xml: <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/NCT06013917</url>
    </required_header>
    <id_info>
      <org_study_id>Pro00065572</org_study_id>
      <secondary_id>R41HL160317-01A1</secondary_id>
      <nct_id>NCT06013917</nct_id>
    </id_info>
    <brief_title>Artificial Intelligence (AI) Enabled, Cloud-based ECG Diagnostic Solution (ZBPro) Feasibility Testing</brief_title>
    <official_title>Feasibility Testing of a Novel AI-enabled, Cloud-based ECG Diagnostic Solution to Enable Fast and Affordable Diagnosis in Long-term Continuous Ambulatory ECG Monitoring</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>ZBeats INC</agency>
        <agency_class>Industry</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>National Heart, Lung, and Blood Institute (NHLBI)</agency>
        <agency_class>NIH</agency_class>
      </collaborator>
      <collaborator>
        <agency>Stony Brook University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Main Line Health</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>ZBeats INC</source>
    <oversight_info>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>Yes</is_fda_regulated_device>
      <is_us_export>No</is_us_export>
    </oversight_info>
    <brief_summary>
      <textblock>
        The proposed research is to address the accessibility and affordability of technology to&#xD;
        capture symptomatic and asymptomatic cardiac events via Long-Term Continuous&#xD;
        Electrocardiogram Monitoring (LTCM), and to provide physicians with full access to their&#xD;
        patients' recorded data in a timely manner. We adopt an FDA cleared single- lead OEM patch&#xD;
        Holter made of flexible material to make long-term wearing more comfortable and more patient&#xD;
        compliant. The patch transmits the recorded data to our cloud-based platform: ZBPro™, where&#xD;
        our innovative technologies reside. Our proprietary AI algorithms with innovative human&#xD;
        interaction tools, which were developed under the National Science Foundation (NSF) Small&#xD;
        Business Innovation Research (SBIR) Phase I (Award #: 2025951) Award analyze and interpret&#xD;
        the recorded data to detect and annotate arrhythmia/cardiac events, and generates daily&#xD;
        reports for physician review. The feasibility of our algorithms has been verified using&#xD;
        ZBeats' proprietary ECG database based on the standard ANSI/AAMI EC57. Data collection and&#xD;
        transmission has been verified in the office environment.&#xD;
  &#xD;
        This proposed observational study will utilize a multidisciplinary collaboration of ZBeats&#xD;
        Inc. (ZBTS), Stony Brook University (SBU), and Lankenau Medical Center (LMC). The study will&#xD;
        enroll patients undergoing ECG monitoring. The primary outcome measure will be the ability to&#xD;
        capture cardiac arrhythmias and events from participants. The prescribed FDA-cleared device&#xD;
        will serve as the ground truth (GT) for our analyses. The detected arrhythmias and events&#xD;
        from our solution will be compared with the findings from the ground truth to obtain our&#xD;
        system's detection rate. The goal is to achieve a detection rate of &gt;80% to be deemed&#xD;
        successful.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        The proposed research is to address the accessibility and affordability of technology to&#xD;
        capture symptomatic and asymptomatic cardiac events via Long-Term Continuous&#xD;
        Electrocardiogram Monitoring (LTCM), and to provide physicians with full access to their&#xD;
        patients' recorded data in a timely manner. We adopt an FDA cleared single- lead OEM patch&#xD;
        Holter made of flexible material to make long-term wearing more comfortable and more patient&#xD;
        compliant. The patch transmits the recorded data to our cloud-based platform: ZBPro™, where&#xD;
        our innovative technologies reside. Our proprietary AI algorithms with innovative human&#xD;
        interaction tools, which were developed under the NSF SBIR Phase I (Award #: 2025951) Award&#xD;
        analyze and interpret the recorded data to detect and annotate arrhythmia/cardiac events, and&#xD;
        generates daily reports for physician review. The feasibility of our algorithms has been&#xD;
        verified using ZBeats' proprietary ECG database based on the standard ANSI/AAMI EC57. Data&#xD;
        collection and transmission has been verified in the office environment.&#xD;
  &#xD;
        Specific Aim 1: Study Setup: Setup the study REDCap instance with role-based access under&#xD;
