Automated Identification of Psychogenic Nonepileptic Seizures

NCT03013348 | Unknown

• 1 other identifier: NES-1.5-09.2016
• Study Type: observational
• Target: 104
• Locations: 0 countries
• Sites: N/A

Brief Summary

A retrospective validation study of a post-processing method intended to identify psychogenic nonepileptic seizures

Conditions

Convulsion, Non-Epileptic

Outcome Measures

Primary Outcomes (1)

• > 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.

  6 months

Study Arms (3)

Adults (22-99),

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.

Device: Brain Sentinel's sEMG Post-processing algorithm

Adolescents (13-21)

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.

Device: Brain Sentinel's sEMG Post-processing algorithm

Children (2-12)

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.

Device: Brain Sentinel's sEMG Post-processing algorithm

Interventions

Brain Sentinel's sEMG Post-processing algorithm DEVICE

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.

Adolescents (13-21); Adults (22-99),; Children (2-12)

Eligibility Criteria

• Age: 2 Years - 99 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Subjects previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit with at least one PNES recorded during that admission.

You may qualify if:

• Subject was previously admitted to the Medical University of South Carolina for inpatient vEEG monitoring in the MUSC Epilepsy Monitoring Unit and at least one PNES was recorded during that admission.
• Male or female between the ages of 2-99
• Can understand and sign written informed consent, or will have a parent or a legally authorized representative (LAR) who can do so, prior to the performance of any study assessments

Sponsors & Collaborators

• Brain Sentinel: lead

MeSH Terms

Conditions

Seizures

Condition Hierarchy (Ancestors)

Neurologic Manifestations; Nervous System Diseases; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Jonathan Halford, MD

  Medical University of South Carolina

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 4, 2017
• First Posted: January 6, 2017
• Study Start: January 1, 2017
• Primary Completion: May 21, 2019
• Study Completion: August 1, 2020
• Last Updated: December 19, 2019

Record last verified: 2019-12

Data Sharing

• IPD Sharing: Will not share