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Multi-Modal Monitoring of Disease Symptoms in Myasthenia Gravis (BioDigit MG-02)

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BioSensics

Status

Not yet enrolling

Conditions

Myasthenia Gravis
Myasthenia Gravis, Generalized

Study type

Observational

Funder types

Other
Industry
NIH

Identifiers

NCT07224386
BioDigit MG-02
R44NS122672 (U.S. NIH Grant/Contract)

Details and patient eligibility

About

Evaluate the feasibility of using digital health technologies to monitor symptoms in myasthenia gravis (MG).

Study subjects will be screened and enrolled at Massachusetts General Brigham Hospital to participate in this 12 month observational study. Study subjects will be asked to wear multiple wearable sensors to monitor their physical activity and PPG during daily activities. Participants will also complete speech, video, and ePRO and eCOA digital assessments at home and during study visits.

The primary objective for this observational study is to measure the correlation of sensor-derived measures of physical activity to MG-specific ratings of MG-ADL, QMG, MGC, and Neuro-QoL Fatigue

Full description

MG is a chronic autoimmune neuromuscular disease characterized by fluctuating muscle weakness that interferes with activities of daily living. Ocular, facial, swallowing, neck, limb and breathing muscles can be affected. The prevalence of MG is estimated at approximately 60,000 patients in the United States. MG symptoms are currently assessed in person through a careful history and physical exam by a neuromuscular disease expert. This is time-consuming, costly, and poses challenges in a chronic disease with fluctuating symptoms, where patients may not demonstrate any abnormality at the time of in-clinic assessment. The principal means of measuring disease severity are specific scales such as the MGC, QMG and the MG Manual Muscle Testing (MMT) scales. Although valuable, these scales are subjective and require training to administer correctly. Additionally, they provide only snapshot of a patient's disease and do not adequately reflect the spectrum of fluctuating weakness, which is a hallmark of MG. Wearable sensors and digital health technologies could enable objective, sensitive, continuous assessment of physical activity as well as motor and ocular impairments in individuals with MG.

BioSensics LLC (Newton, MA) is a medical device company specializing in wearable sensors and digital health technology for healthcare. BioSensics LLC offers a wearable sensor system and digital health solution for long-term remote monitoring of motor performance during everyday life.

The first phase of this project (NCT06277830) was conducted by Dr. Amanda Guidon at MGB, recruiting 20 patients with generalized MG over the course of 5 months to test initial feasibility of BioDigit MG.

This is an analytic observational study following participants over the course of 12 months. Subjects with documented diagnosis of MG with MGFA severity classes IIa/b, IIIa/b or IVa/b will be screened and recruited to participate in this non--interventional study.

The objective of the study is to evaluate the feasibility of using wearable sensors and digital health technologies to measure motor and speech function, as well as developing measures of ocular and facial expression to monitor the progression of the disease for people with MG. To achieve these objectives, we will conduct an observational study to investigate the correlation between outcomes as measured by the PAMSys sensor and digital health technologies with the total score and sub-scores of MG-ADL, QMG, MGC, and Fatigue Short Form of the Neuro-QOL in individuals with different MGFA severity Classes (Class IIa/b, IIIa/b or IVa/b).

Enrollment

50 estimated patients

Sex

All

Ages

18 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Autoimmune MG with or without history of thymoma, MGFA severity Class IIa/b, IIIa/b or IVa/b at the screening visit

  • Diagnosed gMG through ONE of the following methods:

    • Positive acetylcholine receptor antibody (AChR Ab) test
    • Positive muscle specific kinase receptor antibody (MuSK Ab) test
    • Positive LRP4 antibody and abnormal neuromuscular transmission demonstrated by single-fiber electromyography (SFEMG) or repetitive nerve stimulation (RNS) OR has maintained a positive response to treatments such as AChE inhibitors, IVIG/PLEX, FcRn antagonists or C5 inhibitors
    • Abnormal neuromuscular transmission demonstrated by single-fiber electromyography (SFEMG) or repetitive nerve stimulation (RNS) OR has maintained a positive response to treatments such as AChE inhibitors, IVIG/PLEX, FcRn antagonists or C5 inhibitors.
  • Physically and cognitively able to provide informed consent and adhere to the protocol, as determined by the investigator's judgment

  • Ambulatory status defined as the ability to walk a distance of 10 meters independently, with or without the use of an assistive device

  • Male or female, between the ages of 18 years old and 80 years old

  • Speaks and reads English fluently

Exclusion criteria

  • Inability to engage in activities that are essential for independent living, such as dressing, bathing, toileting, or eating independently.
  • Neurological or orthopedic problems independent of myasthenia which significantly affect gait and ADLs in the investigator's judgement.
  • Any significant medical, laboratory, or psychiatric condition that, in the judgment of the investigators, would potentially interfere with the ability to participate in the study.
  • Residence in long-term care centers or institutions, nursing facilities, skilled nursing facilities, or recipients of hospice care, or incarceration.
  • MGFA severity class I or V (MG crisis)
  • Pregnant women.
  • Concurrent participation in an interventional clinical trial (observational studies, biomarker studies and registries are acceptable)

Trial design

50 participants in 1 patient group

Myasthenia Gravis
Description:
All participants meeting the study inclusion criteria will be assigned to this group to complete the study activities

Trial contacts and locations

1

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Central trial contact

Ana Enriquez; Ashkan Vaziri, PhD

Data sourced from clinicaltrials.gov

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