<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/NCT03013348</url>
  </required_header>
  <id_info>
    <org_study_id>NES-1.5-09.2016</org_study_id>
    <nct_id>NCT03013348</nct_id>
  </id_info>
  <brief_title>Automated Identification of Psychogenic Nonepileptic Seizures</brief_title>
  <official_title>Automated Identification of Psychogenic Nonepileptic Seizures</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Brain Sentinel</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Brain Sentinel</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      A retrospective validation study of a post-processing method intended to identify psychogenic&#xD;
      nonepileptic seizures&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      This is a validation study of a post-processing method intended to identify psychogenic&#xD;
      nonepileptic seizures by analysis of surface electromyographic (sEMG) artifact previously&#xD;
      recorded during routine video-electroencephalographic (vEEG) monitoring&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Active, not recruiting</last_known_status>
  <start_date type="Actual">January 2017</start_date>
  <completion_date type="Anticipated">August 2020</completion_date>
  <primary_completion_date type="Actual">May 21, 2019</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Only</observational_model>
    <time_perspective>Retrospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>&gt; 70% sensitivity of a post processing method for classification of psychogenic nonepileptic seizures in sEMG artifact captured during vEEG recordings as compared to vEEG interpretation by a panel of three independent Neurologists.</measure>
    <time_frame>6 months</time_frame>
  </primary_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Actual">104</enrollment>
  <condition>Convulsion, Non-Epileptic</condition>
  <arm_group>
    <arm_group_label>Adults (22-99),</arm_group_label>
    <description>Male or female subject between the ages of 22-99, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Adolescents (13-21)</arm_group_label>
    <description>Male or female subject between the ages of 13-21, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Children (2-12)</arm_group_label>
    <description>Male or female subject between the ages of 2-12, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>Brain Sentinel's sEMG Post-processing algorithm</intervention_name>
    <description>Brain Sentinel has developed a post processing method that identifies sEMG signals (recorded from the biceps brachii or as muscle artifact in electroencephalography [EEG] recordings) that are pathognomonic for PNES activity.</description>
    <arm_group_label>Adolescents (13-21)</arm_group_label>
    <arm_group_label>Adults (22-99),</arm_group_label>
    <arm_group_label>Children (2-12)</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Subjects previously admitted to the Medical University of South Carolina for inpatient vEEG&#xD;
        monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES recorded during that&#xD;
        admission.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
        A subject will be eligible for inclusion in this study if the following criteria apply.&#xD;
&#xD;
          -  Subject was previously admitted to the Medical University of South Carolina for&#xD;
             inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit and at least one PNES&#xD;
             was recorded during that admission.&#xD;
&#xD;
          -  Male or female between the ages of 2-99&#xD;
&#xD;
          -  Can understand and sign written informed consent, or will have a parent or a legally&#xD;
             authorized representative (LAR) who can do so, prior to the performance of any study&#xD;
             assessments&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  No exclusion criteria have been established for this study.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>2 Years</minimum_age>
    <maximum_age>99 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Jonathan Halford, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Medical University of South Carolina</affiliation>
  </overall_official>
  <verification_date>December 2019</verification_date>
  <study_first_submitted>January 4, 2017</study_first_submitted>
  <study_first_submitted_qc>January 5, 2017</study_first_submitted_qc>
  <study_first_posted type="Estimate">January 6, 2017</study_first_posted>
  <last_update_submitted>December 18, 2019</last_update_submitted>
  <last_update_submitted_qc>December 18, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">December 19, 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>Seizures</mesh_term>
    <mesh_term>Psychogenic Nonepileptic Seizures</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/NCT03013348
org study id: NES-1.5-09.2016
nct id: NCT03013348
lead sponsor: 
has dmc: No
A retrospective validation study of a post-processing method intended to identify psychogenic
      nonepileptic seizures
This is a validation study of a post-processing method intended to identify psychogenic
      nonepileptic seizures by analysis of surface electromyographic (sEMG) artifact previously
      recorded during routine video-electroencephalographic (vEEG) monitoring
observational model: Case-Only
time perspective: Retrospective
measure: > 70% sensitivity of a post processing method for classification of psychogenic nonepileptic seizures in sEMG artifact captured during vEEG recordings as compared to vEEG interpretation by a panel of three independent Neurologists.
time frame: 6 months
arm group label: Adults (22-99),
description: Male or female subject between the ages of 22-99, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.
arm group label: Adolescents (13-21)
description: Male or female subject between the ages of 13-21, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.
arm group label: Children (2-12)
description: Male or female subject between the ages of 2-12, previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES was recorded during that admission. Validation of Brain Sentinel's sEMG Post-processing algorithm will involve prospective evaluation of at least 30 PNES events in this group.
intervention type: Device
intervention name: Brain Sentinel's sEMG Post-processing algorithm
description: Brain Sentinel has developed a post processing method that identifies sEMG signals (recorded from the biceps brachii or as muscle artifact in electroencephalography [EEG] recordings) that are pathognomonic for PNES activity.
arm group label: Adolescents (13-21)
arm group label: Adults (22-99),
arm group label: Children (2-12)
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 2 Years
maximum age: 99 Years
healthy volunteers: No
last name: Jonathan Halford, MD
role: Principal Investigator
affiliation: Medical University of South Carolina
responsible party type: Sponsor
mesh term: Seizures
mesh term: Psychogenic Nonepileptic Seizures
sharing ipd: No