        SBU's REDCap system. Prepare data collection forms. Deliver the study devices to clinical&#xD;
        sites. Provide training to clinical personnel regarding the study, procedure, informed&#xD;
        consent and data collection. Project team assess the protocols and training are in place for&#xD;
        the study.&#xD;
  &#xD;
        Specific Aim 2: Acceptability Evaluation: Identify and evaluate the device acceptability in&#xD;
        up-to-7-day wearing. 60-75 participants will be enrolled during 6-7-month study period.&#xD;
        Participants' enrollment, follow-up and closeout questionnaires regarding the acceptability&#xD;
        will be conducted in-person or via telephone by the research associate in each clinical site.&#xD;
        Success of Aim 2: the mean acceptability percentage of the close-out survey will be &gt; 70%.&#xD;
  &#xD;
        Specific Aim 3: Arrhythmia Capture Evaluation: Evaluate devices' ability to detect cardiac&#xD;
        arrhythmia and events, as well as the ECG signal quality. Physicians' questionnaire will be&#xD;
        completed by the physicians from each clinical site after ZBeats' reports are reviewed and&#xD;
        compare with reports generated by the prescription device as the ground truth. The quality of&#xD;
        signals will be assessed by an independent cardiologist. Success of Aim 3: the physician's&#xD;
        having a 7-day acceptance rate of &gt; 80% and a detection sensitivity of &gt; 80%.&#xD;
  &#xD;
        Specific Aim 4: Drafting the study protocol and business plan for Phase II: Conduct&#xD;
        statistical analysis, sample size calculations, provide projections, start working on the&#xD;
        protocol for Phase II study.&#xD;
  &#xD;
        Success of this project will resolve the feasibility concern of the proposed LTCM solution in&#xD;
        clinical practice, enabling physicians with more proactive participation in early detection&#xD;
        of cardiac arrhythmias and accurate risk stratification. Moreover, the proposed Phase I and&#xD;
        Phase II studies will mitigate commercialization risk by showing clinical evidence to prove&#xD;
        its substantial equivalence to the predicate device to receive FDA 510k cleared as well as&#xD;
        Medicare's approval.&#xD;
  &#xD;
        This proposed observational study will utilize a multidisciplinary collaboration of ZBeats&#xD;
        INC (ZBTS), Stony Brook University (SBU), and Lankenau Medical Center (LMC). The study will&#xD;
        enroll patients undergoing ECG monitoring. Patients will be asked to wear the study monitor&#xD;
        and be followed for up to 7 days while wearing their prescribed FDA cleared devices&#xD;
        simultaneously. The study does not intend to use any data or information from the&#xD;
        investigational solution to interfere, intervene or affect any clinical decisions made for&#xD;
        the participants. The primary outcome measure will be the ability to capture cardiac&#xD;
        arrhythmias and events from participants. The prescribed FDA-cleared device will serve as the&#xD;
        ground truth (GT) for our analyses. The detected arrhythmias and events from our solution&#xD;
        will be compared with the findings from the ground truth to obtain our system's detection&#xD;
        rate. The goal is to achieve a detection rate of &gt;80% to be deemed successful. The secondary&#xD;
        outcome measures include: 1) assessing signal quality by conducting independent reviewer's&#xD;
        questionnaire; and, 2) assessing user acceptability by obtaining participants' and&#xD;
        physicians' questionnaire.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">August 2023</start_date>
    <completion_date type="Anticipated">May 2024</completion_date>
    <primary_completion_date type="Anticipated">May 2024</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>Capturing cardiac arrhythmias and events</measure>
      <time_frame>7 days after intervention</time_frame>
      <description>The ability to capture cardiac arrhythmias and events from participants will be the primary outcome of this study. The prescribed FDA-cleared device will serve as the ground truth (GT) for our analyses. The detected arrhythmias and events from our solution will be compared with the findings from the ground truth to obtain our system's detection rate. The goal is to achieve a detection rate of &gt;80% to be deemed successful.</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Assessing signal quality</measure>
      <time_frame>7 days after intervention</time_frame>
      <description>Assessing signal quality by conducting independent reviewer's questionnaire. An average score &gt;70% across all domains will define success.</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Assessing user acceptability</measure>
