Montreal Cognitive Assessment Performance in Patients with Parkinson's Disease with “Normal” Global Cognition According to Mini‐Mental State Examination Score
- 28 January 2009
- journal article
- research article
- Published by Wiley in Journal of the American Geriatrics Society
- Vol. 57 (2), 304-308
- https://doi.org/10.1111/j.1532-5415.2008.02096.x
Abstract
OBJECTIVES: To examine Montreal Cognitive Assessment (MoCA) performance in patients with Parkinson's disease (PD) with “normal” global cognition according to Mini‐Mental State Examination (MMSE) score. DESIGN: A cross‐sectional comparison of the MoCA and the MMSE. SETTING: Two movement disorders centers at the University of Pennsylvania and the Philadelphia Veterans Affairs Medical Center. PARTICIPANTS: A convenience sample of 131 patients with idiopathic PD who were screened for cognitive and psychiatric complications. MEASUREMENTS: Subjects were administered the MoCA and MMSE, and only subjects defined as having a normal age‐ and education‐adjusted MMSE score were included in the analyses (N=100). As previously recommended in patients without PD, a MoCA score less than 26 was used to indicate the presence of at least mild cognitive impairment (MCI). RESULTS: Mean MMSE and MoCA scores±standard deviation were 28.8±1.1 and 24.9±3.1, respectively. More than half (52.0%) of subjects with normal MMSE scores had cognitive impairment according to their MoCA score. Impairments were seen in numerous cognitive domains, including memory, visuospatial and executive abilities, attention, and language. Predictors of cognitive impairment on the MoCA using univariate analyses were male sex, older age, lower educational level, and greater disease severity; older age was the only predictor in a multivariate model. CONCLUSION: Approximately half of patients with PD with a normal MMSE score have cognitive impairment based on the recommended MoCA cutoff score. These results suggest that MCI is common in PD and that the MoCA is a more sensitive instrument than the MMSE for its detection.Keywords
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