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/NCT06014593</url>
    </required_header>
    <id_info>
      <org_study_id>RECHMPL23_0003</org_study_id>
      <nct_id>NCT06014593</nct_id>
    </id_info>
    <brief_title>Heart Failure Diagnostic Performance of an Expirogram Analysis Algorithm Evaluating 4 Biomarkers</brief_title>
    <acronym>SenseIR-IC</acronym>
    <official_title>Evaluation of the Diagnostic Performance of an Algorithm for Analyzing Expirograms of 4 Biomarkers in Exhaled Air in Patients With Heart Failure</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>University Hospital, Montpellier</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Université Montpellier</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>University Hospital, Montpellier</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>
        Telemonitoring is a key clinical issue in heart failure (HF). Bedside measurement systems&#xD;
        using handheld devices provide &quot;digital biomarkers&quot; useful for remote monitoring. A recent&#xD;
        systematic review and meta-analysis showed that teleconsultations and telemonitoring at home&#xD;
        improved the prognosis of HF patients compared with usual care. Biomarkers contained in&#xD;
        exhaled air could constitute &quot;digital biomarkers&quot; in HF, as measurement is non-invasive, and&#xD;
        4 different species have shown their potential interest: NO, CO, acetone and isoprene. The&#xD;
        assessment of these species in the exhaled air to remains an issue in the perspective of&#xD;
        non-invasive biomarkers in HF. Indeed, it requires selective sensors with low limit of&#xD;
        detection. In addition, these sensors should be miniaturizable. Quartz-enhanced photoacoustic&#xD;
        spectroscopy (QEPAS) are sensors that are suitable in this context. Last, the measured&#xD;
        concentration should be informative and directly related to the HF. However, the&#xD;
        concentration each of these biomarkers is not homogeneous during the expiration as it&#xD;
        reflects the different lung compartments. While the end-expiratory concentration constitutes&#xD;
        a sample of the alveolar concentration (AC) that reflects the blood concentration (BC) of one&#xD;
        specie, the relationship between alveolar and blood concentrations is complex as exchanges&#xD;
        that take place within these different compartments. Thus, measuring the concentration of a&#xD;
        specie in exhaled air during a complete exhalation (or &quot;expirogram&quot;) depends not only on the&#xD;
        BC of the specie, but also on changes in lung function. Because both BC and changes in lung&#xD;
        function depend on the severity of the HF, obtaining a full expirogram each specie should&#xD;
        provide valid diagnosis information in HF. The mathematical modelization of real-time QEPAS&#xD;
        sensors based expirograms together with lung function parameters (volume, flow) and lung&#xD;
        compartment identification (capnography i.e. exhaled CO2 concentration) could provide valid&#xD;
        algorithms with a an acceptable diagnosis performance in HF.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        In the context of chronic diseases and heart failure (HF) in particular, telemedicine and&#xD;
        telemonitoring have emerged as major clinical challenges today. The development of&#xD;
        point-of-care measurement systems using hand-held devices provides &quot;digital biomarkers&quot; that&#xD;
        are a key element in remote monitoring.&#xD;
  &#xD;
        Biomarkers contained in exhaled air could constitute &quot;digital biomarkers&quot;, as the measurement&#xD;
        of molecules in exhaled air is non-invasive. Currently, 6 exhaled biomarkers are validated by&#xD;
        the US FDA and used in a clinical context. In heart failure, 4 different species have been&#xD;
        shown to be of potential diagnostic or prognostic interest: NO, CO, acetone and isoprene.&#xD;
        However, while the concentration of these species in alveolar air (CA) reflects their blood&#xD;
        concentration (Cs), the relationship is more complex, having to take into account the&#xD;
        different compartments of the bronchial tree and the exchanges that take place within these&#xD;
        different compartments. Thus, measuring the concentration of a species in exhaled air during&#xD;
        a complete exhalation (or &quot;expirogram&quot;) using a real-time measurement, turns out to be&#xD;
        dependent not only on the systemic concentration of the species, but also on changes in lung&#xD;
        function.Thus, obtaining an expirogram not only makes it possible to specify the measurement&#xD;
        of the endogenous source of the species, but also provides information on changes in&#xD;
        pulmonary function, directly induced by heart failure, and which have a well-recognized&#xD;
        prognostic value.&#xD;
  &#xD;
        → The combination of different candidate exhaled biomarkers in IC, during a real-time&#xD;
