Assessment of Mild Cognitive Impairment Using CogEvo: A Computerized Cognitive Function Assessment Tool.

IF 3 Q1 PRIMARY HEALTH CARE
Toru Satoh, Yoichi Sawada, Hideaki Saba, Hiroshi Kitamoto, Yoshiki Kato, Yoshiko Shiozuka, Tomoko Kuwada, Sayoko Shima, Kana Murakami, Megumi Sasaki, Yudai Abe, Kaori Harano
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引用次数: 0

Abstract

Introduction/objectives: To assess the utility of the computerized cognitive function assessment tool, CogEvo, as a screening tool for mild cognitive impairment in primary care, we explored the relationship between CogEvo performance, age, and the severity of cognitive dysfunction evaluated by the Mini-Mental State Examination (MMSE).

Methods: The observational cross-sectional study included 209 individuals' data (mean age 79.4 ± 8.9 years). We conducted a correlation analysis between CogEvo and MMSE scores, compared the performance among the 3 cognitive function groups (MMSE ≥ 28 group; MMSE24-27 group; MMSE ≤ 23 group) using the MMSE cut-off, and evaluated CogEvo's predictive accuracy for cognitive dysfunction through ROC analysis.

Results: Both total CogEvo and MMSE scores significantly decreased with age. A significant positive correlation was observed between total CogEvo and MMSE scores, but a ceiling effect was detected in MMSE performance. Significant differences were observed in the total CogEvo score, including orientation and spatial cognitive function scores, among the 3 groups. CogEvo showed no educational bias. ROC analyses indicated moderate discrimination between the MMSE ≥ 28 group and the MMSE24-27 and MMSE ≤ 23 groups.

Conclusions: The computer-administered CogEvo has the advantage of not exhibiting ceiling effects or educational bias like the MMSE, and was found to be able to detect age-related cognitive decline and impairment.

使用 CogEvo 评估轻度认知功能障碍:计算机化认知功能评估工具
简介/目的为了评估计算机化认知功能评估工具 CogEvo 作为初级保健中轻度认知功能障碍筛查工具的实用性,我们探讨了 CogEvo 性能、年龄和通过迷你精神状态检查(MMSE)评估的认知功能障碍严重程度之间的关系:观察性横断面研究包括 209 人的数据(平均年龄为 79.4 ± 8.9 岁)。我们对 CogEvo 和 MMSE 分数进行了相关性分析,使用 MMSE 临界值比较了 3 个认知功能组(MMSE ≥ 28 组;MMSE24-27 组;MMSE ≤ 23 组)的表现,并通过 ROC 分析评估了 CogEvo 对认知功能障碍的预测准确性:结果:随着年龄的增长,CogEvo和MMSE总分均明显下降。CogEvo 总分和 MMSE 分数之间存在明显的正相关,但在 MMSE 表现中发现了天花板效应。在 CogEvo 总分(包括定向和空间认知功能得分)方面,3 组之间存在明显差异。CogEvo 没有显示出教育偏差。ROC分析表明,MMSE≥28组与MMSE24-27组和MMSE≤23组之间存在中等程度的差异:结论:计算机管理的 CogEvo 具有不像 MMSE 那样表现出天花板效应或教育偏差的优点,并且能够检测出与年龄相关的认知能力下降和损伤。
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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来源期刊
CiteScore
4.80
自引率
2.80%
发文量
183
审稿时长
15 weeks
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