      <time_frame>7 days after intervention</time_frame>
      <description>Assessing user acceptability by obtaining participants' and physicians' questionnaire. An average score &gt;70% across all domains will define success.</description>
    </secondary_outcome>
    <number_of_groups>1</number_of_groups>
    <enrollment type="Anticipated">75</enrollment>
    <condition>Arrhythmias, Cardiac</condition>
    <arm_group>
      <arm_group_label>Patients on ECG monitoring post-transcatheter aortic valve replacement (TAVR) or other cardiac event</arm_group_label>
      <description>Patients at our clinical collaborators practices who have undergone TAVR or other cardiac event and who are placed on ECG monitoring will be placed on an FDA cleared cardiac monitor. We adopt an FDA cleared, reusable, single-lead OEM patch Holter made of flexible material to make long-term wearing more comfortable and more patient compliance.</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>Cardiac Monitoring</intervention_name>
      <description>FDA cleared ECG monitoring device that will be used to obtain ECG recordings and capture cardiac arrhythmias/events from participants</description>
      <arm_group_label>Patients on ECG monitoring post-transcatheter aortic valve replacement (TAVR) or other cardiac event</arm_group_label>
    </intervention>
    <eligibility>
      <study_pop>
        <textblock>
          Our study population will include patients that are prescribed to undergo ECG monitoring&#xD;
          following a TAVR or recent cardiac-related event. We will recruit 60-75 participants to&#xD;
          provide 62-78 events. SBU will recruit 15-20 TAVR patients (&lt; 4 participants /month, &lt; 2 in&#xD;
          any week). LMC will recruit 10-15 TAVR patients &amp; 35-40 other cardiac patients (&lt; 10&#xD;
          participants/month, &lt; 4 in any week). A combined recruitment pool of 956 patients can be&#xD;
          identified within 7 months from both sites.&#xD;
        </textblock>
      </study_pop>
      <sampling_method>Non-Probability Sample</sampling_method>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            1. Patients who are &gt; 18 years of age&#xD;
  &#xD;
            2. Patients who are from one of the clinical collaborators practices&#xD;
  &#xD;
            3. Patients who are prescribed to undergo ECG monitoring using an FDA-cleared monitoring&#xD;
               device&#xD;
  &#xD;
            4. Patients who are post TAVR procedure, a recent history of stroke/TIA, or having&#xD;
               cardiac related symptoms&#xD;
  &#xD;
            5. Patients who are comfortable using a smartphone or have someone in the home to help&#xD;
               with data transmission&#xD;
  &#xD;
            6. Patients who have manual dexterity to be able to recharge the phone battery or someone&#xD;
               in the home to help them&#xD;
  &#xD;
            7. Patients who are English speaking&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            1. Patients who are &lt;18 years of age&#xD;
  &#xD;
            2. Patients who are not being prescribed with cardiac monitor testing&#xD;
  &#xD;
            3. Patients who refuse to sign informed consent&#xD;
  &#xD;
            4. Patients who are unable to provide informed consent&#xD;
  &#xD;
            5. Patients who have a pacemaker implanted&#xD;
  &#xD;
            6. Patients who are presenting with any dermatitis or infected skin over left anterior&#xD;
               thorax&#xD;
  &#xD;
            7. Patients who have a history of reaction to a prior cardiac monitor device&#xD;
  &#xD;
            8. Patients who are uncomfortable having a cell phone at home for the duration of study&#xD;
               participation&#xD;
  &#xD;
            9. Patients who non-English speaking&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>18 Years</minimum_age>
      <maximum_age>N/A</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Puja Parikh, MD</last_name>
      <role>Principal Investigator</role>
      <affiliation>Stony Brook University</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Bin Fang, PhD</last_name>
      <phone>6312202463</phone>
      <email>bin.fang@zbeats.co</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Ashutosh Yaligar, MBA</last_name>
      <phone>5182219417</phone>
      <email>ashutosh.yaligar@zbeats.co</email>
    </overall_contact_backup>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 22, 2023</study_first_submitted>
    <study_first_submitted_qc>August 22, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 28, 2023</study_first_posted>
