Clinical trial NCT06743490: Capturing Key MG-symptoms Using Smartphone Recordings.
Official title: Capturing Key Symptoms Using Smartphone Recordings in Patients With Myasthenia Gravis (CAPTURE-MG)
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Myasthenia Gravis
Fatigue
Keywords: Myasthenia Gravis
Fatigue
Digital features
Machine Learning Algorithms
Dysarthria
Dysphonia
Proximal arm fatigue
Ptosis
Lead sponsor: Leiden University Medical Center
Sponsor class: OTHER
Collaborators: name: Huma
First posted: 2024-12-20
Enrollment: 225
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: We aim to include 150 patients with Myasthenia Gravis, recruited from the national Dutch-Belgia MG registry, the patient organisation 'Spierziekten Nederland' or identified by the clinical team of Leiden University Medical Center (LUMC).

Non-MG participants are preferentially sampled from friends and family of enrolled MG patients. The highest preference will be same-household family members, lowest preference will be non-household non-family members. This acts as both a natural source of control participants and a natural control for any environmental confounders. Furthermore, non-MG participants will be recruited separately by placing flyers in crowded areas in the LUMC.

Brief summary: This study will make use of a cross-sectional design of MG patients and non-MG participants to quantitatively assess key MG symptoms, and to explore the applicability of machine learning algorithms to their measurement.

Detailed description: Due to the cross-sectional design, participants will only have to visit Leiden University Medical Center (LUMC) once. For patients already treated in the LUMC, we will try to align this visit with a standard clinical appointment.

After inclusion, all baseline data, consisting of demographics, clinical history and a number of questionnaires (four for MG participants, three for non-MG participants), will be collected. The symptom-specific assessments are performed in a standard order, with the most fatiguing task (i.e. proximal arm fatigue static assessment) last. We estimate the visit will take a total of 60 minutes.

This study is considered to be low risk. Withholding pyridostigmine for a limited period is part of standard care of MG (before investigations or clinical assessments) and does not affect long term clinical outcome. MG participants will consent to withhold pyridostigmine for 12 hours prior to the study visit if they are on this treatment and restart it after the visit. As this is a non-interventional, observational study where only questionnaire-based and non-contact digital data are being collected, the only source of marginal risk relates to data protection and confidentiality, including arrangements for the transfer and storage of data. Given it would not be possible to deidentify the digital audio or video data while maintaining the requisite integrity for data analysis, we will seek explicit consent for the sharing of this information in this identifiable format.

Eligibility criteria: Inclusion Criteria:

1. Age ≥ 18 years
2. Ability to understand the requirements of the study and provide written informed consent.

Inclusion Criteria for MG participants only:

1. A clinical diagnosis of myasthenia gravis (ocular or generalized) with the typical fluctuating muscle weakness and at least one of the following:

   * a positive serologic test for AChR or MuSK antibodies;
   * an abnormal electrodiagnostic test: repetitive nerve stimulation (RNS) or single-fiber electromyography (SFEMG).
2. MGFA Clinical Classification of disease severity I-IV.
3. Subjects have at least one of the symptoms of interest (namely dysarthria, dysphonia, proximal arm fatigue and/or ptosis).

Inclusion Criteria for non-MG participants only

1. Subjects are not diagnosed with and have no clinical suspicion of MG.
2. Subjects do not have a medical history of any of the symptoms of interest (namely dysarthria, dysphonia, proximal arm fatigue and/or ptosis).

Exclusion Criteria:

1. Not willing to be audio-recorded for the study assessments.
2. Not willing to be video-recorded for the study assessments.
3. Subjects currently taking part in a clinical trial of an Investigational Medicinal Product.
4. Subjects who have used an immediate release pyridostigmine-based medication in the 12 hours prior to their participation and participants on prolonged release pyridostigmine.
5. Subjects have cognitive or physical limitations that, in the opinion of the investigator, limits the subject's ability to complete study procedures/

Exclusion Criteria for MG participants only:

1. Subjects with an upper-limb amputation or who are non-verbal.
2. Subjects with a diagnosed neurological disease resulting in muscle weakness, other than MG.

Exclusion Criteria for non-MG participants only:

1. Limitation of upper limb mobility or speech impairment of any cause.

Primary outcomes:
measure: Differentiating between MG-patients and non-MG participants using digital features of dysarhtria, dysphonia, proximal arm fatigue and ptosis.
timeFrame: Assessed at a single time point during outpatient visit
Secondary outcomes:
measure: Correlating digital features of dysarthria, dysphonia, proximal arm fatigue and ptosis in MG patients with disease severity as measured by the MGC score.
timeFrame: Assessed at a single time point during outpatient visit
measure: Correlating digital features of dysarthria, dysphonia, proximal arm fatigue and ptosis in MG patients with the impact of MG on daily activities as measured by the MG-ADL.
timeFrame: Assessed at a single time point during outpatient visit
measure: The performance of automated signal processing of speech recordings collected through smartphone microphone for detection of dysarthria and dysphonia compared to clinical assessment.
timeFrame: Assessed at a single time point during outpatient visit
measure: The performance of automated measurement of proximal arm-fatiguing exercises through computer vision techniques applied to smartphone camera recordings for detection of proximal arm muscle weakness and fatigability compared to clinical assessment.
timeFrame: Assessed at a single time point during outpatient visit
measure: The performance of automated measurement of ptosis-provoking exercises through computer vision techniques applied to smartphone camera recordings for detection of ptosis compared to clinical assessment.
timeFrame: Assessed at a single time point during outpatient visit
measure: Correlating digital features of dysarthria, dysphonia, proximal arm fatigue and ptosis in MG patients with their level of fatigue as measured by the CIS-fatigue subscale.
timeFrame: Assessed at a single time point during outpatient visit
Other outcomes:
Locations:
city: Leiden
country: Netherlands
facility: Leiden University Medical Center
state: South-Holland
city: Leiden
country: Netherlands
facility: Leiden University Medical Center
Study officials:
affiliation: Leiden University Medical Center
name: Martijn R. Tannemaat, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References: