Institute of Neuroscience, Newcastle University Institute for Aging, Newcastle upon Tyne, UK.
Physiotherapy. 2017 Dec;103(4):459-464. doi: 10.1016/j.physio.2016.08.002. Epub 2016 Sep 3.
Falls are a major problem for people with Parkinson's disease (PD). Despite years of focused research knowledge of falls aetiology is poor. This may be partly due to classification approaches which conventionally report fall frequency. This nosology is blunt, and does not take into account causality or the circumstances in which the fall occurred. For example, it is likely that people who fall from a postural transition are phenotypically different to those who fall during high level activities. Recent evidence supports the use of a novel falls classification based on fall related activity, however its clinimetric properties have not yet been tested.
This study describes further development of the Fall-Related Activity Classification (FRAC) and reports on its inter-rater reliability (IRR).
Descriptors of the FRAC were refined through an iterative process with a multidisciplinary team. Three categories based on the activity preceding the fall were identified. PD fallers were categorised as: (1) advanced (2) combined or (3) transitional. Fifty-five fall scenarios were rated by 23 raters using a standardised process. Raters comprised 3 clinical subgroups: (1) physiotherapists, (2) physicians, (3) non-medical researchers. IRR analysis was performed using weighted kappa coefficients and included sub group analysis based on clinical speciality.
Excellent agreement was reached for all clinicians, κ=0.807 (95% CI 0.732 to 0.870). Clinical subgroups performed similarly well (range of κ=0.780 to 0.822).
The FRAC can be reliably used to classify falls. This may discriminate between phenotypically different fallers and subsequently strengthen falls predictors in future studies.
跌倒对于帕金森病（PD）患者来说是一个主要问题。尽管经过多年的集中研究，但对跌倒的病因知之甚少。这可能部分归因于传统上报告跌倒频率的分类方法。这种分类方法比较生硬，没有考虑到因果关系或跌倒发生的情况。例如，从姿势转换中跌倒的人与在高水平活动中跌倒的人在表型上可能有所不同。最近的证据支持使用基于与跌倒相关的活动的新型跌倒分类，但尚未对其临床计量学特性进行测试。
本研究进一步描述了跌倒相关活动分类（FRAC）的开发情况，并报告了其组内一致性（IRR）。
通过多学科团队的迭代过程对 FRAC 的描述符进行了改进。根据跌倒前的活动确定了三个类别。将 PD 跌倒者分为：（1）高级，（2）综合或（3）过渡。使用标准化程序，由 23 名评估者对 55 个跌倒场景进行了评估。评估者由 3 个临床亚组组成：（1）物理治疗师，（2）医生，（3）非医学研究人员。使用加权 Kappa 系数进行 IRR 分析，包括基于临床专业的亚组分析。
所有临床医生都达到了极好的一致性，κ=0.807（95%CI 0.732 至 0.870）。临床亚组的表现同样出色（κ值范围为 0.780 至 0.822）。
FRAC 可可靠地用于分类跌倒。这可能区分表型不同的跌倒者，并随后在未来的研究中增强跌倒预测因子。
