![]() Īmato MP, Razzolini L, Goretti B et al (2013) Cognitive reserve and cortical atrophy in multiple sclerosis: a longitudinal study. Īmato MP, Ponziani G, Siracusa G et al (2001) Cognitive dysfunction in early-onset multiple sclerosis: a reappraisal after 10 years. Sumowski JF, Benedict R, Enzinger C, Filippi M, Geurts JJ, Hamalainen P et al (2018) Cognition in multiple sclerosis: state of the field and priorities for the future. Rao SM, Leo GJ, Bernardin L, Unverzagt F (1991) Cognitive dysfunction in multiple sclerosis: frequency, patterns, and prediction. Zhang X, Zhang F, Huang D et al (2017) Contribution of gray and white matter abnormalities to cognitive impairment in multiple sclerosis. ![]() Ĭhiaravalloti ND, DeLuca J (2008) Cognitive impairment in multiple sclerosis. Trapp BD, Ransohoff R, Rudick R (1999) Axonal pathology in multiple sclerosis: relationship to neurologic disability. Nonetheless, more studies are required to examine the optimum cut-off score for detecting cognitive impairments in MS patients. In patients with MS, the MoCA provides information on general cognitive functions disturbances. Furthermore, in MS patients without subjective cognitive complaints, a cutoff of 27 could provide a better balance between the sensitivity and the specificity of the test. Although the MoCA test demonstrated good sensitivity and specificity when used at the recommended threshold of 26, a lower threshold than the original cut-off was also reported to be useful for optimal screening, as it lowers false positive rates and improves diagnostic accuracy. Publication period ranged from 2012 to 2020. We identified fourteen studies that met the inclusion criteria: three cross-sectional studies and two case – control studies comparing MoCA to a battery of tests, one study comparing MoCA to Mini-Mental State Examination (MMSE), and eight studies estimating the prevalence of cognitive impairment in individuals with MS. We conducted a systematic literature review, searching five databases from inception until May 2020. Conclusions: MoCA test better meets the criteria for screening tests for the detection of MCI among patients over 60 years of age than MMSE.This study aims to systematically review the evidence on the accuracy of the Montreal Cognitive Assessment (MoCA) test for evaluating the presence of cognitive impairment in patients with multiple sclerosis (MS) and to outline the quality and quantity of research evidence available about the use of MoCA in this population. 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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