        measurement of forced expiration, using selective, sensitive and miniaturizable sensors would&#xD;
        provide diagnostic, prognostic and patient outcome information in heart failure.&#xD;
  &#xD;
        Quartz-enhanced photoacoustic spectroscopy (QEPAS) is a suitable method for remote monitoring&#xD;
        of heart failure patients. It enables the creation of sensors characterized by good&#xD;
        selectivity and low detection thresholds. What's more, real-time analysis is possible, and&#xD;
        the sensors are potentially miniaturizable. These sensors are therefore capable of providing&#xD;
        expirograms for different species (rather than simply measuring CA at the end of expiration).&#xD;
        Complex signals of this type can be analyzed using mathematical modeling and artificial&#xD;
        intelligence techniques such as &quot;deep neural networks&quot;. These mathematical modelling methods&#xD;
        have been used to model pulmonary, neurological or cardiac function parameters.&#xD;
  &#xD;
        As part of a translational research project in collaboration with Dr. A. Vicet (MCF- UM,&#xD;
        Institut d'Electronique et des Systèmes) and Prof. N. Molinari (CHRU Montpellier, Institut&#xD;
        Desbrest d'Épidémiologie et de Santé Publique), the research team is currently developing&#xD;
        sensors for various exhaled biomarkers using the QEPAS method, which have been coupled with&#xD;
        synchronous quantification of volumes, flows and lung compartments. These sensors are&#xD;
        currently undergoing analytical validation (in the laboratory). The first expirograms have&#xD;
        been obtained and modelled using a spline regression dimension reduction method.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">October 1, 2023</start_date>
    <completion_date type="Anticipated">October 1, 2026</completion_date>
    <primary_completion_date type="Anticipated">October 1, 2024</primary_completion_date>
    <phase>N/A</phase>
    <study_type>Interventional</study_type>
    <has_expanded_access>No</has_expanded_access>
    <study_design_info>
      <allocation>Non-Randomized</allocation>
      <intervention_model>Parallel Assignment</intervention_model>
      <intervention_model_description>The device will be tested to measure biomarkers in a group of 55 Heart Failure patients and 20 healthy subjects.</intervention_model_description>
      <primary_purpose>Other</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled CO</measure>
      <time_frame>Baseline</time_frame>
      <description>Pattern of exhaled CO, concentration during the full expiration (in ppmv)</description>
    </primary_outcome>
    <secondary_outcome>
      <measure>Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled NO</measure>
      <time_frame>Baseline</time_frame>
      <description>Patterns of exhaled NO concentration during the full expiration (in ppmv)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled acetone</measure>
      <time_frame>Baseline</time_frame>
      <description>Patterns of exhaled acetone concentration during the full expiration (in ppmv)</description>
    </secondary_outcome>
    <secondary_outcome>
      <measure>Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled isoprene</measure>
      <time_frame>Baseline</time_frame>
      <description>Patterns of exhaled isoprene concentration during the full expiration (in ppmv)</description>
    </secondary_outcome>
    <number_of_arms>2</number_of_arms>
    <enrollment type="Anticipated">75</enrollment>
    <condition>Heart Failure</condition>
    <arm_group>
      <arm_group_label>Heart failure patients</arm_group_label>
      <arm_group_type>Other</arm_group_type>
      <description>Stable or relapsing heart failure patients aged between 25 and 85, diagnosed by a cardiologist and requiring respiratory and cardiac investigations at the Montpellier University Hospital.</description>
    </arm_group>
    <arm_group>
      <arm_group_label>Healthy voluntary</arm_group_label>
      <arm_group_type>Other</arm_group_type>
      <description>Volunteers Aged 25 to 85 with no previous cardiorespiratory history or treatment.</description>
    </arm_group>
    <intervention>
      <intervention_type>Device</intervention_type>
      <intervention_name>expirogram</intervention_name>
      <description>Recovery of heart failure data (left ventricular ejection fraction LVEF on cardiac echography (in mL), VO²max during, maximal cardio-pulmonary exercise test, plethysmographic spirometry, carbon monoxide transfer, NT-ProBNP assay,), clinical examination and finally expirogram with the device measuring the 4 exhaled biomarkers (CO/NO/Acetone/Isoprene).</description>
      <arm_group_label>Healthy voluntary</arm_group_label>
      <arm_group_label>Heart failure patients</arm_group_label>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Inclusion Criteria:&#xD;
  &#xD;
            -  Age from 25 to 85,&#xD;
  &#xD;
            -  Stable or worsening heart failure, diagnosed by a cardiologist,&#xD;
  &#xD;
            -  Patients requiring respiratory function tests and cardiac explorations as part of a&#xD;
