Huang Yanzhen, Wu Yu, Zhou Shaodan, Que Xianting, Jiang Ailing, Shi Danli, Lu Ting, Chen Yanlan, Lin Ziqun, Liu Chao, Wen Yishuang, Zhang Shuyi, Huang Wen
Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Guangxi, China.
University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Virol J. 2025 May 13;22(1):140. doi: 10.1186/s12985-025-02774-y.
Little research has been conducted on new-onset myasthenia gravis (MG) patients following the coronavirus disease 2019 (COVID-19) pandemic. COVID-19 surged in China on December 7th, 2022. This study aimed to explore the clinical characteristics of new-onset MG patients after COVID-19 and analyze factors affecting their disease improvement.
All new-onset MG patients before (December 1st, 2021 to December 7th, 2022) and after COVID-19 outbreak (December 8th, 2022 to November 30th, 2023) were included in this study. Data was collected through the electronic medical record system and follow-up. Multivariate logistic regression was used to identify independent predictors of clinical improvement in patients with new-onset MG.
359 new-onset MG patients (165 before COVID-19 outbreak and 194 after COVID-19 outbreak) were enrolled in this study. After COVID-19 outbreak, there was an increase in new-onset MG patients, with more cases occurring within the first three months. The rates of pulmonary inflammation (40.28%), COVID-19 vaccination (88.14%), and treatment with tacrolimus (15.98%) and MG duration (15 weeks, IQR: 5.75, 32) were higher, while rates of thymectomy (13.92%), baseline MG-ADL (3, IQR: 3, 6), and QMGS (7, IQR: 5,8) were lower compared to new-onset MG patients before COVID-19 outbreak. Multivariate logistic regression analysis showed that age at onset (OR 0.964, p < 0.001), baseline MG-ADL (OR 1.611, p < 0.001), and ocular MG (OR 0.401, p = 0.041) were independent predictors of clinical improvement in new-onset MG after the COVID-19 outbreak.
In this single-center cross-sectional study, new-onset MG patients following the COVID-19 outbreak showed altered seasonal onset patterns, milder disease severity, and higher OMG onset age. Age at onset is an independently negative predictor of improvement in new-onset MG patients after the COVID-19 outbreak. Whereas baseline MG-ADL is an independently positive predictor.
关于2019冠状病毒病（COVID-19）大流行后新发性重症肌无力（MG）患者的研究较少。2022年12月7日，COVID-19在中国激增。本研究旨在探讨COVID-19后新发性MG患者的临床特征，并分析影响其疾病改善的因素。
本研究纳入了COVID-19爆发前（2021年12月1日至2022年12月7日）和爆发后（2022年12月8日至2023年11月30日）的所有新发性MG患者。通过电子病历系统和随访收集数据。采用多因素逻辑回归分析确定新发性MG患者临床改善的独立预测因素。
本研究共纳入359例新发性MG患者（COVID-19爆发前165例，爆发后194例）。COVID-19爆发后，新发性MG患者数量增加，且更多病例发生在头三个月内。肺部炎症发生率（40.28%）、COVID-19疫苗接种率（88.14%）、他克莫司治疗率（15.98%）和MG病程（15周，四分位间距：5.75，32）较高，而胸腺切除术发生率（13.92%）、基线MG-ADL评分（3分，四分位间距：3，6）和QMGS评分（7分，四分位间距：5，8）低于COVID-19爆发前的新发性MG患者。多因素逻辑回归分析显示，发病年龄（OR 0.964，p＜0.001）、基线MG-ADL评分（OR 1.611，p＜0.001）和眼肌型MG（OR 0.401，p = 0.041）是COVID-19爆发后新发性MG患者临床改善的独立预测因素。
在这项单中心横断面研究中，COVID-19爆发后的新发性MG患者表现出季节性发病模式改变、疾病严重程度较轻和眼肌型MG发病年龄较高。发病年龄是COVID-19爆发后新发性MG患者改善的独立负性预测因素。而基线MG-ADL评分是独立的正性预测因素。
