<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/NCT03043703</url>
  </required_header>
  <id_info>
    <org_study_id>ES-RDIVal-01</org_study_id>
    <nct_id>NCT03043703</nct_id>
  </id_info>
  <brief_title>AirSense 10 AHI Validation Study</brief_title>
  <official_title>Accuracy of Detection and Reporting of Sleep-disordered Breathing Metrics Determined by the ResMed AirSense 10 in AirView</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>ResMed</agency>
      <agency_class>Industry</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>ResMed</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The AirSense 10 platform is able to detect respiratory events at night and report these data&#xD;
      via telemonitoring. The accuracy of the AirSense 10 will be compared with scoring with&#xD;
      polysomnography (PSG). 100 patients will be observed in a sleep facility under PSG and&#xD;
      AirSense treatment.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Sleep disordered breathing is commonly assessed by calculating an Apnea-Hypopnea-Index AHI&#xD;
      and a Hypopnea-Index HI to define how frequent breathing or breathing efforts stop during the&#xD;
      night. The severity of sleep apnea (SA) is determined by the number of occurring apneas and&#xD;
      hypopneas. The respiratory disturbance index (RDI) captures these events and is calculated&#xD;
      comprising an AHI but also RERAs via the flow signal. Polysomnography (PSG) is being used in&#xD;
      the sleep laboratory as the Gold standard method to document a patient's sleep behavior by&#xD;
      tracking air flow, respiratory effort, blood oxygen and electrocardiac as well as&#xD;
      electromyographic signals. This way a comprehensive sleep pattern analysis can be created and&#xD;
      different forms of SA can be detected. However, the method is laborious and cost-intensive,&#xD;
      so it could save time and costs to have events accurately scored by the device itself. Device&#xD;
      data become important when tracking a patient's sleep night by night and not only once.&#xD;
      Reliable sleep data can be a valuable tool for tailoring sleep therapy to specific patient's&#xD;
      needs. Accurate device data also build the foundation for analysis of large amounts of data,&#xD;
      which can help us understanding how sleep disorders develop.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Withdrawn</overall_status>
  <why_stopped>
    Study has no principal investigator at the moment.&#xD;
  </why_stopped>
  <start_date type="Anticipated">April 2019</start_date>
  <completion_date type="Anticipated">June 2020</completion_date>
  <primary_completion_date type="Anticipated">March 2020</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>
    <intervention_model_description>Cohort study</intervention_model_description>
    <primary_purpose>Diagnostic</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>To evaluate the diagnostic accuracy of the AirSense 10 Apnea-Hypopnea-Index (AHI) algorithm compared to polysomnography (PSG) scored AHI.</measure>
    <time_frame>1 night</time_frame>
    <description>Calculate accuracy of the device when scoring Apnoeas and Hypopneas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and Hypopneas (decrease of airflow by at least 30% for at least 10 seconds accompanied by a reduction of Oxygen Saturation of 4%) and calculate the apnea-hypopnea-index (AHI): (apneas + hypopneas)/hours of sleep.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>To evaluate the diagnostic accuracy of the AirSense 10 Apnea-Hypopnea-Index (AHI) detection compared to polysomnography (PSG) gold standard scored AHI for clinical relevant threshold values.</measure>
    <time_frame>1 night</time_frame>
    <description>For secondary endpoint different cut-off values of AHI will be used to determine the accuracy at clinical relevant thresholds. To calculate device AHI accuracy compared to PSG AHI, receiver-operator-curves will be created and sensitivity and specificity calculated based on an AHI cut-off of 5, 15 or 30.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>To evaluate the diagnostic accuracy of the AirSense 10 Obstructive Apnea-Index (OAI) detection compared to polysomnography (PSG) gold standard scored OAI.</measure>
    <time_frame>1 night</time_frame>
    <description>Calculate accuracy of the device when scoring obstructive apnoeas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and calculate the obstructive apnea-index (OAI): (apneas)/hours of sleep.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>To evaluate the diagnostic accuracy of the AirSense 10 Central Apnea-Index (CAI) detection compared to polysomnography (PSG) gold standard scored CAI.</measure>
    <time_frame>1 night</time_frame>
    <description>Calculate accuracy of the device when scoring central apnoeas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and calculate the central apnea-index (CAI): (apneas)/hours of sleep.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>To evaluate the diagnostic accuracy of the AirSense 10 Respiratory-Disturbance-Index (RDI) detection compared to polysomnography (PSG) gold standard scored RDI.</measure>
    <time_frame>1 night</time_frame>
    <description>Calculate accuracy of the device when scoring respiratory disturbances by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and hypopneas (at least 90% decrease of airflow for at least 10 seconds) with a 3%drop in Oxygen saturation from baseline Level, and RERAs (flow Limitation that does not Count as an hypopnea) and calculate the respiratory disturbance-index (RDI): (apneas + hypopneas + RERAs)/hours of sleep.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Evaluate the diagnostic accuracy of the AirSense 10 Respiratory Effort Related Arousals (RERA) detection compared to polysomnography (PSG) gold standard scored RERA.</measure>
    <time_frame>1 night</time_frame>
    <description>Calculate accuracy of the device when scoring RERAs by comparing to polysomnography scoring RERAs. Identify RERAs (flow Limitation that does not Count as an hypopnea) and calculate the RERA-Index: RERAs/hours of sleep.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>To evaluate the diagnostic accuracy of AirView AHI reporting compared to reporting via ResScan (SD card data)</measure>
    <time_frame>1 night</time_frame>
    <description>AirView is a cloud-based ResMed telemonitoring platform where sleep data can be transferred remotely, displayed and analysed. ResScan is an analysis and reporting software, where device data from the memory card is being uploaded.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>To evaluate the diagnostic accuracy of AirView RDI reporting compared to reporting via ResScan (SD card data).</measure>
    <time_frame>1 night</time_frame>
    <description>AirView is a cloud-based ResMed telemonitoring platform where sleep data can be transferred remotely, displayed and analysed. ResScan is an analysis and reporting software, where device data from the memory card is being uploaded.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Sensitivity, specificity and accuracy of the sleep state detection algorithm of the AirSense10 for Her</measure>
    <time_frame>1 night</time_frame>
    <description>Identify the sleep stage: Stage W (wakefulness), stage N1 (NREM1), stage N2 (NREM2), stage N3 (NREM3) and stage R (REM)</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Sensitivity, specificity and accuracy of sleep efficiency as derived from the sleep state detection algorithm of the AirSense10 for Her</measure>
    <time_frame>1 night</time_frame>
    <description>Calculate sleep efficiency by dividing minutes of sleep by minutes of time in bed</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">0</enrollment>
  <condition>Sleep Apnea</condition>
  <arm_group>
    <arm_group_label>AirSense 10 AutoSet for Her</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Treatment for 1 night with ResMed AirSense 10 AutoSet for Her. Intervention: Administration of PAP Treatment with suboptimal pressure for 1 night.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>AirSense 10 AutoSet for Her</intervention_name>
    <description>Positive airway pressure</description>
    <arm_group_label>AirSense 10 AutoSet for Her</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. Patients aged ≥18 years who are able to understand and follow the instructions of the&#xD;
             study personnel&#xD;
&#xD;
          2. Patients with an indication for PAP therapy or currently adherent to PAP therapy&#xD;
             (device usage ≥4 h/ night) for moderate to severe sleep apnoea and diagnostic AHI&#xD;
             ˃15/h and/or a residual CAI ˃5/h&#xD;
&#xD;
          3. Patients with currently titrated fixed CPAP pressure ≥8 cmH2O; or 95th percentile APAP&#xD;
             pressure ≥8 cmH2O; or ASV therapy with a 95th percentile IPAP of ≥8 cmH2O&#xD;
&#xD;
          4. Patients who are established PAP users (PAP use duration ≥6 weeks)&#xD;
&#xD;
          5. Dated and signed written informed consent&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Patients with moderate to severe obstructive airway disease and/or respiratory&#xD;
             insufficiency&#xD;
&#xD;
          2. Patients with heart failure in NYHA class III or IV, unstable hypertension,&#xD;
             paroxysmal/persistent atrial fibrillation, unstable angina pectoris, cardiac or&#xD;
             cerebral ischemic events within the last 6 months before screening&#xD;
&#xD;
          3. Patients with current primary or secondary insomnia&#xD;
&#xD;
          4. Patients who are pregnant or breastfeeding&#xD;
&#xD;
          5. Patients who are physically unable to comply with the protocol&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>99 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Volker Toepfer, Dr</last_name>
