Wang Hui, Hu Binbin, Huang Juan, Chen Lin, Yuan Min, Tian Xingfu, Shi Ting, Zhao Jiahao, Huang Wei
Department of Neurology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Department of Neurology, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, China.
Front Neurol. 2023 Jun 14;14:1172320. doi: 10.3389/fneur.2023.1172320. eCollection 2023.
The study aimed to analyze the clinical features and gait characteristics of patients with Parkinson's disease (PD) who also suffer from fatigue and to develop a model that can help identify fatigue states in the early stages of PD.
A total of 81 PD patients have been enrolled for the Parkinson's Fatigue Scale (PFS-16) assessment and divided into two groups: patients with or without fatigue. Neuropsychological assessments of the two groups, including motor and non-motor symptoms, were collected. The patient's gait characteristics were collected using a wearable inertial sensor device.
PD patients who experienced fatigue had a more significant impairment of motor symptoms than those who did not, and the experience of fatigue became more pronounced as the disease progressed. Patients with fatigue had more significant mood disorders and sleep disturbances, which can lead to a poorer quality of life. PD patients with fatigue had shorter step lengths, lower velocity, and stride length and increased stride length variability. As for kinematic parameters, PD patients with fatigue had lower shank-forward swing max, trunk-max sagittal angular velocity, and lumbar-max coronal angular velocity than PD patients without fatigue. The binary logistic analysis found that Movement Disorder Society-Unified Parkinson's Disease Rating Scale-I (MDS-UPDRS-I) scores, Hamilton Depression Scale (HAMD) scores, and stride length variability independently predicted fatigue in PD patients. The area under the curve (AUC) of these selected factors in the receiver operating characteristic (ROC) analysis was 0.900. Moreover, HAMD might completely mediate the association between Hamilton Anxiety Scale (HAMA) scores and fatigue (indirect effect: β = 0.032, 95% confidence interval: 0.001-0.062), with a percentage of mediation of 55.46%.
Combining clinical characteristics and gait cycle parameters, including MDS-UPDRS-I scores, HAMD scores, and stride length variability, can identify PD patients with a high fatigue risk.
本研究旨在分析同时患有疲劳症的帕金森病（PD）患者的临床特征和步态特点，并建立一个有助于在PD早期识别疲劳状态的模型。
共纳入81例PD患者进行帕金森疲劳量表（PFS-16）评估，并分为两组：有疲劳症状的患者和无疲劳症状的患者。收集两组患者的神经心理学评估结果，包括运动和非运动症状。使用可穿戴惯性传感器设备收集患者的步态特征。
经历疲劳的PD患者比未经历疲劳的患者运动症状受损更显著，且随着疾病进展，疲劳体验愈发明显。有疲劳症状的患者有更显著的情绪障碍和睡眠障碍，这会导致生活质量更差。有疲劳症状的PD患者步长更短、速度更低、步幅更小且步幅变异性增加。至于运动学参数，有疲劳症状的PD患者比无疲劳症状的PD患者小腿前摆最大幅度、躯干最大矢状角速度和腰椎最大冠状角速度更低。二元逻辑分析发现，运动障碍协会统一帕金森病评定量表第一部分（MDS-UPDRS-I）评分、汉密尔顿抑郁量表（HAMD）评分和步幅变异性独立预测PD患者的疲劳。在接受者操作特征（ROC）分析中，这些选定因素的曲线下面积（AUC）为0.900。此外，HAMD可能完全介导汉密尔顿焦虑量表（HAMA）评分与疲劳之间的关联（间接效应：β = 0.032，95%置信区间：0.001 - 0.062），中介百分比为55.46%。
结合临床特征和步态周期参数，包括MDS-UPDRS-I评分、HAMD评分和步幅变异性，可以识别出疲劳风险高的PD患者。