               work-up at Montpellier University Hospital (pre-cardiac transplant,&#xD;
               pre-rehabilitation, pre-surgery, etc....).&#xD;
  &#xD;
          Exclusion Criteria:&#xD;
  &#xD;
            -  Subject in a period of relative exclusion in relation to another protocol, or for whom&#xD;
               the maximum annual indemnity of €6000 has been reached.&#xD;
  &#xD;
            -  Adult protected by law (guardianship, curatorship or safeguard of justice)&#xD;
  &#xD;
            -  Subject participating in another interventional research protocol&#xD;
  &#xD;
            -  Subject not affiliated to a social security scheme or not benefiting from such a&#xD;
               scheme.&#xD;
  &#xD;
            -  Pregnant or breast-feeding woman, patient unable to give consent, protected adult,&#xD;
               vulnerable persons (art.L. 1121-6, L. 1121-7, L. 1211-8, L. 1211-9 of the french&#xD;
               legislation).&#xD;
  &#xD;
            -  Subject deprived of liberty by judicial or administrative decision&#xD;
  &#xD;
            -  Subject having refused to give consent&#xD;
  &#xD;
          Healthy Volunteers :&#xD;
  &#xD;
            -  Age from 25 to 85,&#xD;
  &#xD;
            -  Volunteers with no previous cardiorespiratory history or treatment.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>25 Years</minimum_age>
      <maximum_age>85 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Fares GOUZI, MD</last_name>
      <role>Study Director</role>
      <affiliation>CHU de Montpellier</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>fares GOUZI, MD</last_name>
      <phone>04 67 33 59 08</phone>
      <phone_ext>+33</phone_ext>
      <email>f-gouzi@chu-montpellier.fr</email>
    </overall_contact>
    <location>
      <facility>
        <name>CHU de Montpellier</name>
        <address>
          <city>Montpellier</city>
          <zip>34000</zip>
          <country>France</country>
        </address>
      </facility>
    </location>
    <location_countries>
      <country>France</country>
    </location_countries>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>August 11, 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>heart failure</keyword>
    <keyword>exhaled air biomarkers</keyword>
    <keyword>sensors</keyword>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Heart Failure</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </patient_data>
    <!-- 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/NCT06014593
  org study id: RECHMPL23_0003
  nct id: NCT06014593
  lead sponsor: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: No
  Telemonitoring is a key clinical issue in heart failure (HF). Bedside measurement systems
        using handheld devices provide "digital biomarkers" useful for remote monitoring. A recent
        systematic review and meta-analysis showed that teleconsultations and telemonitoring at home
        improved the prognosis of HF patients compared with usual care. Biomarkers contained in
        exhaled air could constitute "digital biomarkers" in HF, as measurement is non-invasive, and
        4 different species have shown their potential interest: NO, CO, acetone and isoprene. The
        assessment of these species in the exhaled air to remains an issue in the perspective of
        non-invasive biomarkers in HF. Indeed, it requires selective sensors with low limit of
        detection. In addition, these sensors should be miniaturizable. Quartz-enhanced photoacoustic
        spectroscopy (QEPAS) are sensors that are suitable in this context. Last, the measured
        concentration should be informative and directly related to the HF. However, the
        concentration each of these biomarkers is not homogeneous during the expiration as it
        reflects the different lung compartments. While the end-expiratory concentration constitutes
        a sample of the alveolar concentration (AC) that reflects the blood concentration (BC) of one
        specie, the relationship between alveolar and blood concentrations is complex as exchanges
        that take place within these different compartments. Thus, measuring the concentration of a
        specie in exhaled air during a complete exhalation (or "expirogram") depends not only on the
        BC of the specie, but also on changes in lung function. Because both BC and changes in lung
        function depend on the severity of the HF, obtaining a full expirogram each specie should
        provide valid diagnosis information in HF. The mathematical modelization of real-time QEPAS
        sensors based expirograms together with lung function parameters (volume, flow) and lung
        compartment identification (capnography i.e. exhaled CO2 concentration) could provide valid
        algorithms with a an acceptable diagnosis performance in HF.
  In the context of chronic diseases and heart failure (HF) in particular, telemedicine and
        telemonitoring have emerged as major clinical challenges today. The development of
        point-of-care measurement systems using hand-held devices provides "digital biomarkers" that
        are a key element in remote monitoring.
