Predicting Cognitive Decline in Parkinson’s Disease with Mild Cognitive Impairment: A One-Year Observational Study

We conducted an observational study to investigate clinical predictors of cognitive decline in patients with mild cognitive impairment (MCI), with a focus on patients with Parkinson’s disease (PD) and Alzheimer’s disease (AD). The study was performed with detailed neuropsychological testing, a porta...

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Bibliographic Details
Main Authors: Pei-Hao Chen, Fang-Yu Cheng, Shih-Jung Cheng, Jin-Siang Shaw
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Parkinson's Disease
Online Access:http://dx.doi.org/10.1155/2020/8983960
Description
Summary:We conducted an observational study to investigate clinical predictors of cognitive decline in patients with mild cognitive impairment (MCI), with a focus on patients with Parkinson’s disease (PD) and Alzheimer’s disease (AD). The study was performed with detailed neuropsychological testing, a portable device for gait analysis, and a comprehensive geriatric assessment for patients with MCI. Cognitive decline was defined as subjective cognitive impairment with an objective decline in the Mini-Mental State Examination (MMSE) ≥2 points at the one-year follow-up. Participants (n = 74) had a median age of 70 (interquartile range 60–79) years, and 45.9% of them were women. At the end of the study, 17.6% of the patients with MCI had a cognitive decline. Although no differences were observed between groups at the baseline cognitive study, patients with PD-MCI demonstrated more cognitive decline than patients with AD-MCI (28.6% vs. 7.7% p = 0.03). Patients with PD-MCI had more physical disabilities, including scores of instrumental activities of daily living (IADL), Tinetti balance, and gait scores, and some Timed Up and Go components. Initial Clinical Dementia Rating—Sum of Boxes score was a better predictor of future cognitive decline than MMSE in PD-MCI. For predicting the occurrence of cognitive decline in PD-MCI, the prediction accuracy increased from the reduced model (AUC = 0.822, p<0.001) to the full model (a total of five independent variables, AUC = 0.974, p<0.001). Given the potentially modifiable predictor, our findings also highlight the importance of identifying sleep quality and the ability to perform IADL.
ISSN:2042-0080