4.6 Article

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

期刊

FRONTIERS IN AGING NEUROSCIENCE
卷 14, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fnagi.2022.913958

关键词

dementia; Montreal Cognitive Assessment; social functioning; Parkinson's disease; mild cognitive impairment

资金

  1. Higher Education Sprout Project, Ministry of Education
  2. Ministry of Science and Technology (MOST), Taipei, Taiwan [MOST 110-2628-B-006-020]

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The study aimed to simplify commonly used tools and combine cognitive and social functioning tests to detect early MCI and PDD. According to MDS diagnostic criteria, patients were grouped into PD nonMCI, PD-MCI, or PDD.
BackgroundThe 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). ObjectiveWe aimed to simplify the commonly used tools and combine cognitive and social functioning tests to detect early MCI and PDD. Materials and MethodsA 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. ResultsTo 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). ConclusionWe suggest considering both cognitive and social functions when detecting PD-MCI and PDD.

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