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.
Primary Language | English |
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Subjects | Medical Education |
Journal Section | Original Articles |
Authors | |
Publication Date | December 29, 2023 |
Submission Date | October 21, 2023 |
Acceptance Date | December 8, 2023 |
Published in Issue | Year 2023 |