Sanders Donald B, Massey Janice M
Neuromuscular Section, Department of Neurology, Box 3403, Duke University Medical Center, Durham, North Carolina, 27710, USA.
Muscle Nerve. 2017 Jul;56(1):45-50. doi: 10.1002/mus.25440. Epub 2017 Feb 15.
The objective of this study was to determine if single-fiber electromyography (SFEMG) jitter accurately reflects change in severity in myasthenia gravis (MG).
We reviewed jitter and outcome data from all MG patients in our clinic who had at least 2 jitter measurements in the extensor digitorum or frontalis muscle.
Change in all parameters of jitter measured with SFEMG electrodes predicted clinical change with acceptable accuracy. Absolute and percentage change in mean value of consecutive interval differences were equally accurate in predicting clinical change and were more accurate than change in the proportion of fiber pairs with blocking or normal jitter.
Jitter is a sensitive measure of severity in MG and has a potential role as a biomarker in clinical trials and the clinic. Absolute or percentage change in mean jitter is the best jitter parameter to follow. The accuracy of change in jitter measured with other electrodes has yet to be determined. Muscle Nerve 56: 45-50, 2017.
本研究的目的是确定单纤维肌电图（SFEMG）的颤抖是否能准确反映重症肌无力（MG）严重程度的变化。
我们回顾了诊所中所有MG患者的颤抖和结果数据，这些患者在指伸肌或额肌至少进行了2次颤抖测量。
用SFEMG电极测量的所有颤抖参数的变化以可接受的准确性预测了临床变化。连续间隔差异平均值的绝对变化和百分比变化在预测临床变化方面同样准确，并且比具有阻滞或正常颤抖的纤维对比例变化更准确。
颤抖是MG严重程度的敏感指标，在临床试验和临床中作为生物标志物具有潜在作用。平均颤抖的绝对或百分比变化是最佳的跟踪颤抖参数。用其他电极测量的颤抖变化的准确性尚未确定。《肌肉与神经》56: 45 - 50, 2017。
