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ME&MG is a standalone software (digital solution) running on patients smartphones, connected to a web portal for physicians. It is intended to be used as an unsupervised digital self-assessment tool for the monitoring of disabilities in patients living with MG.
ME&MG contains digital active tests for the assessment of ptosis, breathing, dysarthria, upper- and lower-limb (arms and legs) weakness, treatment follow-up, and validated e-questionnaires related to daily activities, pain, fatigue, sleep, and depression disorders.
The objectives of this study are to validate the accuracy, reliability and reproducibility of the unsupervised at-home self-assessment of symptoms on the patient's smartphone with ME&MG versus the standard in-clinic testing, as well as to evaluate the safety of the solution, its usability and satisfaction.
Myasthenia gravis (MG) is an autoimmune neuromuscular disease characterised by fatigable muscle weakness due to autoantibodies targeting components of the neuromuscular junction.
Deficits are measured using validated clinical scales such as the Quantitative Myasthenia Gravis score (QMG) QMG, Myasthenia Gravis Composite Score (MCS), Myasthenia Gravis Activities of Daily Living score (MG-ADL), etc., Unfortunately, this type of assessment might require expensive material, time, and personnel training, which make MG assessment difficult for clinicians in routine care.
Research on the matter has highlighted the importance of Patient-Reported Outcomes (PROs), composite measures of disease severity and quality-of-life measurements. This has led to the development of a number of tools for the self-assessment of PROs with validated questionnaires. However, there is no tool that overcomes the constraints of standard tests such as the QMG while allowing for the collection of objective data and PROs between visits.
ME&MG is a standalone software (digital solution) running on patients smartphones, connected to a web portal for physicians. It is intended to be used as an unsupervised digital self-assessment tool for the monitoring of disabilities in patients living with MG.
ME&MG contains digital active tests for the assessment of ptosis, breathing, dysarthria, upper- and lower-limb (arms and legs) weakness, treatment follow-up, and validated e-questionnaires related to daily activities, pain, fatigue, sleep, and depression disorders.
The objectives of this study are to validate the accuracy, reliability and reproducibility of the unsupervised at-home self-assessment of symptoms on the patient's smartphone with ME&MG versus the standard in-clinic testing, as well as to evaluate the safety of the solution, its usability and satisfaction.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| MG patients | Experimental | MG patients will perform 3 in-clinic visits and use the ME&MG app at-home during 12 months |
|
| Healthy volunteers | Other | Healthy volunteers will perform one in-clinic visit and will use the app at-home once |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| ME&MG mobile application | Device | ME&MG is a standalone software (digital solution) running on patients smartphones, connected to a web portal for physicians. It is intended to be used as an unsupervised digital self-assessment tool for the monitoring of disabilities in patients living with MG. |
| Measure | Description | Time Frame |
|---|---|---|
| To demonstrate that ME&MG tests results performed at-home, under unsupervised condition, are correlated to standard tests results performed in-clinic, under supervised conditions | Pearson correlation coefficient will be used to assess the relationship between digital tests versus standard tests | baseline |
| Measure | Description | Time Frame |
|---|---|---|
| To compare results between in-clinic digital tests and in-clinic standard tests, test to test | pearson correlation coefficient between digital tests and standard tests | baseline |
| To assess reproducibility between in-clinic digital tests and at-home digital tests |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Pr Laforet | Contact | +33147107752 | pascal.laforet@aphp.fr |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Colorado Denver | Recruiting | Aurora | Colorado | 80204 | United States |
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|
intraclass correlation coefficient |
| baseline, day 1, day 89, day 90 |
| To assess test-retest reliability of at-home digital tests | intraclass correlation coefficient mean k raters (ICCk; k=day) | Day1, Day 2, Day 3, Day 87, Day 88, Day 89 |
| To compare results obtained with the at-home ME&MG composite score and the in-clinic standard QMG composite score | Pearson correlation coefficient between digital composite score and QMG score | baseline, day 1 |
| To assess adverse events related to the use of the mobile application | Descriptive analysis of adverse events (AEs) related to the use of the application | through study completion, an average of 1 year |
| To assess satisfaction and user experience with the smartphone application | descriptive analysis of questionnaires resulsts | through study completion, an average of 1 year |
| To assess correlation of the at-home ME&MG composite score with the Myasthenia Gravis Activities of Daily Living (MG-ADL) score | Pearson's correlation coefficient between ME&MG composite score and MG-ADL scores | baseline, day 90, day 365 |
| to assess daily activites | Myasthenia Gravis Activities of Daily Living (MG-ADL) | 12 months |
| to assess depression | Patient Health Questionnaire-8 (PHQ8) | 12 months |
| to assess pain | pain likert scale | 12 months |
| to assess insomnia | Insomnia Severity Index | 12 months |
| To assess at-home compliance to the ME&MG smartphone application | descriptive analysis of adherence data | through study completion, an average of 1 year |
| To assess quality of life | 36-Item Short Form Survey (SF-36) | Baseline, day 90, Day 365 |
| University of Florida Health | Recruiting | Jacksonville | Florida | 32209 | United States |
|
| HealthParterns Institute | Completed | Bloomington | Indiana | 47401 | United States |
| Indiana University Health | Recruiting | Indianapolis | Indiana | 46123 | United States |
|
| University of Kentucky | Recruiting | Lexington | Kentucky | 40536 | United States |
|
| Neurological Associates of Long Island, P.C. | Recruiting | Lake Success | New York | 11042 | United States |
|
| Duke University | Recruiting | Durham | North Carolina | 27708 | United States |
|
| OHSU | Recruiting | Portland | Oregon | 97239 | United States |
|
| Thomas Jefferson University | Recruiting | Philadelphia | Pennsylvania | 19144 | United States |
|
| The University of Tennessee Medical Center | Not yet recruiting | Knoxville | Tennessee | 37920 | United States |
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| Vanderbilt Health | Recruiting | Nashville | Tennessee | 37232 | United States |
|
| Hôpital Raymond Poincaré | Recruiting | Garches | 92380 | France |
|
| CHU Grenoble | Not yet recruiting | Grenoble | France |
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| Hôpital Salengro | Recruiting | Lille | France |
|
| CHRU Nancy | Recruiting | Nancy | 54035 | France |
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| CHU Nantes | Recruiting | Nantes | France |
|
| Pitié-Salpêtrière | Recruiting | Paris | 75013 | France |
|
| CHU de Strasbourg - Hôpital de Hautepierre | Completed | Strasbourg | 67200 | France |
| CHU Toulouse | Recruiting | Toulouse | France |
|
| ID | Term |
|---|---|
| D009157 | Myasthenia Gravis |
| ID | Term |
|---|---|
| D020361 | Paraneoplastic Syndromes, Nervous System |
| D009423 | Nervous System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D010257 | Paraneoplastic Syndromes |
| D020274 | Autoimmune Diseases of the Nervous System |
| D009422 | Nervous System Diseases |
| D019636 | Neurodegenerative Diseases |
| D020511 | Neuromuscular Junction Diseases |
| D009468 | Neuromuscular Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
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