![]() ![]() Conclusions: MoCA test better meets the criteria for screening tests for the detection of MCI among patients over 60 years of age than MMSE. For MMSE, it turned out that more important cut-off was of 27/28 (n = 882, 66.34% sensitivity and specificity of 72.94%). 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%). 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). Longitudinal cognitive testing is essential for developing novel preventive interventions for dementia and Alzheimer’s disease however, the few available tools have significant practice effect and depend on an external evaluator. 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. ![]() At the end, for the evaluation of MoCA 20, and MMSE 13 studies were qualified. Papers which met inclusion and exclusion criteria were chosen to be included in this review. A feasibility study of conducting the Montreal Cognitive Assessment remotely in individuals with movement disorders A Abdolahi, MT Bull, KC Darwin Health informatics, 2016 Health Informatics J. The following medical subject headings were used in the search: mild cognitive impairment, mini-mental state examination, Montreal cognitive assessment, diagnostics value. ![]() 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. MMSE credibility assessment in detecting MCI, while taking into consideration the sensitivity and specificity by cut-off points. The Montreal Cognitive Assessment (MoCA), was created as an alternative method for MMSE.Īim. Nowadays, the MiniMental State Examination (MMSE) is the most commonly used scale in cognitive function evaluation, albeit it is claimed to be imprecise for MCI detection. Bold-faced p-values are 0.05 and indicate that the AUC of the respective short. a Bonferroni-adjusted p-values in the comparisons of AUC between the original MoCA and the respective short versions. Objectives: Screening tests play a crucial role in dementia diagnostics, thus they should be very sensitive for mild cognitive impairment (MCI) assessment. MoCA, Montreal Cognitive Assessment AUC, area under the receiver operating characteristics curve CI, confidence interval Ref, reference. ![]()
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