    <last_update_submitted>August 22, 2023</last_update_submitted>
    <last_update_submitted_qc>August 22, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 28, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <keyword>Artificial Intelligence</keyword>
    <keyword>Cardiac Monitoring</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Arrhythmias, Cardiac</mesh_term>
    </condition_browse>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT06013917
  org study id: Pro00065572
  secondary id: R41HL160317-01A1
  nct id: NCT06013917
  lead sponsor: 
  collaborator: 
  collaborator: 
  collaborator: 
  is fda regulated drug: No
  is fda regulated device: Yes
  is us export: No
  The proposed research is to address the accessibility and affordability of technology to
        capture symptomatic and asymptomatic cardiac events via Long-Term Continuous
        Electrocardiogram Monitoring (LTCM), and to provide physicians with full access to their
        patients' recorded data in a timely manner. We adopt an FDA cleared single- lead OEM patch
        Holter made of flexible material to make long-term wearing more comfortable and more patient
        compliant. The patch transmits the recorded data to our cloud-based platform: ZBPro™, where
        our innovative technologies reside. Our proprietary AI algorithms with innovative human
        interaction tools, which were developed under the National Science Foundation (NSF) Small
        Business Innovation Research (SBIR) Phase I (Award #: 2025951) Award analyze and interpret
        the recorded data to detect and annotate arrhythmia/cardiac events, and generates daily
        reports for physician review. The feasibility of our algorithms has been verified using
        ZBeats' proprietary ECG database based on the standard ANSI/AAMI EC57. Data collection and
        transmission has been verified in the office environment.
  
        This proposed observational study will utilize a multidisciplinary collaboration of ZBeats
        Inc. (ZBTS), Stony Brook University (SBU), and Lankenau Medical Center (LMC). The study will
        enroll patients undergoing ECG monitoring. The primary outcome measure will be the ability to
        capture cardiac arrhythmias and events from participants. The prescribed FDA-cleared device
        will serve as the ground truth (GT) for our analyses. The detected arrhythmias and events
        from our solution will be compared with the findings from the ground truth to obtain our
        system's detection rate. The goal is to achieve a detection rate of >80% to be deemed
        successful.
  The proposed research is to address the accessibility and affordability of technology to
        capture symptomatic and asymptomatic cardiac events via Long-Term Continuous
        Electrocardiogram Monitoring (LTCM), and to provide physicians with full access to their
        patients' recorded data in a timely manner. We adopt an FDA cleared single- lead OEM patch
        Holter made of flexible material to make long-term wearing more comfortable and more patient
        compliant. The patch transmits the recorded data to our cloud-based platform: ZBPro™, where
        our innovative technologies reside. Our proprietary AI algorithms with innovative human
        interaction tools, which were developed under the NSF SBIR Phase I (Award #: 2025951) Award
        analyze and interpret the recorded data to detect and annotate arrhythmia/cardiac events, and
        generates daily reports for physician review. The feasibility of our algorithms has been
        verified using ZBeats' proprietary ECG database based on the standard ANSI/AAMI EC57. Data
        collection and transmission has been verified in the office environment.
  
        Specific Aim 1: Study Setup: Setup the study REDCap instance with role-based access under
        SBU's REDCap system. Prepare data collection forms. Deliver the study devices to clinical
        sites. Provide training to clinical personnel regarding the study, procedure, informed
        consent and data collection. Project team assess the protocols and training are in place for
        the study.
  
        Specific Aim 2: Acceptability Evaluation: Identify and evaluate the device acceptability in
        up-to-7-day wearing. 60-75 participants will be enrolled during 6-7-month study period.
        Participants' enrollment, follow-up and closeout questionnaires regarding the acceptability
        will be conducted in-person or via telephone by the research associate in each clinical site.
        Success of Aim 2: the mean acceptability percentage of the close-out survey will be > 70%.
