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蒙特利尔认知评估量表(MoCA)临界值的重新审视。

A re-examination of Montreal Cognitive Assessment (MoCA) cutoff scores.

作者信息

Carson Nicole, Leach Larry, Murphy Kelly J

机构信息

Department of Psychology, York University, Toronto, Ontario, Canada.

Department of Psychology, Glendon College, Toronto, Ontario, Canada.

出版信息

Int J Geriatr Psychiatry. 2018 Feb;33(2):379-388. doi: 10.1002/gps.4756. Epub 2017 Jul 21.

DOI:10.1002/gps.4756
PMID:28731508
Abstract

OBJECTIVE

The Montreal Cognitive Assessment (MoCA; Nasreddine et al., 2005) is a cognitive screening tool that aims to differentiate healthy cognitive aging from Mild Cognitive Impairment (MCI). Several validation studies have been conducted on the MoCA, in a variety of clinical populations. Some studies have indicated that the originally suggested cutoff score of 26/30 leads to an inflated rate of false positives, particularly for those of older age and/or lower education. We conducted a systematic review and meta-analysis of the literature to determine the diagnostic accuracy of the MoCA for differentiating healthy cognitive aging from possible MCI.

METHODS

Of the 304 studies identified, nine met inclusion criteria for the meta-analysis. These studies were assessed across a range of cutoff scores to determine the respective sensitivities, specificities, positive and negative predictive accuracies, likelihood ratios for positive and negative results, classification accuracies, and Youden indices.

RESULTS

Meta-analysis revealed a cutoff score of 23/30 yielded the best diagnostic accuracy across a range of parameters.

CONCLUSIONS

A MoCA cutoff score of 23, rather than the initially recommended score of 26, lowers the false positive rate and shows overall better diagnostic accuracy. We recommend the use of this cutoff score going forward. Copyright © 2017 John Wiley & Sons, Ltd.

摘要

目的

蒙特利尔认知评估量表(MoCA;Nasreddine等人,2005年)是一种认知筛查工具,旨在区分健康的认知衰老与轻度认知障碍(MCI)。针对MoCA已在多种临床人群中开展了多项验证研究。一些研究表明,最初建议的26/30的临界值会导致假阳性率过高,尤其是对于年龄较大和/或受教育程度较低的人群。我们对文献进行了系统综述和荟萃分析,以确定MoCA区分健康认知衰老与可能的MCI的诊断准确性。

方法

在检索到的304项研究中,有9项符合荟萃分析的纳入标准。对这些研究在一系列临界值下进行评估,以确定各自的敏感性、特异性、阳性和阴性预测准确性、阳性和阴性结果的似然比、分类准确性以及约登指数。

结果

荟萃分析显示,23/30的临界值在一系列参数中产生了最佳诊断准确性。

结论

MoCA临界值设定为23而非最初推荐的26,可降低假阳性率,并显示出总体上更好的诊断准确性。我们建议今后使用这个临界值。版权所有© 2017约翰·威利父子有限公司。

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