<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/NCT01675063</url>
  </required_header>
  <id_info>
    <org_study_id>UM HUM 63973</org_study_id>
    <nct_id>NCT01675063</nct_id>
  </id_info>
  <brief_title>Minimally Invasive Cardiac Output Monitoring Device</brief_title>
  <official_title>Development of a Minimally Invasive Cardiac Output Monitoring Device for Critically Ill Patients</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Michigan</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Retia Medical</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Michigan</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The overall goal of this collaborative study is to advance the novel &quot;pulse contour analysis&quot;&#xD;
      to the point at which it can be incorporated into a real-time device. The specific objective&#xD;
      is to establish an auto-calibration algorithm that conveniently yields cardiac output (CO) in&#xD;
      units of liters-per-minute. To achieve this objective, the waveforms for analysis and&#xD;
      reference pulmonary artery catheter CO measurements will be recorded from critically ill&#xD;
      patients and then analyzed off-line at Retia Medical. Successful completion of this study may&#xD;
      ultimately help lead to improved outcomes of critically ill patients.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Completed</overall_status>
  <start_date>August 2012</start_date>
  <completion_date type="Actual">October 2015</completion_date>
  <primary_completion_date type="Actual">October 2015</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Other</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output</measure>
    <time_frame>8 hours post cardiac surgery</time_frame>
    <description>The primary outcome of this work is to establish a dataset that would enable the calculation of a predicted cardiac output using waveform analysis from multiple sensors. The primary outcome of this work is the number of subjects that successfully contributed data.</description>
  </primary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">77</enrollment>
  <condition>Cardiac Event</condition>
  <arm_group>
    <arm_group_label>Retia Non-Invasive Sensors</arm_group_label>
    <arm_group_type>Other</arm_group_type>
    <description>Sensors will be placed on the patient and connected to an amplifier that produces a waveform for 8 hours post cardiac surgery.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Retia Non-Invasive Sensors</intervention_name>
    <description>Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform.</description>
    <arm_group_label>Retia Non-Invasive Sensors</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  All adult patients admitted to the University of Michigan ICU following cardiac&#xD;
             surgery with both a pulmonary and radial artery catheter.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Adult patients with mechanical cardiac support including intra-aortic balloon pumps,&#xD;
             LVAD, or ECMO, and persistent ventricular arrhythmias.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>James M Blum, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Michigan</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of Michigan</name>
      <address>
        <city>Ann Arbor</city>
        <state>Michigan</state>
        <zip>48109</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>March 2017</verification_date>
  <study_first_submitted>August 27, 2012</study_first_submitted>
  <study_first_submitted_qc>August 28, 2012</study_first_submitted_qc>
  <study_first_posted type="Estimate">August 29, 2012</study_first_posted>
  <results_first_submitted>October 11, 2016</results_first_submitted>
  <results_first_submitted_qc>March 27, 2017</results_first_submitted_qc>
  <results_first_posted type="Actual">May 8, 2017</results_first_posted>
  <last_update_submitted>March 27, 2017</last_update_submitted>
  <last_update_submitted_qc>March 27, 2017</last_update_submitted_qc>
  <last_update_posted type="Actual">May 8, 2017</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Michigan</investigator_affiliation>
    <investigator_full_name>Dr. James M. Blum</investigator_full_name>
    <investigator_title>Assistant Professor Of Anesthesiology, Director of Critical Care Research</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Cardiovascular Diseases</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>

