Unveiling Myasthenia Gravis: A Comprehensive Analysis of Diagnostic Tools and Clinical Insights

Samet Öncel, Abdulkadir Tunç
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Abstract

Objective: This research offers a comprehensive analysis of Myasthenia Gravis (MG), uncovering the remarkable accuracy of spinal accessory, ulnar, and facial nerve repetitive nerve stimulation (RNS), along with the precision of single fiber electromyography (SF-EMG) in MG diagnosis. We also embark on an exploration of clinical features and autoantibody test results in generalized MG patients. Methods: In this prospective study, we welcomed 31 individuals definitively diagnosed with generalized MG into our quest. The categorization of patients was conducted in accordance with the criteria set by the Myasthenia Gravis Foundation of America (MGFA). We examined patients' trapezius, nasalis, and abductor digiti minimi (ADM) muscles using RNS. We meticulously recorded the presence of MG autoantibodies, clinical subtypes based on affected muscle groups, and SF-EMG jitter rates. Results: The mean age of the 31 patients of whom 19 (61.3%) were male, was 64 ± 13.9 years. Among them, 20 showed positivity in the Anti-AChR antibody test. In 28 patients, accounting for 90.3% of the study group, single fiber electromyography (EMG) displayed increased jitter. There were 4 (12.9%), 24 (77.4%) and 12 (38.7%) patients featuring a decremental response of exceeding 10% in ADM, trapezius and nasalis muscles, respectivelyOur investigation revealed notable findings, such as the absence of substantial correlations between decremental response rates and age, gender, duration of complaints, antibody test results, thymus abnormalities, affected muscle types, familial history, or increased jitter rates in SF-EMG (p>0.05). Conclusion: As our findings clearly show, we can confidently attest to the remarkable sensitivity of RNS in MG diagnosis when muscle selection is precise. A gem discovered on our study is the high sensitivity of the spinal accessory nerve, a revelation that should guide the course of routine RNS studies, particularly for those facing ocular-onset myasthenia.
揭开肌无力症的神秘面纱:诊断工具和临床见解的全面分析
研究目的本研究对重症肌无力(MG)进行了全面分析,揭示了脊髓附属神经、尺神经和面神经重复神经刺激(RNS)的显著准确性,以及单纤维肌电图(SF-EMG)在诊断重症肌无力中的精确性。我们还着手对全身型 MG 患者的临床特征和自身抗体检测结果进行探讨。 研究方法在这项前瞻性研究中,我们迎来了 31 名被明确诊断为全身型 MG 的患者。我们根据美国肌无力基金会(MGFA)制定的标准对患者进行了分类。我们使用 RNS 检查了患者的斜方肌、鼻肌和小腹肌 (ADM)。我们仔细记录了肌萎缩症自身抗体的存在情况、基于受影响肌肉群的临床亚型以及 SF-EMG 抖动率。 研究结果31 名患者中有 19 人(61.3%)为男性,平均年龄为 64 ± 13.9 岁。其中,20 人的抗 AChR 抗体检测呈阳性。28名患者(占研究组的90.3%)的单纤维肌电图(EMG)显示抖动增加。我们的调查发现了一些值得注意的结果,如反应减弱率与年龄、性别、病程、抗体检测结果、胸腺异常、受影响的肌肉类型、家族史或 SF-EMG 抖动率增加之间没有实质性关联(P>0.05)。 结论我们的研究结果清楚地表明,如果肌肉选择准确,我们可以自信地证明 RNS 在 MG 诊断中的显著灵敏度。我们在研究中发现的一个亮点是脊髓附属神经的高灵敏度,这一启示应指导常规 RNS 研究的进程,尤其是对于那些面临眼肌型肌无力的患者。
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