使用德国 CERAD 的总分进行阿尔茨海默病的早期检测。

Early detection of Alzheimer's disease with a total score of the German CERAD.

机构信息

Department of Geriatrics, University Hospital Basel, Basel, Switzerland.

出版信息

J Int Neuropsychol Soc. 2010 Sep;16(5):910-20. doi: 10.1017/S1355617710000822. Epub 2010 Aug 4.

PMID:20682088

Abstract

The goal of the present study was to evaluate the diagnostic discriminability of three different global scores for the German version of the Consortium to Establish a Registry on Alzheimer's Disease-Neuropsychological Assessment Battery (CERAD-NAB). The CERAD-NAB was administered to 1100 healthy control participants [NC; Mini-Mental State Examination (MMSE) mean = 28.9] and 352 patients with very mild Alzheimer's disease (AD; MMSE mean = 26.1) at baseline and subsets of participants at follow-up an average of 2.4 (NC) and 1.2 (AD) years later. We calculated the following global scores: Chandler et al.'s (2005) score (summed raw scores), logistic regression on principal components analysis scores (PCA-LR), and logistic regression on demographically corrected CERAD-NAB variables (LR). Correct classification rates (CCR) were compared with areas under the receiver operating characteristics curves (AUC). The CCR of the LR score (AUC = .976) exceeded that of the PCA-LR, while the PCA-LR (AUC = .968) and Chandler (AUC = .968) scores performed comparably. Retest data improved the CCR of the PCA-LR and Chandler (trend) scores. Thus, for the German CERAD-NAB, Chandler et al.'s total score provided an effective global measure of cognitive functioning, whereby the inclusion of retest data tended to improve correct classification of individual cases.

摘要

本研究旨在评估 Consortium to Establish a Registry on Alzheimer's Disease-Neuropsychological Assessment Battery（CERAD-NAB）德语版的三个不同总体评分的诊断区分能力。在基线时，对 1100 名健康对照参与者[NC；简易精神状态检查（MMSE）平均= 28.9]和 352 名轻度阿尔茨海默病（AD）患者[MMSE 平均= 26.1]进行了 CERAD-NAB 测试，并在平均 2.4 年[NC]和 1.2 年[AD]后对参与者进行了随访。我们计算了以下总体评分：Chandler 等人的（2005 年）评分（原始分数总和），基于主成分分析得分的逻辑回归（PCA-LR），以及基于人口统计学校正的 CERAD-NAB 变量的逻辑回归（LR）。正确分类率（CCR）与接收者操作特征曲线下的面积（AUC）进行了比较。LR 评分的 CCR（AUC =.976）高于 PCA-LR，而 PCA-LR（AUC =.968）和 Chandler（AUC =.968）评分的性能相当。重测数据提高了 PCA-LR 和 Chandler（趋势）评分的 CCR。因此，对于德语 CERAD-NAB，Chandler 等人的总分提供了认知功能的有效总体衡量标准，其中包含重测数据有助于提高个体病例的正确分类。