Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA.
Institute of Gerontology, Wayne State University, Detroit, MI, USA.
J Int Neuropsychol Soc. 2022 Mar;28(3):239-248. doi: 10.1017/S135561772100028X. Epub 2021 Mar 23.
Black adults are approximately twice as likely to develop Alzheimer's disease (AD) than non-Hispanic Whites and access diagnostic services later in their illness. This dictates the need to develop assessments that are cost-effective, easily administered, and sensitive to preclinical stages of AD, such as mild cognitive impairment (MCI). Two computerized cognitive batteries, NIH Toolbox-Cognition and Cogstate Brief Battery, have been developed. However, utility of these measures for clinical characterization remains only partially determined. We sought to determine the convergent validity of these computerized measures in relation to consensus diagnosis in a sample of MCI and healthy controls (HC).
Participants were community-dwelling Black adults who completed the neuropsychological battery and other Uniform Data Set (UDS) forms from the AD centers program for consensus diagnosis (HC = 61; MCI = 43) and the NIH Toolbox-Cognition and Cogstate batteries. Discriminant function analysis was used to determine which cognitive tests best differentiated the groups.
NIH Toolbox crystallized measures, Oral Reading and Picture Vocabulary, were the most sensitive in identifying MCI apart from HC. Secondarily, deficits in memory and executive subtests were also predictive. UDS neuropsychological test analyses showed the expected pattern of memory and executive functioning tests differentiating MCI from HC.
Contrary to expectation, NIH Toolbox crystallized abilities appeared preferentially sensitive to diagnostic group differences. This study highlights the importance of further research into the validity and clinical utility of computerized neuropsychological tests within ethnic minority populations.
黑种成年人患阿尔茨海默病（AD）的可能性是非西班牙裔白种人的两倍，并且在疾病的后期才开始接受诊断服务。这就要求我们开发出具有成本效益、易于管理并且能够敏感地检测 AD 临床前阶段（如轻度认知障碍[MCI]）的评估方法。已经开发出了两种计算机化认知电池，即 NIH 工具包认知测试和 Cogstate 简短电池。然而，这些措施在临床特征描述方面的效用仍部分确定。我们旨在确定这些计算机化测量方法与 MCI 和健康对照组（HC）的共识诊断之间的收敛有效性。
参与者是居住在社区的黑种成年人，他们完成了神经心理学测试以及 AD 中心计划的统一数据集（UDS）表单，以进行共识诊断（HC = 61；MCI = 43），并完成了 NIH 工具包认知测试和 Cogstate 电池测试。使用判别函数分析来确定哪些认知测试最能区分这些组。
NIH 工具包的结晶测量，口头阅读和图片词汇，除了 HC 之外，是最能识别 MCI 的方法。其次，记忆和执行子测试的缺陷也具有预测性。UDS 神经心理学测试分析显示了记忆和执行功能测试区分 MCI 和 HC 的预期模式。
与预期相反，NIH 工具包的结晶能力似乎对诊断组之间的差异更敏感。这项研究强调了进一步研究计算机化神经心理学测试在少数民族群体中的有效性和临床实用性的重要性。
