Optimal cut-off scores for the Mini Mental State Examination and Montreal Cognitive Assessment to detect MCI and dementia in Multiple System Atrophy

Background: Mild cognitive impairment (MCI) and dementia are reported in up to 44 % and 7 % of patients with Multiple system atrophy (MSA), respectively. The sensitivity and discriminative power of brief cognitive screening tools such as the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) for detecting MCI and dementia in MSA has not yet been evaluated. Objective: The aim of this study was to determine the optimal cut-off scores of the MMSE and MoCA for accurately differentiating MSA patients with MCI and dementia from those with normal cognition. The fluency item of MoCA was also assessed separately for the same purpose. Methods: Sixty-two MSA patients underwent a comprehensive II level neuropsychological evaluation, in order to diagnose dementia or MCI. ROC analyses were used to establish the optimal cut-off scores for MCI and dementia, respectively. Results: According to the II level neuropsychological evaluation, 4.8 % of MSA patients met criteria for dementia and 53,2 % for MCI. The optimal MMSE cut-off scores were 20.5 for dementia (AUC = 0.915) and 26.5 for MCI (AUC = 0.698). For MoCA, the most accurate cut-offs were 14.0 to detect dementia (AUC = 0.919) and 19.5 to detect MCI (AUC = 0.702).ROC analysis suggested that both tests were more accurate to identify MCI than dementia. The optimal cut-off for MoCA fluency item to identify MCI was 8.5 words (AUC = 0.717). Conclusion: Our findings support MMSE and MoCA as effective and accessible tools to detect MCI and dementia in MSA. MoCA fluency item emerged as a reliable tool to detect MCI.