Mercer's Institute for Research on Ageing, St James's Hospital, Dublin 8, Ireland.
Int J Geriatr Psychiatry. 2010 Dec;25(12):1280-7. doi: 10.1002/gps.2480.
The Cambridge cognitive examination (CAMCOG) is a mini neuropsychological battery which is well established and widely used. The utility of the CAMCOG in detecting prodromal Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI) has not been determined. The objectives of this study are: to establish which subtests of cognitive domains contained within the CAMCOG are predictive of conversion to AD, to compare these with an extended version of the delayed word recall (DWR) test and to establish optimal cut points for all measures used.
182 patients with MCI were identified from consecutive referrals to a memory clinic. Logistic regression, cox regression and receiver operating characteristic curve (ROC) analyses were conducted.
The DWR displayed the best sensitivity (77%) and specificity (76%). The composite memory score contained within the CAMCOG achieved similar sensitivity (78%) and specificity (74%). The recognition component of the extended DWR demonstrated good specificity (85%) but poor sensitivity (57%). The optimal predictive model combined category fluency with the DWR and achieved predictive accuracy of 83%.
The DWR, which is a test specifically designed to have high predictive accuracy for AD, performed best. The composite measure of memory contained within the CAMCOG performed similarly well. The DWR has the advantage of being brief, easy to administer and suitable for use in non-specialist settings. The CAMCOG takes longer to administer but provides information regarding additional cognitive domains and is sensitive to change over time. Category fluency may be usefully combined with the DWR to improve predictive accuracy.
剑桥认知测验(CAMCOG)是一种成熟且广泛应用的微型神经心理学测试。CAMCOG 在检测轻度认知障碍(MCI)患者前驱期阿尔茨海默病(AD)中的作用尚未确定。本研究的目的是:确定 CAMCOG 认知领域的哪些子测验可预测向 AD 的转化;将其与扩展后的延迟词回忆测试(DWR)进行比较;并确定所有使用的测量方法的最佳临界点。
从连续转诊至记忆门诊的 MCI 患者中确定了 182 名患者。进行逻辑回归、Cox 回归和受试者工作特征曲线(ROC)分析。
DWR 的敏感性(77%)和特异性(76%)最佳。CAMCOG 中包含的复合记忆评分具有相似的敏感性(78%)和特异性(74%)。扩展 DWR 的识别成分特异性较好(85%)但敏感性较差(57%)。最佳预测模型结合了类别流畅性与 DWR,预测准确率为 83%。
专为 AD 预测设计的 DWR 表现最佳。CAMCOG 中的记忆综合测量表现同样出色。DWR 的优点是简短、易于管理且适用于非专业环境。CAMCOG 的实施时间较长,但提供了有关其他认知领域的信息,并且对时间的变化敏感。类别流畅性可能与 DWR 相结合,以提高预测准确性。