Studies have evaluated the effectiveness of MoCA in different settings around the world, and it has been shown to be valid and reliable tool to detect dementia. ![]() 9–11 A cut point of 26 has been recommended to identify major neurocognitive disorder and MoCA had 100% sensitivity, 87% specificity, 89% positive predictive value, and 91% negative predictive values in the initial validation study. 9 Visuospatial, executive functioning, short-term memory, attention/concentration/working memory, language, and orientation are the cognitive domains assessed by the tool. MoCA is a brief cognitive function assessment tool with 12 items developed by Nasreddine et al in 2005. 4, 8 This warrants the development of new tools or testing the available ones for their applicability in low educated and highly diverse populations of LMICs. Many of the currently available cognitive screening tools were developed in the socioeconomically developed settings. 3, 6 Availability of such the screening tools would enable service providers in Low- and Middle-Income Countries (LMIC) to identify the disorder and direct effective interventions. The need for such tools is even more pronounced in the developing countries with a significant gap in human, material, and facility resources to effectively identify those with the dementia. For this reason, brief and effective screening tools have been developed over the years. ![]() However, all these may not always be available, especially in resource limited settings. 5Įffective diagnosis and identification of the disorder and its treatment require extensive evaluations, diagnostic procedures, imaging, and laboratory tests. 4 A study in Ethiopia reported a 43.8% prevalence of Dementia among older adults among whom22.9% were reported to have moderate-to-severe cognitive impairment. 1–3 Globally, it is estimated that around 55 million people live with Dementia, which is the seventh leading cause of mortality worldwide. Major neurocognitive disorder (Dementia) is a neurodegenerative disorder characterized mainly by progressive decline in the cognitive functioning. Conclusions: MoCA test better meets the criteria for screening tests for the detection of MCI among patients over 60 years of age than MMSE.Cognition is one of the most complex functions of the human brain that incorporates language, attention, orientation, memory, judgment, abstract reasoning, problem-solving, praxis, and executive function. 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). 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. 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. Objectives: Screening tests play a crucial role in dementia diagnostics, thus they should be very sensitive for mild cognitive impairment (MCI) assessment.
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