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Updated: Sep 5, 2025

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
Published on: July 24, 2019
A New Instrument Combines Cognitive and Social Functioning Items for Detecting Mild Cognitive Impairment and Dementia
Ya-Wen Yu1, Chun-Hsiang Tan2,3, Hui-Chen Su4
1Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan City, Taiwan.
Background:
The commonly used screening tests for Parkinson's disease (PD) are the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE), both of which only focus on cognitive function. A composite assessment that considers both cognitive and social dysfunction in PD would be helpful in detecting mild cognitive impairment (MCI) and PD dementia (PDD).
Objective:
We aimed to simplify the commonly used tools and combine cognitive and social functioning tests to detect early MCI and PDD.
Materials And Methods:
A total of 166 participants (84 PD patients and 82 healthy) were recruited who completed the MMSE, MoCA, PD social functioning scale (PDSFS), clock drawing test, activities of daily living, comprehensive neuropsychological assessment (e.g., executive, attention, language, memory, and visuospatial functions), and movement disorder society (MDS)-unified PD rating scale. According to the MDS diagnostic criteria, the patients were grouped into PD-nonMCI, PD-MCI, or PDD.
Results:
To detect PD-MCI, the optimal cut-off scores for the simplified MoCA and the combined test were 9 and 35. The discrimination values measured by the area under the receiver operating characteristic curve (AUC) of the two tests were 0.767 (p < 0.001) and 0.790 (p < 0.001). When the simplified MoCA was 7 or the combined test 30, the patients would be classified as having PDD. The AUCs of the two tests were 0.846 (p < 0.001) and 0.794 (p = 0.003).
Conclusion:
We suggest considering both cognitive and social functions when detecting PD-MCI and PDD.
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