Abstract：
OBJECTIVE: Early differentiation between Parkinson\'s disease (PD) and Multiple system atrophy (MSA), particularly the parkinsonian subtypes (MSA-P), is challenging due to similar clinical symptoms. We aimed to evaluate Sympathetic skin response (SSR) and Cutaneous silent period (CSP) parameters in patients with MSA-P and PD to identify possible biomarkers that could distinguish the two groups of patients in early stage.
METHODS: 22 individuals with early-stage MSA-P, 29 with early-stage PD, and 28 healthy controls were recruited from Guangdong Provincial People\'s Hospital. Demographic data was collected for all participants. Their SSR and CSP were evaluated using clinical electromyography equipment. Data were compared between different groups. The diagnostic accuracy of SSR and CSP parameters was calculated using the ROC curve. Logistic regression was used to produce an integration model to enhance diagnostic utility.
RESULTS: Foot amplitude, CSP end latency and duration distinguished MSA-P from PD with the area under the curve (AUC) 0.770, 0.806, and 0.776, respectively. Foot and hand SSR amplitude distinguished PD from HC with the AUC 0.871 and 0.768, respectively. Foot SSR amplitude, hand SSR amplitude, and CSP end latency distinguished MSA-P from HC with the AUC 0.964, 0.872, and 0.812, respectively. The combination of SSR and CSP parameters differentiation between MSA-P and PD, PD and HC with the AUC 0.829 and 0.879, respectively.
CONCLUSIONS: Analysis of SSR and CSP parameters showed excellent diagnostic accuracy in discriminating patients with early-stage MSA-P from HC and good diagnostic accuracy in discriminating patients with MSA-P from PD with early stages.
METHODS: 22 individuals with early-stage MSA-P, 29 with early-stage PD, and 28 healthy controls were recruited from Guangdong Provincial People\'s Hospital. Demographic data was collected for all participants. Their SSR and CSP were evaluated using clinical electromyography equipment. Data were compared between different groups. The diagnostic accuracy of SSR and CSP parameters was calculated using the ROC curve. Logistic regression was used to produce an integration model to enhance diagnostic utility.
RESULTS: Foot amplitude, CSP end latency and duration distinguished MSA-P from PD with the area under the curve (AUC) 0.770, 0.806, and 0.776, respectively. Foot and hand SSR amplitude distinguished PD from HC with the AUC 0.871 and 0.768, respectively. Foot SSR amplitude, hand SSR amplitude, and CSP end latency distinguished MSA-P from HC with the AUC 0.964, 0.872, and 0.812, respectively. The combination of SSR and CSP parameters differentiation between MSA-P and PD, PD and HC with the AUC 0.829 and 0.879, respectively.
CONCLUSIONS: Analysis of SSR and CSP parameters showed excellent diagnostic accuracy in discriminating patients with early-stage MSA-P from HC and good diagnostic accuracy in discriminating patients with MSA-P from PD with early stages.
摘要：
目的：帕金森病（PD）与多系统萎缩（MSA）的早期鉴别，特别是帕金森病亚型(MSA-P)，由于类似的临床症状，具有挑战性。我们旨在评估MSA-P和PD患者的交感神经皮肤反应（SSR）和皮肤沉默期（CSP）参数，以确定可能的生物标志物，可以在早期区分两组患者。
方法：22名早期MSA-P患者，29患有早期PD，并从广东省人民医院招募了28名健康对照。收集所有参与者的人口统计学数据。使用临床肌电图设备评估其SSR和CSP。比较不同组之间的数据。使用ROC曲线计算SSR和CSP参数的诊断准确性。使用Logistic回归产生整合模型以增强诊断效用。
结果：脚振幅，CSP结束潜伏期和持续时间将MSA-P与PD区分开，曲线下面积（AUC）分别为0.770、0.806和0.776。脚和手SSR振幅分别以AUC0.871和0.768区分PD和HC。脚SSR振幅,手部SSR振幅,和CSP结束延迟分别以AUC0.964、0.872和0.812区分MSA-P与HC。SSR和CSP参数的组合区分MSA-P和PD，PD和HC的AUC分别为0.829和0.879。
结论：SSR和CSP参数分析表明，在区分早期MSA-P患者和HC患者方面具有良好的诊断准确性，在区分早期MSA-P患者和PD患者方面具有良好的诊断准确性。
方法：22名早期MSA-P患者，29患有早期PD，并从广东省人民医院招募了28名健康对照。收集所有参与者的人口统计学数据。使用临床肌电图设备评估其SSR和CSP。比较不同组之间的数据。使用ROC曲线计算SSR和CSP参数的诊断准确性。使用Logistic回归产生整合模型以增强诊断效用。
结果：脚振幅，CSP结束潜伏期和持续时间将MSA-P与PD区分开，曲线下面积（AUC）分别为0.770、0.806和0.776。脚和手SSR振幅分别以AUC0.871和0.768区分PD和HC。脚SSR振幅,手部SSR振幅,和CSP结束延迟分别以AUC0.964、0.872和0.812区分MSA-P与HC。SSR和CSP参数的组合区分MSA-P和PD，PD和HC的AUC分别为0.829和0.879。
结论：SSR和CSP参数分析表明，在区分早期MSA-P患者和HC患者方面具有良好的诊断准确性，在区分早期MSA-P患者和PD患者方面具有良好的诊断准确性。
