Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, , London, UK.
J Neurol Neurosurg Psychiatry. 2014 Jan;85(1):31-7. doi: 10.1136/jnnp-2013-305420. Epub 2013 Jul 4.
To present methods and baseline results for an online screening tool to identify increased risk for Parkinson's disease (PD) in the UK population.
Risk estimates for future PD were derived from the results of a systematic review of risk factors and early features of PD. Participants aged 60-80 years without PD were recruited by self-referral. They completed an online survey (including family history, non-motor symptoms and lifestyle factors), a keyboard-tapping task and the University of Pennsylvania Smell Identification Test. Risk scores were calculated based on survey answers. Preliminary support for the validity of this algorithm was assessed by comparing those estimated to be higher risk for PD with those at lower risk using proxies, including smell loss, REM-sleep behaviour disorder and reduced tapping speed, and by assessing associations in the whole group.
1324 eligible participants completed the survey and 1146 undertook the keyboard-tapping task. Smell tests were sent to 1065 participants. Comparing the 100 highest-risk participants and 100 lowest-risk participants, median University of Pennsylvania Smell Identification Test scores were 30/40 versus 33/40 (p<0.001), mean number of key taps in 30 s were 55 versus 58 (p=0.045), and 24% versus 10% scored above cut-off for REM-sleep behaviour disorder (p=0.008). Regression analyses showed increasing risk scores were associated with worse scores in the three proxies across the whole group (p≤0.001).
PREDICT-PD is the first study to systematically combine risk factors for PD in the general population. Validity to predict risk of PD will be tested through longitudinal follow-up of incident PD diagnosis.
介绍一种在线筛查工具的方法和基线结果，用于识别英国人群中帕金森病（PD）的发病风险增加。
通过对 PD 的危险因素和早期特征的系统回顾得出未来 PD 的风险估计。通过自我推荐招募年龄在 60-80 岁之间且没有 PD 的参与者。他们完成了在线调查（包括家族史、非运动症状和生活方式因素）、键盘敲击任务和宾夕法尼亚大学嗅觉识别测试。根据调查答案计算风险评分。通过使用嗅觉丧失、快速眼动睡眠行为障碍和降低的敲击速度等替代指标来比较那些估计患有 PD 风险较高的人与风险较低的人，以及评估整个组中的关联，初步评估了该算法的有效性。
1324 名符合条件的参与者完成了调查，1146 名参与者进行了键盘敲击任务。向 1065 名参与者发送了嗅觉测试。比较 100 名风险最高的参与者和 100 名风险最低的参与者，宾夕法尼亚大学嗅觉识别测试的中位数分数分别为 30/40 与 33/40（p<0.001），30 秒内的平均敲击次数分别为 55 与 58（p=0.045），24%与 10%的 REM 睡眠行为障碍评分高于临界值（p=0.008）。回归分析显示，整个组中风险评分越高，三个替代指标的得分越差（p≤0.001）。
PREDICT-PD 是第一项系统地将一般人群中的 PD 危险因素结合在一起的研究。通过对 PD 发病风险的纵向随访，将对其预测有效性进行测试。