  <clinical_results>

    <participant_flow>
      <group_list>
        <group group_id="P1">
          <title>Retia Non-Invasive Sensors</title>
          <description>Sensors will be placed on the patient and connected to an amplifier that produces a waveform for 8 hours post cardiac surgery.&#xD;
Retia Non-Invasive Sensors: Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform.</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Overall Study</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="77"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="77"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="0"/>
              </participants_list>
            </milestone>
          </milestone_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <group_list>
        <group group_id="B1">
          <title>Retia Non-Invasive Sensors</title>
          <description>Sensors will be placed on the patient and connected to an amplifier that produces a waveform for 8 hours post cardiac surgery.&#xD;
Retia Non-Invasive Sensors: Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform.</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="77"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>&lt;=18 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Between 18 and 65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="28"/>
                  </measurement_list>
                </category>
                <category>
                  <title>&gt;=65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="49"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Age</title>
          <units>years</units>
          <param>Mean</param>
          <dispersion>Full Range</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="69" lower_limit="35" upper_limit="90"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Sex: Female, Male</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Female</title>
                  <measurement_list>
                    <measurement group_id="B1" value="31"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Male</title>
                  <measurement_list>
                    <measurement group_id="B1" value="46"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Region of Enrollment</title>
          <units>participants</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>United States</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="77"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output</title>
        <description>The primary outcome of this work is to establish a dataset that would enable the calculation of a predicted cardiac output using waveform analysis from multiple sensors. The primary outcome of this work is the number of subjects that successfully contributed data.</description>
        <time_frame>8 hours post cardiac surgery</time_frame>
        <population>patients had undergone routine cardiac surgery. some patients did not have PA catheters placed and subsequently data was not obtained on cardiac output.</population>
        <group_list>
          <group group_id="O1">
            <title>Retia Non-Invasive Sensors</title>
            <description>Sensors will be placed on the patient and connected to an amplifier that produces a waveform for 8 hours post cardiac surgery.&#xD;
Retia Non-Invasive Sensors: Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform.</description>
          </group>
        </group_list>
        <measure>
          <title>Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output</title>
          <description>The primary outcome of this work is to establish a dataset that would enable the calculation of a predicted cardiac output using waveform analysis from multiple sensors. The primary outcome of this work is the number of subjects that successfully contributed data.</description>
          <population>patients had undergone routine cardiac surgery. some patients did not have PA catheters placed and subsequently data was not obtained on cardiac output.</population>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="77"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>analyzable data obtained</title>
                  <measurement_list>
                    <measurement group_id="O1" value="75"/>
                  </measurement_list>
                </category>
                <category>
                  <title>data flawed and unable to analyze</title>
                  <measurement_list>
                    <measurement group_id="O1" value="2"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
    </outcome_list>

    <reported_events>
      <time_frame>2 years</time_frame>
      <group_list>
        <group group_id="E1">
          <title>Retia Non-Invasive Sensors</title>
          <description>Sensors will be placed on the patient and connected to an amplifier that produces a waveform for 8 hours post cardiac surgery.&#xD;
Retia Non-Invasive Sensors: Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform.</description>
        </group>
      </group_list>
      <serious_events>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="77"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>0</frequency_threshold>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="77"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>Principal Investigators are NOT employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>The PI is not involved with the ultimate analysis of the data which is to be used for proprietary algorithm development. The PI was engaged with his opinion on algorithm development and review of waveform data.</restrictive_agreement>
    </certain_agreements>
    <point_of_contact>
      <name_or_title>James Blum</name_or_title>
      <organization>Emory University</organization>
      <phone>404-778-3482</phone>
      <email>jmblum@emory.edu</email>
    </point_of_contact>
  </clinical_results>
</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/NCT01675063
org study id: UM HUM 63973
nct id: NCT01675063
lead sponsor: 
collaborator: 
has dmc: No
The overall goal of this collaborative study is to advance the novel "pulse contour analysis"
      to the point at which it can be incorporated into a real-time device. The specific objective
      is to establish an auto-calibration algorithm that conveniently yields cardiac output (CO) in
      units of liters-per-minute. To achieve this objective, the waveforms for analysis and
      reference pulmonary artery catheter CO measurements will be recorded from critically ill
      patients and then analyzed off-line at Retia Medical. Successful completion of this study may
      ultimately help lead to improved outcomes of critically ill patients.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Other
masking: None (Open Label)
measure: Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output
time frame: 8 hours post cardiac surgery
description: The primary outcome of this work is to establish a dataset that would enable the calculation of a predicted cardiac output using waveform analysis from multiple sensors. The primary outcome of this work is the number of subjects that successfully contributed data.
arm group label: Retia Non-Invasive Sensors
arm group type: Other
description: Sensors will be placed on the patient and connected to an amplifier that produces a waveform for 8 hours post cardiac surgery.
intervention type: Device
intervention name: Retia Non-Invasive Sensors
description: Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform.
arm group label: Retia Non-Invasive Sensors
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: James M Blum, MD
role: Principal Investigator
affiliation: University of Michigan
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: University of Michigan
investigator full name: Dr. James M. Blum
investigator title: Assistant Professor Of Anesthesiology, Director of Critical Care Research
mesh term: Cardiovascular Diseases
sharing ipd: No
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
point of contact: 