Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Biomed Res Int. 2021 Mar 4;2021:5592472. doi: 10.1155/2021/5592472. eCollection 2021.
Myasthenia gravis (MG) is a chronic autoimmune disease of the nervous system, which is still incurable. In recent years, with the progress of immunosuppressive and supportive treatment, the therapeutic effect of MG in the acute stage is satisfactory, and the mortality rate has been greatly reduced. However, there is still no consensus on how to conduct long-term management of stable MG, such as guiding patients to identify relapses, practice exercise, return to work and school, etc. In the international consensus guidance for management of myasthenia gravis published by the Myasthenia Gravis Foundation of America (MGFA) in 2020, for the first time, "the role of physical training/exercise in MG" was identified as the topic of discussion. Finally, due to a lack of high-quality evidence on physical training/exercise in patients with MG, the topic was excluded after the literature review. Therefore, this paper reviewed the current status of MG rehabilitation research and the difficulties faced by stable MG patients in self-management. It is suggested that we should take advantage of artificial intelligence (AI) and leverage it to develop the data-driven decision support platforms for MG management which can be used for adverse event monitoring, disease education, chronic management, and a wide variety of data collection and analysis.
重症肌无力（MG）是一种慢性自身免疫性神经系统疾病，目前仍然无法治愈。近年来，随着免疫抑制和支持治疗的进展，MG 急性期的治疗效果令人满意，死亡率大大降低。然而，对于稳定期 MG 的长期管理，如指导患者识别复发、进行锻炼、重返工作和学校等，仍没有共识。2020 年，美国重症肌无力基金会（MGFA）在发布的重症肌无力管理国际共识指南中，首次将“体力训练/锻炼在 MG 中的作用”确定为讨论主题。最后，由于缺乏重症肌无力患者体力训练/锻炼的高质量证据，在文献回顾后，该主题被排除。因此，本文综述了 MG 康复研究的现状以及稳定期 MG 患者在自我管理中面临的困难。建议利用人工智能（AI）并借助其开发用于 MG 管理的数据驱动决策支持平台，可用于不良事件监测、疾病教育、慢性管理以及各种数据收集和分析。