    <role>Principal Investigator</role>
    <affiliation>Lungenzentrum Ulm</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Schlaf- und Beatmungszentrum Blaubeuren</name>
      <address>
        <city>Blaubeuren</city>
        <state>Baden-Wuerttemberg</state>
        <zip>89143</zip>
        <country>Germany</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Ruhrlandklinik Essen</name>
      <address>
        <city>Essen</city>
        <state>Nordrhein-Westfalen</state>
        <zip>45239</zip>
        <country>Germany</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Germany</country>
  </location_countries>
  <reference>
    <citation>Pepin JL, Guillot M, Tamisier R, Levy P. The upper airway resistance syndrome. Respiration. 2012;83(6):559-66. doi: 10.1159/000335839. Epub 2012 Mar 1.</citation>
    <PMID>22377755</PMID>
  </reference>
  <reference>
    <citation>Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R, Parthasarathy S, Quan SF, Redline S, Strohl KP, Davidson Ward SL, Tangredi MM; American Academy of Sleep Medicine. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med. 2012 Oct 15;8(5):597-619. doi: 10.5664/jcsm.2172.</citation>
    <PMID>23066376</PMID>
  </reference>
  <verification_date>March 2019</verification_date>
  <study_first_submitted>February 2, 2017</study_first_submitted>
  <study_first_submitted_qc>February 2, 2017</study_first_submitted_qc>
  <study_first_posted type="Estimate">February 6, 2017</study_first_posted>
  <last_update_submitted>March 26, 2019</last_update_submitted>
  <last_update_submitted_qc>March 26, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">March 28, 2019</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>Sleep Apnea Syndromes</mesh_term>
  </condition_browse>
  <!-- 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/NCT03043703
org study id: ES-RDIVal-01
nct id: NCT03043703
lead sponsor: 
is fda regulated drug: No
is fda regulated device: No
The AirSense 10 platform is able to detect respiratory events at night and report these data
      via telemonitoring. The accuracy of the AirSense 10 will be compared with scoring with
      polysomnography (PSG). 100 patients will be observed in a sleep facility under PSG and
      AirSense treatment.
Sleep disordered breathing is commonly assessed by calculating an Apnea-Hypopnea-Index AHI
      and a Hypopnea-Index HI to define how frequent breathing or breathing efforts stop during the
      night. The severity of sleep apnea (SA) is determined by the number of occurring apneas and
      hypopneas. The respiratory disturbance index (RDI) captures these events and is calculated
      comprising an AHI but also RERAs via the flow signal. Polysomnography (PSG) is being used in
      the sleep laboratory as the Gold standard method to document a patient's sleep behavior by
      tracking air flow, respiratory effort, blood oxygen and electrocardiac as well as
      electromyographic signals. This way a comprehensive sleep pattern analysis can be created and
      different forms of SA can be detected. However, the method is laborious and cost-intensive,
      so it could save time and costs to have events accurately scored by the device itself. Device
      data become important when tracking a patient's sleep night by night and not only once.
      Reliable sleep data can be a valuable tool for tailoring sleep therapy to specific patient's
      needs. Accurate device data also build the foundation for analysis of large amounts of data,
      which can help us understanding how sleep disorders develop.
allocation: N/A
intervention model: Single Group Assignment
intervention model description: Cohort study
primary purpose: Diagnostic
masking: None (Open Label)
measure: To evaluate the diagnostic accuracy of the AirSense 10 Apnea-Hypopnea-Index (AHI) algorithm compared to polysomnography (PSG) scored AHI.
time frame: 1 night
description: Calculate accuracy of the device when scoring Apnoeas and Hypopneas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and Hypopneas (decrease of airflow by at least 30% for at least 10 seconds accompanied by a reduction of Oxygen Saturation of 4%) and calculate the apnea-hypopnea-index (AHI): (apneas + hypopneas)/hours of sleep.
measure: To evaluate the diagnostic accuracy of the AirSense 10 Apnea-Hypopnea-Index (AHI) detection compared to polysomnography (PSG) gold standard scored AHI for clinical relevant threshold values.
time frame: 1 night
description: For secondary endpoint different cut-off values of AHI will be used to determine the accuracy at clinical relevant thresholds. To calculate device AHI accuracy compared to PSG AHI, receiver-operator-curves will be created and sensitivity and specificity calculated based on an AHI cut-off of 5, 15 or 30.
measure: To evaluate the diagnostic accuracy of the AirSense 10 Obstructive Apnea-Index (OAI) detection compared to polysomnography (PSG) gold standard scored OAI.
