Construction of A Multimodal Digital Assessment Model for Myasthenia Gravis

Обзор

This research is a single-center, exploratory, observational study to be carried out in the outpatient or inpatient ward of the Neurology Department at Huashan Hospital, affiliated to Fudan University. The aim is to develop a digital assessment model for Myasthenia Gravis by gathering multimodal digital phenotypic data from MG patients. This includes physiological signals, facial videos, eye movements, speech, limb movements, various scales, and quality of life metrics.

Подробное описание

The goal is to define the multimodal digital phenotypes of myasthenia gravis patients, determine the specificities of their symptoms, and develop a digital evaluation model and remote assessment system that is objective, precise, and user-friendly. This will provide a scientific foundation and technical support for diagnosing, treating, and rehabilitating individuals with MG.

Key issues to be addressed include:

* Whether digital phenotyping can comprehensively represent the disease characteristics and severity gradations in MG. * The feasibility of using multimodal digital phenotypic modeling for the objective evaluation of MG. * The challenges and obstacles faced by the AI-enhanced medical model in clinical demonstration applications.

The study is focused on three main objectives:

1. Perform a descriptive analysis and comparison of phenotypic data across various subgroups to pinpoint key characteristics associated with MG disease grade and scale score. 2. Construct a digital evaluation model for MG patients using chosen features, validate the model with prospectively gathered data, and conduct a correlative analysis with the clinical functional scales to assess its effectiveness on predicting MG symptom grading and disease progression. 3. Develop a patient-centric remote evaluation system utilizing the refined MG digital evaluation model to facilitate its application in real-world clinical settings.

Первичные конечные точки

• Descriptive Analysis and Comparison of Digital Phenotypic Data across Subgroups [Срок оценки: At baseline (single study visit)]
• Correlation Between Digital Evaluation Model and Quantitative Myasthenia Gravis (QMG) Scale [Срок оценки: At baseline (single study visit)]

Вторичные конечные точки (2)

• Interclass Correlation Coefficient (ICC) of the Digital Outcome Assessment Model [Срок оценки: Baseline and Week 2]
• Prospectively validate the model effectiveness [Срок оценки: 1 year]

Критерии участия

Критерии включения

For Patients with MG

• Patients have a confirmed diagnosis of myasthenia gravis and be over 18 years old.
• Patients have the clinical classification of Myasthenia Gravis Foundation of America (MGFA) within I-IV, or be asymptomatic after treatment.
• Patients must sign the informed consent form and the privacy confidentiality agreement.

For Healthy Participants

• Age group matched with MG participants

Критерии исключения

For Patients with MG

• Patients are in the crisis stage of myasthenia gravis (MGFA class V) and unable to cooperate with scoring.
• Patients are with severe cardiopulmonary diseases and unable to cooperate with the scoring.
• Patients with any psychiatric disorder or cognitive dysfunction that, in the investigator's judgment, may interfere with their participation in the study.
• Patients with any other unspecified unstable medical condition.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

Китай · 1 центр

• Huashan Hospital, affiliated to Fudan University — Шанхай

Идентификаторы

NCT: NCT07146425 · KY2023-664

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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