<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/NCT02188498</url>
  </required_header>
  <id_info>
    <org_study_id>Electrocardiography Study</org_study_id>
    <nct_id>NCT02188498</nct_id>
  </id_info>
  <brief_title>Electrocardiography Data Analysis in Sleep Disorders</brief_title>
  <acronym>Holter</acronym>
  <official_title>Electrocardiography Data Analysis in Sleep Disorders</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Weill Medical College of Cornell University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Weill Medical College of Cornell University</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The objective of this study is to determine if a non-invasive technique, using an innovative&#xD;
      analysis of electrocardiogram (ECG) data, would allow for detection of respiratory events&#xD;
      during sleep and discrimination between central and obstructive apnea. Obstructive Sleep&#xD;
      Apnea (OSA) is the most common respiratory disturbance seen during sleep, with an estimated&#xD;
      prevalence of 10 % in the population and is strongly associated with the development of&#xD;
      cardiovascular disease. In patients with underlying cardiac disease, particularly in heart&#xD;
      failure (HF), central respiratory events such as Cheyne-Stokes Respiration (CSR) are often&#xD;
      seen during sleep. The presence of CSR is also associated with increased cardiovascular&#xD;
      morbidity and mortality. Currently, the identification and classification of sleep related&#xD;
      respiratory disturbances is performed during over-night sleep studies (polysomnography),&#xD;
      which are labor-intensive, time-consuming, expensive and difficult for patients. Thus, the&#xD;
      development of alternative techniques to assist in the identification of those events in the&#xD;
      outpatient setting is of marked importance for widespread screening of sleep apnea.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      This study aims to use novel analyses of electrocardiogram data to detect the presence and&#xD;
      type of respiratory event observed in patients during sleep. Our specific aims include:&#xD;
      determining the accuracy of using a non-invasive electrocardiogram (ECG) to detect sleep&#xD;
      apnea and to distinguish between obstructive sleep apnea (OSA) and Cheyne-Stokes Respiration&#xD;
      (CSR). For this investigator-initiated study, data from approximately 400 consecutive&#xD;
      patients presenting to the Weill Cornell Center for Sleep Medicine for polysomnography will&#xD;
      be collected. A sample size of 45 subjects in each group will be needed to quantify mean&#xD;
      amplitude change in the ECG derived respiratory signal. Study procedures are outlined below.&#xD;
      Standard and novel, research measurements from the ECG will be correlated with findings from&#xD;
      polysomnography and used to assess the presence and severity of a variety of ECG-based&#xD;
      measures of cardiovascular disease, such as left ventricular hypertrophy and prior Q-wave&#xD;
      myocardial infarction. Subjects will also have to complete a Questionnaire prior to their ECG&#xD;
      at their visit.&#xD;
&#xD;
      Detailed procedures:&#xD;
&#xD;
        1. Subjects will be asked to complete a brief questionnaire (see attached). This&#xD;
           questionnaire will ask questions relating to subjects' sleep patterns, etc. Potential&#xD;
           risks include possible discomfort while completing the questionnaire.&#xD;
&#xD;
        2. Continuous 12-lead ECG recordings, using torso-located electrodes, will be obtained with&#xD;
           Mortara Instrument H12+ recorders. An MTA Agreement has been established for the use of&#xD;
           this equipment for the duration of this study. Electrocardiograms will be obtained in&#xD;
           standard clinical fashion using GE Medical Systems equipment. Patients will be asked to&#xD;
           lie in the supine position and 10 recording electrodes will be applied. With the patient&#xD;
           lying quietly, a 10 second digital ECG will be recorded and then downloaded via analog&#xD;
           modem to the MUSE ECG analysis and storage system at New York Presbyterian Hospital&#xD;
           where it will be stored on a dedicated site of our password protected MUSE server. ECG&#xD;
           information:12-lead ECGs will be downloaded from the MUSE system to a secure network&#xD;
           drive and then copied to the hard drive of a password protected computer where they will&#xD;
           be batch-analyzed using an ECG research analysis program, Magellan, provided by GE&#xD;
           Medical Systems. Magellan will generate a series of measurements from each ECG and will&#xD;
           then export these measurements to an Excel file which will be converted to SPSS files&#xD;
           for data analysis. Deidentified ECG data may be downloaded to the Electrocardiography&#xD;
           data center and transferred using a secure file transfer system, such as Cornell's file&#xD;
           transfer website, to an outside company (Mortara, Inc.) for further analysis as needed.&#xD;
&#xD;
        3. Standard polysomnography will be performed for 12 hours at approximately the patients&#xD;
           regular sleep time. Sleep data will be recorded in a digitized system and analyzed using&#xD;
           Grass Twin software ® (Middleton, WI) for the determination and classification of&#xD;
           respiratory events and other sleep related parameters. The Apnea-Hypopnea Index (AHI)&#xD;
           will be calculated by computing the average number of obstructive apneas plus&#xD;
           obstructive hypopneas per hour of sleep. Obstructive sleep apnea (OSA) is here defined&#xD;
           by an AHI &amp;#8805;5. Intermittent hypoxemia (IH) will be determined by the number of&#xD;
           periods &amp;#8805;6 sec with SaO2 drops &amp;#8805;4%. Cheyne-Stokes Respiration will be&#xD;
           determined by the typical crescendo-decrescendo pattern on the respiratory flow signal,&#xD;
           chest and thoracic impedance, using standard criteria. Total duration of CSR will be&#xD;
           calculated for the determination of the % of sleep time on CSR. Data regarding&#xD;
           percentage of sleep time at SaO2 &amp;#8804;90% (%TST&amp;lt;90) and lowest saturation level&#xD;
           (LowSaO2) will also be recorded.&#xD;
&#xD;
      Upon completion of data attainment some de-identified data will be remote analyzed.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date>September 2013</start_date>
  <completion_date type="Actual">December 2017</completion_date>
  <primary_completion_date type="Actual">November 2017</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Cross-Sectional</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Heart rate variability</measure>
    <time_frame>One night of sleep study</time_frame>
    <description>The variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Analysis of QRS morphology</measure>
    <time_frame>One night of sleep study</time_frame>
    <description>The variation in the QRS waves.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>electrocardiogram signal</measure>
    <time_frame>One night of sleep study</time_frame>
    <description>Variation and analysis in the ecg signal.</description>
  </secondary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">120</enrollment>
  <condition>Sleep Disorders</condition>
  <condition>Sleep Apnea</condition>
  <condition>Sleep Disordered Breathing</condition>
  <arm_group>
    <arm_group_label>Polysomnography with Holter monitoring</arm_group_label>
    <description>Patients will undergo resting electrocardiogram (ECG) test at the beginning of the night and be monitored by a Holter device for the duration of the sleep study.</description>
  </arm_group>
  <intervention>
    <intervention_type>Procedure</intervention_type>
    <intervention_name>Polysomnography</intervention_name>
    <description>Polysomnography, also called a sleep study, is a test used to diagnose sleep disorders. Polysomnography records your brain waves, the oxygen level in your blood, heart rate and breathing, as well as eye and leg movements during the study.</description>
    <arm_group_label>Polysomnography with Holter monitoring</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        patients undergoing overnight sleep studies&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Patients presenting to the WCMC Sleep Center for polysomnography&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  N/A&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>95 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Ana Krieger, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Weill Medical College of Cornell University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Weill Cornell Center for Sleep Medicine</name>
      <address>
        <city>New York</city>
        <state>New York</state>
        <zip>10065</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>January 2019</verification_date>
  <study_first_submitted>July 2, 2014</study_first_submitted>
  <study_first_submitted_qc>July 9, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">July 11, 2014</study_first_posted>
  <last_update_submitted>January 3, 2019</last_update_submitted>
  <last_update_submitted_qc>January 3, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">January 4, 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>
    <mesh_term>Sleep Wake Disorders</mesh_term>
    <mesh_term>Parasomnias</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/NCT02188498
org study id: Electrocardiography Study
nct id: NCT02188498
lead sponsor: 
has dmc: No
The objective of this study is to determine if a non-invasive technique, using an innovative
      analysis of electrocardiogram (ECG) data, would allow for detection of respiratory events
      during sleep and discrimination between central and obstructive apnea. Obstructive Sleep
      Apnea (OSA) is the most common respiratory disturbance seen during sleep, with an estimated
      prevalence of 10 % in the population and is strongly associated with the development of
      cardiovascular disease. In patients with underlying cardiac disease, particularly in heart
      failure (HF), central respiratory events such as Cheyne-Stokes Respiration (CSR) are often
      seen during sleep. The presence of CSR is also associated with increased cardiovascular
      morbidity and mortality. Currently, the identification and classification of sleep related
      respiratory disturbances is performed during over-night sleep studies (polysomnography),
      which are labor-intensive, time-consuming, expensive and difficult for patients. Thus, the
      development of alternative techniques to assist in the identification of those events in the
      outpatient setting is of marked importance for widespread screening of sleep apnea.
This study aims to use novel analyses of electrocardiogram data to detect the presence and
      type of respiratory event observed in patients during sleep. Our specific aims include:
      determining the accuracy of using a non-invasive electrocardiogram (ECG) to detect sleep
      apnea and to distinguish between obstructive sleep apnea (OSA) and Cheyne-Stokes Respiration
      (CSR). For this investigator-initiated study, data from approximately 400 consecutive
      patients presenting to the Weill Cornell Center for Sleep Medicine for polysomnography will
      be collected. A sample size of 45 subjects in each group will be needed to quantify mean
      amplitude change in the ECG derived respiratory signal. Study procedures are outlined below.
      Standard and novel, research measurements from the ECG will be correlated with findings from
      polysomnography and used to assess the presence and severity of a variety of ECG-based
      measures of cardiovascular disease, such as left ventricular hypertrophy and prior Q-wave
      myocardial infarction. Subjects will also have to complete a Questionnaire prior to their ECG
      at their visit.