time frame: 1 night
description: Calculate accuracy of the device when scoring obstructive apnoeas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and calculate the obstructive apnea-index (OAI): (apneas)/hours of sleep.
measure: To evaluate the diagnostic accuracy of the AirSense 10 Central Apnea-Index (CAI) detection compared to polysomnography (PSG) gold standard scored CAI.
time frame: 1 night
description: Calculate accuracy of the device when scoring central apnoeas by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and calculate the central apnea-index (CAI): (apneas)/hours of sleep.
measure: To evaluate the diagnostic accuracy of the AirSense 10 Respiratory-Disturbance-Index (RDI) detection compared to polysomnography (PSG) gold standard scored RDI.
time frame: 1 night
description: Calculate accuracy of the device when scoring respiratory disturbances by comparing to polysomnography scoring. Identify Apneas (at least 90% decrease of airflow for at least 10 seconds) and hypopneas (at least 90% decrease of airflow for at least 10 seconds) with a 3%drop in Oxygen saturation from baseline Level, and RERAs (flow Limitation that does not Count as an hypopnea) and calculate the respiratory disturbance-index (RDI): (apneas + hypopneas + RERAs)/hours of sleep.
measure: Evaluate the diagnostic accuracy of the AirSense 10 Respiratory Effort Related Arousals (RERA) detection compared to polysomnography (PSG) gold standard scored RERA.
time frame: 1 night
description: Calculate accuracy of the device when scoring RERAs by comparing to polysomnography scoring RERAs. Identify RERAs (flow Limitation that does not Count as an hypopnea) and calculate the RERA-Index: RERAs/hours of sleep.
measure: To evaluate the diagnostic accuracy of AirView AHI reporting compared to reporting via ResScan (SD card data)
time frame: 1 night
description: AirView is a cloud-based ResMed telemonitoring platform where sleep data can be transferred remotely, displayed and analysed. ResScan is an analysis and reporting software, where device data from the memory card is being uploaded.
measure: To evaluate the diagnostic accuracy of AirView RDI reporting compared to reporting via ResScan (SD card data).
time frame: 1 night
description: AirView is a cloud-based ResMed telemonitoring platform where sleep data can be transferred remotely, displayed and analysed. ResScan is an analysis and reporting software, where device data from the memory card is being uploaded.
measure: Sensitivity, specificity and accuracy of the sleep state detection algorithm of the AirSense10 for Her
time frame: 1 night
description: Identify the sleep stage: Stage W (wakefulness), stage N1 (NREM1), stage N2 (NREM2), stage N3 (NREM3) and stage R (REM)
measure: Sensitivity, specificity and accuracy of sleep efficiency as derived from the sleep state detection algorithm of the AirSense10 for Her
time frame: 1 night
description: Calculate sleep efficiency by dividing minutes of sleep by minutes of time in bed
arm group label: AirSense 10 AutoSet for Her
arm group type: Experimental
description: Treatment for 1 night with ResMed AirSense 10 AutoSet for Her. Intervention: Administration of PAP Treatment with suboptimal pressure for 1 night.
intervention type: Device
intervention name: AirSense 10 AutoSet for Her
description: Positive airway pressure
arm group label: AirSense 10 AutoSet for Her
criteria: 
gender: All
minimum age: 18 Years
maximum age: 99 Years
healthy volunteers: No
last name: Volker Toepfer, Dr
role: Principal Investigator
affiliation: Lungenzentrum Ulm
facility: 
facility: 
country: Germany
citation: Pepin JL, Guillot M, Tamisier R, Levy P. The upper airway resistance syndrome. Respiration. 2012;83(6):559-66. doi: 10.1159/000335839. Epub 2012 Mar 1.
PMID: 22377755
citation: Berry RB, Budhiraja R, Gottlieb DJ, Gozal D, Iber C, Kapur VK, Marcus CL, Mehra R, Parthasarathy S, Quan SF, Redline S, Strohl KP, Davidson Ward SL, Tangredi MM; American Academy of Sleep Medicine. Rules for scoring respiratory events in sleep: update of the 2007 AASM Manual for the Scoring of Sleep and Associated Events. Deliberations of the Sleep Apnea Definitions Task Force of the American Academy of Sleep Medicine. J Clin Sleep Med. 2012 Oct 15;8(5):597-619. doi: 10.5664/jcsm.2172.
PMID: 23066376
responsible party type: Sponsor
mesh term: Sleep Apnea Syndromes