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采用横断面设计评估将“是/否”任务用作痴呆筛查测试的可行性。

The feasibility of using the go/no-go task as a dementia screening test assessed with a cross-sectional design.

作者信息

Watanabe Noriaki, Kamijo Masayoshi, Nishino Tomoyuki, Ashida Kazuki, Sasamori Fumihito, Okuhara Masao, Maruo Suchinda Jarupat, Tabuchi Hisaaki, Terasawa Koji

机构信息

Graduate School of Medicine, Science and Technology, Shinshu University, 3-15-1, Tokida, Ueda, 386-8567, Nagano, Japan.

Graduate School of Science and Technology, Shinshu University, 3-15-1, Tokida, Ueda, 386-8567, Nagano, Japan.

出版信息

Sci Rep. 2024 Dec 1;14(1):29834. doi: 10.1038/s41598-024-81301-5.

Abstract

The Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Frontal Assessment Battery are screening tests for dementia. The go/no-go task offers an alternative approach for evaluating dementia patients. However, its role in screening for dementia remains unclear. We aimed to explore the feasibility of using the go/no-go task as a screening test for dementia via a cross-sectional design. Twenty-four Japanese individuals were evaluated using the go/no-go task, the MMSE, and the MoCA. The total MMSE and MoCA scores were correlated with the total number of errors in the go/no-go task (r=-0.699, p < 0.01; r=-0.756, p < 0.01). Moreover, When the MoCA cutoff value was 25 for MCI, the optimal cutoff score for the total number of error in the go/no-go task to detect MCI was 2, with an Area Under curve (AUC) of 0.98, a sensitivity of 0.94. When the MMSE cutoff value was 27 for MCI, the optimal cutoff score for the total number of error in the go/no-go task to detect MCI was 6, with an AUC of 0.89, a sensitivity of 0.76, showed respectively values close to 1. The go/no-go task is possible a practical screening test for dementia.

摘要

简易精神状态检查表(MMSE)、蒙特利尔认知评估量表(MoCA)和额叶评估量表是痴呆症的筛查测试。停止信号任务为评估痴呆症患者提供了另一种方法。然而,其在痴呆症筛查中的作用仍不明确。我们旨在通过横断面设计探索将停止信号任务用作痴呆症筛查测试的可行性。对24名日本人进行了停止信号任务、MMSE和MoCA评估。MMSE和MoCA的总分与停止信号任务中的错误总数相关(r = -0.699,p < 0.01;r = -0.756,p < 0.01)。此外,当MoCA用于轻度认知障碍(MCI)的临界值为25时,停止信号任务中用于检测MCI的错误总数的最佳临界分数为2,曲线下面积(AUC)为0.98,灵敏度为0.94。当MMSE用于MCI的临界值为27时,停止信号任务中用于检测MCI的错误总数的最佳临界分数为6,AUC为0.89,灵敏度为0.76,这些值分别接近1。停止信号任务可能是一种实用的痴呆症筛查测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2b87/11609260/7b7f03a2a72f/41598_2024_81301_Fig1_HTML.jpg

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