A New Instrument Combines Cognitive and Social Functioning Items for Detecting Mild Cognitive Impairment and Dementia in Parkinson’s Disease

Ya Wen Yu, Chun Hsiang Tan, Hui Chen Su, Chung Yao Chien, Pi Shan Sung, Tien Yu Lin, Tsung Lin Lee, Rwei Ling Yu

研究成果: Article同行評審

5 引文 斯高帕斯(Scopus)

摘要

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.

原文English
文章編號913958
期刊Frontiers in Aging Neuroscience
14
DOIs
出版狀態Published - 2022 6月 16

All Science Journal Classification (ASJC) codes

  • 老化
  • 認知神經科學

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