  
        Specific Aim 3: Arrhythmia Capture Evaluation: Evaluate devices' ability to detect cardiac
        arrhythmia and events, as well as the ECG signal quality. Physicians' questionnaire will be
        completed by the physicians from each clinical site after ZBeats' reports are reviewed and
        compare with reports generated by the prescription device as the ground truth. The quality of
        signals will be assessed by an independent cardiologist. Success of Aim 3: the physician's
        having a 7-day acceptance rate of > 80% and a detection sensitivity of > 80%.
  
        Specific Aim 4: Drafting the study protocol and business plan for Phase II: Conduct
        statistical analysis, sample size calculations, provide projections, start working on the
        protocol for Phase II study.
  
        Success of this project will resolve the feasibility concern of the proposed LTCM solution in
        clinical practice, enabling physicians with more proactive participation in early detection
        of cardiac arrhythmias and accurate risk stratification. Moreover, the proposed Phase I and
        Phase II studies will mitigate commercialization risk by showing clinical evidence to prove
        its substantial equivalence to the predicate device to receive FDA 510k cleared as well as
        Medicare's approval.
  
        This proposed observational study will utilize a multidisciplinary collaboration of ZBeats
        INC (ZBTS), Stony Brook University (SBU), and Lankenau Medical Center (LMC). The study will
        enroll patients undergoing ECG monitoring. Patients will be asked to wear the study monitor
        and be followed for up to 7 days while wearing their prescribed FDA cleared devices
        simultaneously. The study does not intend to use any data or information from the
        investigational solution to interfere, intervene or affect any clinical decisions made for
        the participants. The primary outcome measure will be the ability to capture cardiac
        arrhythmias and events from participants. The prescribed FDA-cleared device will serve as the
        ground truth (GT) for our analyses. The detected arrhythmias and events from our solution
        will be compared with the findings from the ground truth to obtain our system's detection
        rate. The goal is to achieve a detection rate of >80% to be deemed successful. The secondary
        outcome measures include: 1) assessing signal quality by conducting independent reviewer's
        questionnaire; and, 2) assessing user acceptability by obtaining participants' and
        physicians' questionnaire.
  observational model: Other
  time perspective: Prospective
  measure: Capturing cardiac arrhythmias and events
  time frame: 7 days after intervention
  description: The ability to capture cardiac arrhythmias and events from participants will be the primary outcome of this study. The prescribed FDA-cleared device will serve as the ground truth (GT) for our analyses. The detected arrhythmias and events from our solution will be compared with the findings from the ground truth to obtain our system's detection rate. The goal is to achieve a detection rate of >80% to be deemed successful.
  measure: Assessing signal quality
  time frame: 7 days after intervention
  description: Assessing signal quality by conducting independent reviewer's questionnaire. An average score >70% across all domains will define success.
  measure: Assessing user acceptability
  time frame: 7 days after intervention
  description: Assessing user acceptability by obtaining participants' and physicians' questionnaire. An average score >70% across all domains will define success.
  arm group label: Patients on ECG monitoring post-transcatheter aortic valve replacement (TAVR) or other cardiac event
  description: Patients at our clinical collaborators practices who have undergone TAVR or other cardiac event and who are placed on ECG monitoring will be placed on an FDA cleared cardiac monitor. We adopt an FDA cleared, reusable, single-lead OEM patch Holter made of flexible material to make long-term wearing more comfortable and more patient compliance.
  intervention type: Device
  intervention name: Cardiac Monitoring
  description: FDA cleared ECG monitoring device that will be used to obtain ECG recordings and capture cardiac arrhythmias/events from participants
  arm group label: Patients on ECG monitoring post-transcatheter aortic valve replacement (TAVR) or other cardiac event
  study pop: 
  sampling method: Non-Probability Sample
  criteria: 
  gender: All
  minimum age: 18 Years
  maximum age: N/A
  healthy volunteers: Accepts Healthy Volunteers
  last name: Puja Parikh, MD
  role: Principal Investigator
  affiliation: Stony Brook University
  last name: Bin Fang, PhD
  phone: 6312202463
  email: bin.fang@zbeats.co
  last name: Ashutosh Yaligar, MBA
  phone: 5182219417
  email: ashutosh.yaligar@zbeats.co
  responsible party type: Sponsor
  mesh term: Arrhythmias, Cardiac