Department of Neurology and Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.
Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
J Neurol. 2024 Aug;271(8):5187-5196. doi: 10.1007/s00415-024-12444-8. Epub 2024 Jun 4.
Cognitive impairment is now recognized as an impending public health crisis. About one-third of adults are concerned about their cognition, and the prevalence of objective cognitive impairment is much higher among those with neurological disorders. Existing screening tools are narrowly focused on detecting dementia in older adults and must be clinician-administered and scored, making them impractical for many neurology practices. This study examined the utility of a brief, self-administered, computerized cognitive screening tool, the Brief Assessment of Cognitive Health (BACH), in identifying cognitive impairment in adults.
912 adults (ages 18-84) completed BACH and a neuropsychological battery. Multivariable models were developed to provide a BACH index score reflecting the probability of cognitive impairment for individual patients. Predictive accuracy was compared to that of the Montreal Cognitive Assessment (MoCA) in a subset of 160 older adults from a Memory Disorders clinic.
The final multivariable model showed good accuracy in identifying cognitively impaired individuals (c = 0·77). Compared to MoCA, BACH had superior predictive accuracy in identifying older patients with cognitive impairment (c = 0·79 vs. 0·67) as well as differentiating those with MCI or dementia from those without cognitive impairment (c = 0·86 vs. c = 0·67).
Results suggest that cognitive impairment can be identified in adults using a brief, self-administered, automated cognitive screening tool, and BACH provides several advantages over existing screeners: self-administered; automatic scoring; immediate results in health record; easily interpretable score; utility in wide range of patients; and flags for treatable factors that may contribute to cognitive complaints (i.e., depression, sleep problems, and stress).
认知障碍现已被视为即将出现的公共卫生危机。约有三分之一的成年人担心自己的认知能力，而有神经障碍的成年人中客观认知障碍的患病率要高得多。现有的筛查工具狭隘地专注于检测老年人的痴呆症，且必须由临床医生进行管理和评分，这使得它们在许多神经科实践中都不切实际。本研究检验了一种简短的、自我管理的、计算机化的认知筛查工具，即简要认知健康评估（BACH），在识别成年人认知障碍中的效用。
912 名成年人（年龄 18-84 岁）完成了 BACH 和神经心理学测试。建立多变量模型，为每位患者提供反映认知障碍可能性的 BACH 指数评分。在一个记忆障碍诊所的 160 名老年患者亚组中，将预测准确性与蒙特利尔认知评估（MoCA）进行了比较。
最终的多变量模型在识别认知障碍个体方面具有良好的准确性（c=0.77）。与 MoCA 相比，BACH 在识别认知障碍的老年患者方面具有更高的预测准确性（c=0.79 比 0.67），并且能够区分有轻度认知障碍或痴呆症的患者与没有认知障碍的患者（c=0.86 比 c=0.67）。
结果表明，可以使用一种简短的、自我管理的、自动化的认知筛查工具在成年人中识别认知障碍，并且 BACH 比现有的筛查工具具有几个优势：自我管理；自动评分；在健康记录中立即获得结果；易于解释的分数；适用于广泛的患者；并为可能导致认知主诉的可治疗因素（即抑郁、睡眠问题和压力）标记。
