Finger Tapping Test for Assessing the Risk of Mild Cognitive Impairment.

Shota Suzumura, Aiko Osawa, Yoshikiyo Kanada, Maeda Keisuke, Eiko Takano, Junpei Sugioka, Maeda Natsumi, Taishi Nagahama, Kenta Shiramoto, Katsumi Kuno, Shiori Kizuka, Kenji Satoh, Hiroaki Sakurai, Yuko Sano, Tomohiko Mizuguchi, Akihiko Kandori, Izumi Kondo
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Abstract

Aim: A testing method for early diagnosis of Mild cognitive dementia (MCI) that can be easily applied in clinical practice was investigated in this study. We examined whether MCI risk can be determined through finger movements.

Methods: Between 2013 and 2020, 1097 individuals were screened. After applying propensity-score matching to adjust for variability between the groups, 173 individuals each in the mild cognitive impairment and control groups were selected. Thereafter, differences between groups in mean values of parameters extracted from finger tap movements were determined using unpaired t-test and effect size. Furthermore, area under the curve, sensitivity, and specificity were calculated from the receiver operating characteristic curve for parameters with significant difference.

Results: A significant difference was observed, especially in the number of taps in the MCI group compared with that in the control group (p < .001; 95% CI, -12.7 to -8.8; r = 0.51). A cut-off value of 30 taps was applied (sensitivity, 0.77; specificity, 0.67; AUC, 0.79). Significant differences were also observed in rhythm-related parameters.

Conclusions: These parameters might be useful for capturing MCI risk. Finger taps are easily measured and may be suitable for screening large populations. This tool might be used as a supplemental method to increase the sensitivity of traditional cognitive tests.

Abstract Image

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用于评估轻度认知障碍风险的手指敲击测试。
目的:本研究探讨了一种易于应用于临床实践的早期诊断轻度认知痴呆(MCI)的测试方法。我们研究了是否可以通过手指运动来确定 MCI 风险:方法:2013 年至 2020 年间,我们对 1097 人进行了筛查。采用倾向分数匹配法调整组间差异后,轻度认知障碍组和对照组各选出 173 人。随后,采用非配对 t 检验和效应大小法确定了各组间从手指敲击运动中提取的参数平均值的差异。此外,还根据接收者操作特征曲线计算了有显著差异的参数的曲线下面积、灵敏度和特异性:与对照组相比,MCI 组的拍击次数有明显差异(P < .001;95% CI,-12.7 至 -8.8;r = 0.51)。以 30 次为临界值(灵敏度为 0.77;特异性为 0.67;AUC 为 0.79)。在节律相关参数中也观察到了显著差异:这些参数可能有助于捕捉 MCI 风险。手指敲击法易于测量,可能适用于大量人群的筛查。该工具可作为一种补充方法,提高传统认知测试的灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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