  
        Biomarkers contained in exhaled air could constitute "digital biomarkers", as the measurement
        of molecules in exhaled air is non-invasive. Currently, 6 exhaled biomarkers are validated by
        the US FDA and used in a clinical context. In heart failure, 4 different species have been
        shown to be of potential diagnostic or prognostic interest: NO, CO, acetone and isoprene.
        However, while the concentration of these species in alveolar air (CA) reflects their blood
        concentration (Cs), the relationship is more complex, having to take into account the
        different compartments of the bronchial tree and the exchanges that take place within these
        different compartments. Thus, measuring the concentration of a species in exhaled air during
        a complete exhalation (or "expirogram") using a real-time measurement, turns out to be
        dependent not only on the systemic concentration of the species, but also on changes in lung
        function.Thus, obtaining an expirogram not only makes it possible to specify the measurement
        of the endogenous source of the species, but also provides information on changes in
        pulmonary function, directly induced by heart failure, and which have a well-recognized
        prognostic value.
  
        → The combination of different candidate exhaled biomarkers in IC, during a real-time
        measurement of forced expiration, using selective, sensitive and miniaturizable sensors would
        provide diagnostic, prognostic and patient outcome information in heart failure.
  
        Quartz-enhanced photoacoustic spectroscopy (QEPAS) is a suitable method for remote monitoring
        of heart failure patients. It enables the creation of sensors characterized by good
        selectivity and low detection thresholds. What's more, real-time analysis is possible, and
        the sensors are potentially miniaturizable. These sensors are therefore capable of providing
        expirograms for different species (rather than simply measuring CA at the end of expiration).
        Complex signals of this type can be analyzed using mathematical modeling and artificial
        intelligence techniques such as "deep neural networks". These mathematical modelling methods
        have been used to model pulmonary, neurological or cardiac function parameters.
  
        As part of a translational research project in collaboration with Dr. A. Vicet (MCF- UM,
        Institut d'Electronique et des Systèmes) and Prof. N. Molinari (CHRU Montpellier, Institut
        Desbrest d'Épidémiologie et de Santé Publique), the research team is currently developing
        sensors for various exhaled biomarkers using the QEPAS method, which have been coupled with
        synchronous quantification of volumes, flows and lung compartments. These sensors are
        currently undergoing analytical validation (in the laboratory). The first expirograms have
        been obtained and modelled using a spline regression dimension reduction method.
  allocation: Non-Randomized
  intervention model: Parallel Assignment
  intervention model description: The device will be tested to measure biomarkers in a group of 55 Heart Failure patients and 20 healthy subjects.
  primary purpose: Other
  masking: None (Open Label)
  measure: Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled CO
  time frame: Baseline
  description: Pattern of exhaled CO, concentration during the full expiration (in ppmv)
  measure: Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled NO
  time frame: Baseline
  description: Patterns of exhaled NO concentration during the full expiration (in ppmv)
  measure: Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled acetone
  time frame: Baseline
  description: Patterns of exhaled acetone concentration during the full expiration (in ppmv)
  measure: Diagnostic performance (area under curve of ROC analysis) for the diagnosis of chronic heart failure of exhaled isoprene
  time frame: Baseline
  description: Patterns of exhaled isoprene concentration during the full expiration (in ppmv)
  arm group label: Heart failure patients
  arm group type: Other
  description: Stable or relapsing heart failure patients aged between 25 and 85, diagnosed by a cardiologist and requiring respiratory and cardiac investigations at the Montpellier University Hospital.
  arm group label: Healthy voluntary
  arm group type: Other
  description: Volunteers Aged 25 to 85 with no previous cardiorespiratory history or treatment.
  intervention type: Device
  intervention name: expirogram
  description: Recovery of heart failure data (left ventricular ejection fraction LVEF on cardiac echography (in mL), VO²max during, maximal cardio-pulmonary exercise test, plethysmographic spirometry, carbon monoxide transfer, NT-ProBNP assay,), clinical examination and finally expirogram with the device measuring the 4 exhaled biomarkers (CO/NO/Acetone/Isoprene).
  arm group label: Healthy voluntary
  arm group label: Heart failure patients
  criteria: 
  gender: All
  minimum age: 25 Years
  maximum age: 85 Years
  healthy volunteers: Accepts Healthy Volunteers
  last name: Fares GOUZI, MD
  role: Study Director
  affiliation: CHU de Montpellier
  last name: fares GOUZI, MD
  phone: 04 67 33 59 08
  phone ext: +33
  email: f-gouzi@chu-montpellier.fr
  facility: 
  country: France
  responsible party type: Sponsor
  mesh term: Heart Failure
  sharing ipd: No