Myasthenia Gravis Clinical Trial
Official title:
A Digital Health Trial That Assesses Participant-driven Data Collection Using Smartphone Modules to Characterize Myasthenia Gravis Symptoms and Develop an A.I. Model to Predict Flares
There are limited objective measurements of MG symptoms as well as a dearth of data at a granular level of MG (myasthenia gravis) symptoms and triggers occurring longitudinally. This study is designed to use the strengths of mobile smartphones which enable participant-driven real time capture of data manually and through augmented sensors such as video and audio, in order to better characterize MG symptoms and flares. The study aims to enroll approximately 200 participants for approximately 9 months until analyzable data is available from at least 100 participants. Participants will complete in-app surveys for 3 months with, audiovisual recording of symptoms. This will take approximately 35 minutes per week after the initial survey.
Using their smartphones, potential participants will download the doc.ai research mobile app. There will be a web pre-screening link where potential participants will self-screen to see if they meet the basic eligibility criteria for this study. The recruitment tool for this trial is developed for diversity, fairness, and inclusion. With the aim to ensure diversity in the demographics of the trial to better understand the health needs of different populations. So, while some interested potential participants do qualify, they may not be invited into the trial due to these diversity requirements. Patients with myasthenia gravis (MG) who meet the inclusion criteria will be invited to join this digital health trial. Participants will sign the e-consent and self-enroll into the study. Once their eligibility is confirmed by the study team (to ensure eligibility criteria and validity of participant i.e. eliminate robo sign-ins) they will be asked to take a selfie, provide documented proof of MG diagnosis, respond to a series of survey questions regarding their demographics, current health, medical history, and other MG related information. Enrolled participants will have a daily brief check-in, 2 weekly check-ins and a weekly check-in which will include an audiovisual check-in, and will maintain an audiovisual diary to keep track of their symptoms, connect data, record their voice (to detect vocal symptoms: weakness, nasality) and take videos of their face (to detect facial symptoms: ocular, mouth droop) on a daily to weekly basis through the various data collecting modules in the doc.ai research app for the duration of their study participation. doc.ai's digital health trial platform will be leveraged to collect this data. The study aims to enroll approximately 200 participants in approximately 9 months. It is expected that a minimum of 100 participants will be included in the final analysis as at any given time there will be a lag between potential participants expressing interest in the study, their eligibility being assessed by the PI, and participants completing all required study procedures. At the end of their participation, participants will be asked to complete a questionnaire. After the participant has completed their final survey, they will be able to connect to a link redeemable as an Amazon.com gift card worth $250. All participants will also receive an end-of-trial-summary of the data that they had collected during the study. No medical advice or direction will be given based on this study. In addition, in the final survey participants will be asked if they would be willing to complete a usability interview after their participation in this trial has ended. This subset of participants invited to be part of a follow-up usability interview will include those who complete all study required procedures and some who may not have completed all study required procedures, in order to assess usability experience of the app for the duration of their participation. Participants will be contacted at their end of their period of participation until a total of 10-15 participants successfully complete the usability interview. Participants who successfully complete the usability interview will receive a link for a $50 in Amazon.com gift card via the app. For this study the data and, audio and video recordings will be captured directly on the doc.ai research app and securely stored on a HIPAA compliant cloud provider (Google Cloud Platform). This data will be used to understand the patterns of symptoms and triggers in order to better characterize factors such as the length and timing of flares and any unique symptom patterns in order to create more objective measures of MG symptoms. Ultimately this data would be used to build a machine learning model that could predict MG symptom flares. Primary Objective: Use a collection of digital health modules on the smartphone to collect myasthenia gravis (MG) symptoms and triggers to better characterize symptom patterns and flares. Secondary Objective: Use the data collected to develop an A.I. model to detect and/or predict symptom flares. ;
Status | Clinical Trial | Phase | |
---|---|---|---|
Completed |
NCT05039190 -
Evaluate the Efficacy and Safety of HBM9161(HL161)Subcutaneous Injection in Patients With Generalized MG Patients
|
Phase 3 | |
Recruiting |
NCT04561557 -
Safety and Efficacy of CT103A Cells for Relapsed/Refractory Antibody-associated Inflammatory Diseases of the Nervous System
|
Early Phase 1 | |
Completed |
NCT01727193 -
The Efficacy and Safety of Leflunomide or Azathioprine Therapy in Myasthenia Gravis Patients After Expand Thymectomy
|
Phase 3 | |
Completed |
NCT00285350 -
Mycophenolate Mofetil in Myasthenia Gravis
|
Phase 3 | |
Recruiting |
NCT05890833 -
The Risk of Falls Index for Patients With Neuromuscular Disorders
|
||
Completed |
NCT05694234 -
Influences of Sugammadex on Postoperative Progress in Patients With Myasthenia Gravis Undergoing Video-assisted Thoracoscopic Thymectomy: Retrospective Study
|
||
Recruiting |
NCT05635266 -
Tissue Repository Providing Annotated Biospecimens for Approved Investigator-directed Biomedical Research Initiatives
|
||
Not yet recruiting |
NCT04965987 -
Oxaloacetate in Myasthenia Gravis
|
Phase 1 | |
Not yet recruiting |
NCT05095103 -
Immune Profiles in Myasthenia Gravis
|
||
Terminated |
NCT02102594 -
Therapy of Antibody-mediated Autoimmune Diseases by Bortezomib (TAVAB)
|
Phase 2 | |
Completed |
NCT02774239 -
A Pilot Trial To Assess The Feasibility And Efficacy Of SCIG In Patients With MG Exacerbation (SCIG-MG)
|
Phase 3 | |
Completed |
NCT02066519 -
Benefits and Tolerance of Exercise in Patients With Generalized and Stabilized Myasthenia Gravis
|
N/A | |
Completed |
NCT02118805 -
Innovative Measures of Speech and Swallowing Dysfunction in Neurological Disorders
|
||
Terminated |
NCT01828294 -
Subcutaneous Ig Maintenance Therapy for Myasthenia Gravis
|
Phase 1 | |
Terminated |
NCT00727194 -
Safety and Efficacy Study of Eculizumab in Patients With Refractory Generalized Myasthenia Gravis
|
Phase 2 | |
Recruiting |
NCT04837625 -
Study of Myasthenic Crisis in China
|
||
Not yet recruiting |
NCT01469858 -
Perception and Multisensory Integration in Neurological Patients Using fMRI
|
N/A | |
Completed |
NCT05408702 -
Exercise in Autoimmune Myasthenia Gravis and Myasthenic Syndromes
|
||
Completed |
NCT03205306 -
Myasthenia Gravis and Psyche
|
||
Recruiting |
NCT06106672 -
Evaluate the Safety, Tolerability, Pharmacodynamics and Efficacy of CNP-106 in Subjects With Myasthenia Gravis
|
Phase 1/Phase 2 |