be tested: metronome-paced IC, 6-minute walk test and cardio-pulmonary exercise [every session]. Acoustic features will be extracted from the measurements with an active acoustic sensor worn on the chest. Patient symptoms and vitals will be collected before and after all tests.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Data quality and user experience with medical-grade adhesive</measure>
    <time_frame>30 minutes</time_frame>
    <description>The correlation between medical-grade adhesive options, session length, data quality and patient experience with sensor attachment and detachment procedures. For example: Medical-grade adhesive options will be presented to users at different sessions. Ease of setup, attachment, detachment and data quality will be recorded on a questionnaire for further correlation. A questionnaire with scales from easy-to-hard will be prepared to allow for quantification of different options. The correlation between companion app screens and flows: ease of performing tasks, reading measurements and free-form feedback. Pre-selected alternative application screens, flows and options will be shown to the user in the mobile app and their feedback recorded (free form notes) for User Experience iteration.</description>
  </secondary_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Actual">8</enrollment>
  <condition>COPD</condition>
  <condition>COPD Exacerbation</condition>
  <arm_group>
    <arm_group_label>Cases with Air Trapping</arm_group_label>
    <description>20 COPD patients with lung volumes representing air trapping (RV/TLC and functional residual capacity to TLC [FRC/TLC])</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Cases without Air Trapping</arm_group_label>
    <description>20 COPD patients without lung volumes representing air trapping (RV/TLC and functional residual capacity to TLC [FRC/TLC])</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Healthy Controls</arm_group_label>
    <description>Non COPD patients and non-smokers</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Sylvee</intervention_name>
    <description>The investigators have developed a small sensor that has the same characteristics as a combined hearing aid used for Tinnitus. It has a noise generator intended to transmit white noise (2 - 20 KHz) and a microphone similar to those used in hearing aids to provide sound amplification. Our sensor is substantially equivalent to legally FDA approved marketed devices that can be used for several hours per day. Although it will introduce new indications for use (lung resonance capture), it has the same technological characteristics and will not introduce new hazards or safety risks. Several sound-based devices are already in use for clearing mucus from the lungs by generating and delivering low frequency sound that vibrates the airways and lung secretions, causing them to thin and become expelled. The devices are placed on the patient's chest for up to 3-4 hours in COPD, cystic fibrosis (CF) and other lung diseases.</description>
    <arm_group_label>Cases with Air Trapping</arm_group_label>
    <arm_group_label>Cases without Air Trapping</arm_group_label>
    <arm_group_label>Healthy Controls</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Outpatients People who have a condition but who are not being seen as patients Students&#xD;
        Staff of UCSF or affiliated institutions&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion criteria for cases (COPD patients) are:&#xD;
&#xD;
          1. Men or women over 40 years old.&#xD;
&#xD;
          2. Spirometric COPD.&#xD;
&#xD;
          3. A history of smoking at least 20 pack-years.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Inability to perform lung function testing.&#xD;
&#xD;
          2. Inability to complete the study and return for follow-up visits.&#xD;
&#xD;
          3. Pregnancy.&#xD;
&#xD;
          4. A serious and active heart condition, defined by stable or unstable angina, recent&#xD;
             myocardial infarction (within the last 2 years), active or decompensated congestive&#xD;
             heart failure or cardiomyopathy.&#xD;
&#xD;
          5. End-stage liver disease.&#xD;
&#xD;
          6. Patients unable to do mild exercise (patients with orthopedic-neurologic problems;&#xD;
             patients who have severe heart failure characterized by an ejection fraction of &lt;20%&#xD;
             or by New York Heart Association Class IV disease; patients who should be at complete&#xD;
             rest, confined to a bed or chair; or patients for whom physical activity brings on&#xD;
             discomfort and for whom symptoms occur at rest).&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
  </eligibility>
  <overall_official>
    <last_name>Ganesh Krishna, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Principal Investigator</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>El Camino Hospital</name>
      <address>
        <city>Mountain View</city>
        <state>California</state>
        <zip>94040</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>June 2023</verification_date>
  <study_first_submitted>June 24, 2020</study_first_submitted>
  <study_first_submitted_qc>June 24, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 29, 2020</study_first_posted>
  <last_update_submitted>June 14, 2023</last_update_submitted>
  <last_update_submitted_qc>June 14, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">June 18, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Pulmonary Disease, Chronic Obstructive</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </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/NCT04450368
org study id: 20-30080
nct id: NCT04450368
lead sponsor: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
This is a pilot observational study during which the investigators will conduct a
      longitudinal assessment of air trapping (with up to 2 visits) in 40 patients with COPD and
      variable degrees of air trapping and 20 healthy controls using ARIA. The investigators will
      characterize the clinical phenotype of the subjects by administering health and symptom-based
      questionnaires and obtaining lung function testing at rest and during exertion, and will then
      correlate and validate the ARIA-based indices with those of the more traditional physiologic
      measures of static and dynamic air trapping.
