PDF(Pubmed)
Abstract：
OBJECTIVE: 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.
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: 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).
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: 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).
摘要：
目的：认知障碍现在被认为是一种迫在眉睫的公共卫生危机。大约三分之一的成年人担心他们的认知，在神经系统疾病患者中，客观认知障碍的患病率要高得多。现有的筛查工具只专注于检测老年人的痴呆症，必须由临床医生管理并进行评分。使它们对许多神经病学实践不切实际。这项研究检查了一个简短的实用性，自我管理,计算机化的认知筛查工具，认知健康简要评估(BACH)，在确定成年人的认知障碍。
方法：912名成年人（18-84岁）完成了BACH和神经心理电池。开发了多变量模型以提供反映个体患者认知障碍概率的BACH指数评分。在记忆障碍诊所的160名老年人中，将预测准确性与蒙特利尔认知评估（MoCA）进行了比较。
结果：最终的多变量模型在识别认知障碍个体方面显示出良好的准确性（c=0·77）。与MoCA相比,BACH在识别老年认知障碍患者方面具有较高的预测准确性（c=0.79vs.0·67）以及将MCI或痴呆症患者与无认知障碍患者区分开来（c=0·86与c=0·67）。
结论：结果表明，可以使用简短的，自我管理,自动认知筛查工具，和BACH提供了优于现有筛查者的几个优点：自我管理；自动评分；健康记录的即时结果；易于解释的评分；在广泛的患者中的实用性；以及可能导致认知投诉的可治疗因素的标志（即，抑郁症,睡眠问题,和压力）。
方法：912名成年人（18-84岁）完成了BACH和神经心理电池。开发了多变量模型以提供反映个体患者认知障碍概率的BACH指数评分。在记忆障碍诊所的160名老年人中，将预测准确性与蒙特利尔认知评估（MoCA）进行了比较。
结果：最终的多变量模型在识别认知障碍个体方面显示出良好的准确性（c=0·77）。与MoCA相比,BACH在识别老年认知障碍患者方面具有较高的预测准确性（c=0.79vs.0·67）以及将MCI或痴呆症患者与无认知障碍患者区分开来（c=0·86与c=0·67）。
结论：结果表明，可以使用简短的，自我管理,自动认知筛查工具，和BACH提供了优于现有筛查者的几个优点：自我管理；自动评分；健康记录的即时结果；易于解释的评分；在广泛的患者中的实用性；以及可能导致认知投诉的可治疗因素的标志（即，抑郁症,睡眠问题,和压力）。
