Department of Medical Rehabilitation, Faculty of Health Sciences, University of Nigeria, Enugu Campus, Enugu, Enugu State, Nigeria.
Department of Physiotherapy, Nnamdi Azikiwe University Teaching Hospital, Nnewi, Nigeria.
BMC Geriatr. 2022 Aug 11;22(1):658. doi: 10.1186/s12877-022-03282-2.
Systematic reviews demonstrated that gait variables are the most reliable predictors of future falls, yet are rarely included in fall screening tools. Thus, most tools have higher specificity than sensitivity, hence may be misleading/detrimental to care. Therefore, this study aimed to determine the validity, and reliability of the velocity field diagram (VFD -a gait analytical tool), and the Timed-up-and-go test (TUG)-commonly used in Nigeria as fall screening tools, compared to a gold standard (known fallers) among community-dwelling older adults.
This is a cross-sectional observational study of 500 older adults (280 fallers and 220 non-fallers), recruited by convenience sampling technique at community health fora on fall prevention. Participants completed a 7-m distance with the number of steps and time it took determined and used to compute the stride length, stride frequency, and velocity, which regression lines formed the VFD. TUG test was simultaneously conducted to discriminate fallers from non-fallers. The cut-off points for falls were: TUG times ≥ 13.5 s; VFD's intersection point of the stride frequency, and velocity regression lines (E) ≥ 3.5velots. The receiver operating characteristic (ROC) area under the curves (AUC) was used to explore the ability of the E ≥ 3.5velots to discriminate between fallers and non-fallers. The VFD's and TUG's sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined. Alpha was set at p < 0.05.
The VFD versus TUG sensitivity, specificity, PPV and NPV were 71%, 27%, 55%, and 42%, versus 39%, 59%, 55%, and 43%, respectively. The ROC's AUC were 0.74(95%CI:0.597,0.882, p = 0.001) for the VFD. The optimal categorizations for discrimination between fallers/non-fallers were ≥ 3.78 versus ≤ 3.78 for VFD (fallers versus non-fallers prevalence is 60.71% versus 95.45%, respectively), with a classification accuracy or prediction rate of 0.76 unlike TUG with AUC = 0.53 (95% CI:0.353,0.700, p = 0.762), and a classification accuracy of 0.68, and optimal characterization of ≥ 12.81 s versus ≤ 12.81 (fallers and non-fallers prevalence = 92.86% versus 36.36%, respectively).
The VFD demonstrated a fair discriminatory power and greater reliability in identifying fallers than the TUG, and therefore, could replace the TUG as a primary tool in screening those at risk of falls.
系统评价表明，步态变量是预测未来跌倒最可靠的指标，但很少被纳入跌倒筛查工具。因此，大多数工具的特异性高于敏感性，因此可能对护理产生误导/不利影响。因此，本研究旨在确定速度场图（VFD-一种步态分析工具）和计时起立行走测试（TUG）在尼日利亚常用的跌倒筛查工具的有效性和可靠性，与社区居住的老年人中的金标准（已知跌倒者）进行比较。
这是一项横断面观察性研究，纳入了 500 名老年人（280 名跌倒者和 220 名非跌倒者），通过社区健康论坛的便利抽样技术招募。参与者完成了 7 米的距离，记录了步数和用时，用于计算步长、步频和速度，这些回归线形成了 VFD。同时进行 TUG 测试以区分跌倒者和非跌倒者。跌倒的截断点为：TUG 时间≥13.5 秒；VFD 的步频和速度回归线的交点（E）≥3.5velots。受试者工作特征（ROC）曲线下面积（AUC）用于探索 E≥3.5velots 区分跌倒者和非跌倒者的能力。确定了 VFD 和 TUG 的灵敏度、特异性、阳性预测值（PPV）和阴性预测值（NPV）。α 设置为 p<0.05。
VFD 与 TUG 的灵敏度、特异性、PPV 和 NPV 分别为 71%、27%、55%和 42%，39%、59%、55%和 43%。ROC 的 AUC 为 0.74（95%CI：0.597，0.882，p=0.001）对于 VFD。区分跌倒者/非跌倒者的最佳分类为≥3.78 与≤3.78（跌倒者与非跌倒者的患病率分别为 60.71%和 95.45%），分类准确率或预测率为 0.76，而 TUG 的 AUC 为 0.53（95%CI：0.353，0.700，p=0.762），分类准确率为 0.68，最佳特征为≥12.81 秒与≤12.81 秒（跌倒者和非跌倒者的患病率分别为 92.86%和 36.36%）。
VFD 在识别跌倒者方面表现出良好的区分能力和更高的可靠性，优于 TUG，因此可以替代 TUG 作为跌倒风险筛查的主要工具。
