Is the Montreal Cognitive Assessment (MoCA) test better suited than the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) detection among people aged over 60? Meta-analysis
Is the Montreal Cognitive Assessment (MoCA) test better suited than the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) detection among people aged over 60? Meta-analysis
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DOI：
10.12740/pp/45368
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发表时间：
2016-01-01
影响因子：
1.7
通讯作者：
Kedziora-Kornatowska, Kornelia
中科院分区：
文献类型：
--
作者：
Ciesielska, Natalia;Sokolowski, Remigiusz;Kedziora-Kornatowska, Kornelia
导论.筛查测试在痴呆诊断中起着至关重要的作用，因此它们对于轻度认知障碍（MCI）的评估应该非常敏感。目前，简易精神状态检查量表（MMSE）是认知功能评价中最常用的量表，尽管它被认为对MCI检测不精确。蒙特利尔认知评估（莫卡）是MMSE的替代方法。莫卡与MMSE在MCI检测中的可信度评估，同时考虑了敏感性和特异性的截止点。材料和方法。作者使用EBSCO host Web、Wiley Online Library、Springer Link、Science Direct和Medline数据库进行了系统的文献检索。检索中使用了以下医学主题词：轻度认知障碍、简易精神状态检查、蒙特利尔认知评估、诊断价值。选择符合纳入和排除标准的论文纳入本综述。最后，对莫卡20和MMSE 13项研究进行了评价，通过计算加权算术平均值建立了研究可信度，其中权重定义为达到截止点的敏感性和特异性结果的人群。临界值显示为ROC曲线，莫卡和MMSE的诊断准确度计算为曲线下面积（AUC）。结果莫卡的ROC曲线分析表明，MCI的最佳检测截止点为24/25（n = 9350，敏感性为80.48%，特异性为81.19%）。AUC为0.846（95% CI 0.823-0.868）。对于MMSE，结果表明，更重要的截止值为27/28（n = 882，灵敏度为66.34%，特异性为72.94%）。AUC为0.736（95%CI 0.718-0.767）。莫卡测试比MMSE更好地满足60岁以上患者中MCI检测的筛查测试标准。
Introduction. Screening tests play a crucial role in dementia diagnostics, thus they should be very sensitive for mild cognitive impairment (MCI) assessment. Nowadays, the Mini-Mental State Examination (MMSE) is the most commonly used scale in cognitive function evaluation, albeit it is claimed to be imprecise for MCI detection. The Montreal Cognitive Assessment (MoCA), was created as an alternative method for MMSE.Aim. MoCA vs. MMSE credibility assessment in detecting MCI, while taking into consideration the sensitivity and specificity by cut-off points.Material and methods. A systematic literature search was carried out by the authors using EBSCO host Web, Wiley Online Library, Springer Link, Science Direct and Medline databases. The following medical subject headings were used in the search: mild cognitive impairment, mini-mental state examination, Montreal cognitive assessment, diagnostics value. Papers which met inclusion and exclusion criteria were chosen to be included in this review. At the end, for the evaluation of MoCA 20, and MMSE 13 studies were qualified.Research credibility was established by computing weighted arithmetic mean, where weight is defined as population for which the result of sensitivity and specificity for the cut-off point was achieved. The cut-offs are shown as ROC curve and accuracy of diagnosis for MoCA and MMSE was calculated as the area under the curve (AUC). Results. ROC curve analysis for MoCA demonstrated that MCI best detection can be achieved with a cut-off point of 24/25 (n = 9350, the sensitivity of 80.48% and specificity of 81.19%). AUC was 0.846 (95% CI 0.823-0.868). For MMSE, it turned out that more important cut-off was of 27/28 (n = 882, 66.34% sensitivity and specificity of 72.94%). AUC was 0.736 (95% CI 0.718-0.767).Conclusions. MoCA test better meets the criteria for screening tests for the detection of MCI among patients over 60 years of age than MMSE.