      Detailed procedures:

        1. Subjects will be asked to complete a brief questionnaire (see attached). This
           questionnaire will ask questions relating to subjects' sleep patterns, etc. Potential
           risks include possible discomfort while completing the questionnaire.

        2. Continuous 12-lead ECG recordings, using torso-located electrodes, will be obtained with
           Mortara Instrument H12+ recorders. An MTA Agreement has been established for the use of
           this equipment for the duration of this study. Electrocardiograms will be obtained in
           standard clinical fashion using GE Medical Systems equipment. Patients will be asked to
           lie in the supine position and 10 recording electrodes will be applied. With the patient
           lying quietly, a 10 second digital ECG will be recorded and then downloaded via analog
           modem to the MUSE ECG analysis and storage system at New York Presbyterian Hospital
           where it will be stored on a dedicated site of our password protected MUSE server. ECG
           information:12-lead ECGs will be downloaded from the MUSE system to a secure network
           drive and then copied to the hard drive of a password protected computer where they will
           be batch-analyzed using an ECG research analysis program, Magellan, provided by GE
           Medical Systems. Magellan will generate a series of measurements from each ECG and will
           then export these measurements to an Excel file which will be converted to SPSS files
           for data analysis. Deidentified ECG data may be downloaded to the Electrocardiography
           data center and transferred using a secure file transfer system, such as Cornell's file
           transfer website, to an outside company (Mortara, Inc.) for further analysis as needed.

        3. Standard polysomnography will be performed for 12 hours at approximately the patients
           regular sleep time. Sleep data will be recorded in a digitized system and analyzed using
           Grass Twin software ® (Middleton, WI) for the determination and classification of
           respiratory events and other sleep related parameters. The Apnea-Hypopnea Index (AHI)
           will be calculated by computing the average number of obstructive apneas plus
           obstructive hypopneas per hour of sleep. Obstructive sleep apnea (OSA) is here defined
           by an AHI &#8805;5. Intermittent hypoxemia (IH) will be determined by the number of
           periods &#8805;6 sec with SaO2 drops &#8805;4%. Cheyne-Stokes Respiration will be
           determined by the typical crescendo-decrescendo pattern on the respiratory flow signal,
           chest and thoracic impedance, using standard criteria. Total duration of CSR will be
           calculated for the determination of the % of sleep time on CSR. Data regarding
           percentage of sleep time at SaO2 &#8804;90% (%TST&lt;90) and lowest saturation level
           (LowSaO2) will also be recorded.

      Upon completion of data attainment some de-identified data will be remote analyzed.
observational model: Cohort
time perspective: Cross-Sectional
measure: Heart rate variability
time frame: One night of sleep study
description: The variation in the time interval between heartbeats. It is measured by the variation in the beat-to-beat interval.
measure: Analysis of QRS morphology
time frame: One night of sleep study
description: The variation in the QRS waves.
measure: electrocardiogram signal
time frame: One night of sleep study
description: Variation and analysis in the ecg signal.
arm group label: Polysomnography with Holter monitoring
description: Patients will undergo resting electrocardiogram (ECG) test at the beginning of the night and be monitored by a Holter device for the duration of the sleep study.
intervention type: Procedure
intervention name: Polysomnography
description: Polysomnography, also called a sleep study, is a test used to diagnose sleep disorders. Polysomnography records your brain waves, the oxygen level in your blood, heart rate and breathing, as well as eye and leg movements during the study.
arm group label: Polysomnography with Holter monitoring
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: 95 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Ana Krieger, MD
role: Principal Investigator
affiliation: Weill Medical College of Cornell University
facility: 
country: United States
responsible party type: Sponsor
mesh term: Sleep Apnea Syndromes
mesh term: Sleep Wake Disorders
mesh term: Parasomnias
sharing ipd: No