MoCa predictive power in neuropsychological assessment of patients with dementia

This study aimed to correlate neuropsicometric tests in elderly over 4 years of schooling and assess MoCA accuracy in diagnosing Alzheimer's disease and mild cognitive impairment (MCI). It evaluated 136 elderly patients treated at the Institute of Geriatrics and Gerontology, from April 2010 to December 2012. The instruments used were the Mini-Mental State Examination (MMSE), Cambridge Cognitive Examination (CAMCOG), Clock Drawing Test (CDT), Verbal Fluency test, Geriatric Depression Scale, Pfeffer Functional Activities Questionnaire (PFAQ), and Montreal Cognitive Assessement (MoCA). ROC curve analysis was used to establish cutoffs and the Pearson correlation coefficient to compare the MoCA with the other tests. The results showed that the MoCA was the best test to differentiate Alzheimer's disease from MCI. The sensitivity and specificity found were 82.2% and 92.3%, respectively. The analysis of the correlation test showed that MoCA is strongly correlated with other tests already validated and wide applied in Brazil. The MoCA test showed the greatest predictive value to differentiate AD from MCI and also differ MCI from normal controls. Furthermore, MoCA was significantly correlated with the age variable and MMSE, CAMCOG, CDT, Verbal Fluency and PFAQ tests, instruments that are already validated and widely used in Brazil.