Chronic Obstructive Pulmonary Disease (COPD) is the fourth leading cause of hospitalization
      in the United States. Exacerbations, a worsening or "flare up" of symptoms cause most COPD
      hospitalizations. Early detection of lung function deterioration would facilitate early
      intervention and help prevent hospitalizations, since most exacerbations can be treated with
      changes of inhalers and/or oral medications. Air trapping, defined as an abnormal increase in
      the volume of air remaining in the lungs after exhalation, is a common finding in all forms
      of COPD. Air trapping has been shown to increase during exacerbations and decrease when
      exacerbations resolve. Moreover, increasing recent evidence indicates that air trapping is an
      earlier harbinger of deteriorating lung function than spirometric changes. Recent research
      shows that lung air trapping can be measured by low-frequency ultrasound (1-40 kHz). Thus,
      acoustic monitoring of air trapping could provide clinicians with a non-invasive tool to when
      medical intervention is needed to avoid unnecessary ER visits and hospitalizations. The
      investigators have developed a low-cost, non-invasive, acoustic-based wearable device, Sylvee
      that is capable of continuous monitoring of lung resonance. The device has machine-learning
      algorithms that can detect minor changes in lung resonance, which our preliminary results
      suggest corresponds to changes in air trapping. The overall objective of this pilot project
      is to validate Sylvee's algorithms in a cohort of 60 patients with COPD and variable degree
      of air trapping. Ultimately, Sylvee will allow physicians to remotely monitor their patients'
      lung function and adjust their medications to reduce healthcare costs and improve patients'
      quality of life.
observational model: Other
time perspective: Prospective
measure: Change and variability fo acoustic resonance
time frame: 4 hours
description: The change and variability of acoustic resonance features before, during, and after all pulmonary tests, including those where dynamic hyperinflation will be tested: metronome-paced IC, 6-minute walk test and cardio-pulmonary exercise [every session]. Acoustic features will be extracted from the measurements with an active acoustic sensor worn on the chest, establishing a baseline before and after all tests. Acoustic resonance changes and their rate of change will be recorded.
measure: Correlation between acoustic resonance measurements with clinical testing
time frame: 2 hours
description: The correlation between acoustic resonance measurements and other measurements from pulmonary function tests and wearable devices (respiratory rate, heart rate and oxygen saturation with 80% accuracy rate) before, during (every minute) and after all tests [every session]. Acoustic features will be extracted from the measurements with active acoustic sensors worn on the chest. Other measurements will be measured using medical graded devices such as pulse-oximeters and wearables.
measure: Correlation between acoustic resonance and symptoms
time frame: 1 hour
description: The correlation between acoustic resonance measurements and patient symptoms and vitals before, during and after all pulmonary function tests, including those where dynamic hyperinflation will be tested: metronome-paced IC, 6-minute walk test and cardio-pulmonary exercise [every session]. Acoustic features will be extracted from the measurements with an active acoustic sensor worn on the chest. Patient symptoms and vitals will be collected before and after all tests.
measure: Data quality and user experience with medical-grade adhesive
time frame: 30 minutes
description: The correlation between medical-grade adhesive options, session length, data quality and patient experience with sensor attachment and detachment procedures. For example: Medical-grade adhesive options will be presented to users at different sessions. Ease of setup, attachment, detachment and data quality will be recorded on a questionnaire for further correlation. A questionnaire with scales from easy-to-hard will be prepared to allow for quantification of different options. The correlation between companion app screens and flows: ease of performing tasks, reading measurements and free-form feedback. Pre-selected alternative application screens, flows and options will be shown to the user in the mobile app and their feedback recorded (free form notes) for User Experience iteration.
arm group label: Cases with Air Trapping
description: 20 COPD patients with lung volumes representing air trapping (RV/TLC and functional residual capacity to TLC [FRC/TLC])
arm group label: Cases without Air Trapping
description: 20 COPD patients without lung volumes representing air trapping (RV/TLC and functional residual capacity to TLC [FRC/TLC])
arm group label: Healthy Controls
description: Non COPD patients and non-smokers
intervention type: Device
intervention name: Sylvee
description: The investigators have developed a small sensor that has the same characteristics as a combined hearing aid used for Tinnitus. It has a noise generator intended to transmit white noise (2 - 20 KHz) and a microphone similar to those used in hearing aids to provide sound amplification. Our sensor is substantially equivalent to legally FDA approved marketed devices that can be used for several hours per day. Although it will introduce new indications for use (lung resonance capture), it has the same technological characteristics and will not introduce new hazards or safety risks. Several sound-based devices are already in use for clearing mucus from the lungs by generating and delivering low frequency sound that vibrates the airways and lung secretions, causing them to thin and become expelled. The devices are placed on the patient's chest for up to 3-4 hours in COPD, cystic fibrosis (CF) and other lung diseases.
arm group label: Cases with Air Trapping
arm group label: Cases without Air Trapping
arm group label: Healthy Controls
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
last name: Ganesh Krishna, MD
role: Principal Investigator
affiliation: Principal Investigator
facility: 
country: United States
responsible party type: Sponsor
mesh term: Pulmonary Disease, Chronic Obstructive
sharing ipd: No