对CogEvo对老年人认知能力下降的预测进行了纵向研究
Sadanobu Ichii1, Hikaru Oba2, Yoshikuni Sugimura1
1Department of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki 036-8562, Japan.
Healthcare (Basel, Switzerland)
|July 26, 2024
概括
基于计算机的CogEvo查有效地预测了老年人的认知衰退 (CD). 4级表示CD风险较高,有助于早期识别痴呆症.
科学领域:
- 老年学是一门学科.
- 神经学 神经学
- 医疗信息学 医疗信息学
背景情况:
- 老年人早期认知衰退 (CD) 计算机查的长度验证是有限的.
- 评估CogEvo设备在社区居住的老年人群中对CD的预测效用至关重要.
研究的目的:
- 评估CogEvo的纵向预测能力,CogEvo是一个用户友好的基于计算机的认知查工具,用于识别老年人的认知衰退.
- 为了确定CogEvo的基线判断等级是否可以预测CD在两年内的发展.
主要方法:
- 一组119名日本老年人 (≥65岁) 的小心理状态检查 (MMSE) 得分≥24每年被跟踪两年.
- 认知衰退 (CD) 被定义为一个MMSE得分≤23.
- 在基线时分配了CogEvo判断等级,较低的等级表明更好的认知功能.
主要成果:
- 在为期两年的研究期间,10名参与者发展出认知衰退 (CD).
- 与CogEvo等级为4的参与者显示,与等级≤3 (p <0.01) 的参与者相比,CD的发病率显著更高.
- 在调整了基线MMSE得分和其他混因子后,这种关联仍然显著,CogEvo 4.级的灵敏度为50.0%,特异性为93.6%.
结论:
- 科格埃沃 (CogEvo) 显示出其作为一种有效工具的潜力,用于识别患痴呆症高风险的老年人.
- 虽然有希望,但假阴性结果的可能性需要在实施CogEvo用于查目的时仔细考虑.
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