Noyce Alastair J, Schrag Anette, Masters Joseph M, Bestwick Jonathan P, Giovannoni Gavin, Lees Andrew J
Department of Molecular Neuroscience, Reta Lila Weston Institute, UCL Institute of Neurology, London, UK.
Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
J Neurol Neurosurg Psychiatry. 2017 Mar;88(3):212-217. doi: 10.1136/jnnp-2016-314524. Epub 2016 Dec 16.
The PREDICT-PD study aims to identify increased risk of Parkinson''s disease (PD) using online assessments of previously identified risk and early features of PD and an evidence-based scoring algorithm. We sought to determine whether higher risk participants (defined as those above the 15th centile of risk estimates) were more likely to have mild parkinsonian signs compared with lower risk participants.
Video recordings of neurological examinations, including the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III, of 208 individuals who had previously completed an online risk assessment were scored blindly and independently by two movement-disorders experts. Higher risk and lower risk subjects were compared for MDS-UPDRS part III score (and derivations of this) to identify subclinical parkinsonism, and association of risk estimates with MDS-UPDRS III scores assessed.
Higher risk subjects had significantly higher median UPDRS part III scores (3, IQR 1-5.5) than lower risk subjects (1, IQR 0-3.0; p<0.001), and there was a significantly greater proportion of individuals classified as having subclinical parkinsonism. 18% of the higher risk subjects and 6% of the lower risk subjects exceeded the most stringent published cut-off for subtle parkinsonism of three definitions examined (p=0.027). Linear regression analysis demonstrated a continuous relationship of log-transformed risk estimates with UPDRS part III scores (increase in MDS-UPDRS per doubling of odds 0.52, 95% CI 0.31 to 0.72; p<0.001), which remained after adjustment for multiple vascular risk factors and scores on the Montreal Cognitive Assessment (0.58, 95% CI 0.30 to 0.87; p<0.001).
The PREDICT-PD algorithm identifies a population with an increased rate of motor disturbances.
PREDICT-PD研究旨在通过对帕金森病(PD)先前确定的风险和早期特征进行在线评估以及基于证据的评分算法,来识别帕金森病风险增加的情况。我们试图确定与低风险参与者相比,高风险参与者(定义为风险估计值高于第15百分位数的人群)是否更有可能出现轻度帕金森体征。
对208名先前完成在线风险评估的个体进行神经学检查的视频记录,包括运动障碍协会统一帕金森病评定量表(MDS-UPDRS)第三部分,由两名运动障碍专家进行盲法独立评分。比较高风险和低风险受试者的MDS-UPDRS第三部分评分(及其衍生指标),以识别亚临床帕金森综合征,并评估风险估计值与MDS-UPDRS III评分之间的关联。
高风险受试者的UPDRS第三部分中位数评分(3,四分位距1-5.5)显著高于低风险受试者(1,四分位距0-3.0;p<0.001),并且被归类为患有亚临床帕金森综合征的个体比例显著更高。在研究的三个定义中,18%的高风险受试者和6%的低风险受试者超过了已发表的最严格的轻微帕金森综合征临界值(p=0.027)。线性回归分析表明,对数转换后的风险估计值与UPDRS第三部分评分之间存在连续关系(优势比每增加一倍,MDS-UPDRS增加0.52,95%可信区间0.31至0.72;p<0.001),在对多种血管危险因素和蒙特利尔认知评估得分进行调整后,这种关系仍然存在(0.58,95%可信区间0.30至0.87;p<0.001)。
PREDICT-PD算法识别出了运动障碍发生率增加的人群。