Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Division of Neurology, Department of Internal Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Dement Geriatr Cogn Disord. 2018;45(1-2):38-48. doi: 10.1159/000487232. Epub 2018 Apr 4.
The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) developed a neuropsychological battery (CERAD-NP) to screen patients with Alzheimer's dementia. Mild cognitive impairment (MCI) has received attention as a pre-dementia stage.
To delineate the CERAD-NP features of MCI and their clinical utility to externally validate MCI diagnosis.
The study included 60 patients with MCI, diagnosed using the Clinical Dementia Rating, and 63 normal controls. Data were analysed employing receiver operating characteristic analysis, Linear Support Vector Machine, Random Forest, Adaptive Boosting, Neural Network models, and t-distributed stochastic neighbour embedding (t-SNE).
MCI patients were best discriminated from normal controls using a combination of Wordlist Recall, Wordlist Memory, and Verbal Fluency Test. Machine learning showed that the CERAD features learned from MCI patients and controls were not strongly predictive of the diagnosis (maximal cross-validation 77.2%), whilst t-SNE showed that there is a considerable overlap between MCI and controls.
The most important features of the CERAD-NP differentiating MCI from normal controls indicate impairments in episodic and semantic memory and recall. While these features significantly discriminate MCI patients from normal controls, the tests are not predictive of MCI.
阿尔茨海默病注册研究联盟（CERAD）开发了一种神经心理学测试工具（CERAD-NP），用于筛查阿尔茨海默病患者。轻度认知障碍（MCI）作为一种痴呆前阶段受到了关注。
描述 MCI 的 CERAD-NP 特征及其临床应用，以对外验证 MCI 诊断。
该研究纳入了 60 名 MCI 患者（采用临床痴呆评定量表进行诊断）和 63 名正常对照者。采用受试者工作特征分析、线性支持向量机、随机森林、自适应提升、神经网络模型和 t 分布随机近邻嵌入（t-SNE）进行数据分析。
使用词汇回忆、词汇记忆和语言流畅性测验的组合可以最佳地区分 MCI 患者和正常对照者。机器学习显示，从 MCI 患者和对照组中学习到的 CERAD 特征对诊断的预测性不强（最大交叉验证 77.2%），而 t-SNE 显示 MCI 和对照组之间存在相当大的重叠。
区分 MCI 和正常对照组的 CERAD-NP 最重要的特征表明存在情节记忆和语义记忆及回忆受损。虽然这些特征可以显著区分 MCI 患者和正常对照组，但这些测试不能预测 MCI。
