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

Authors
  • Yu, Ya-Wen1
  • Tan, Chun-Hsiang2, 3
  • Su, Hui-Chen4
  • Chien, Chung-Yao4
  • Sung, Pi-Shan4
  • Lin, Tien-Yu4
  • Lee, Tsung-Lin4
  • Yu, Rwei-Ling1
  • 1 Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan City
  • 2 Department of Neurology, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung City
  • 3 Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung City
  • 4 Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan City
Type
Published Article
Journal
Frontiers in Aging Neuroscience
Publisher
Frontiers Media SA
Publication Date
Jun 16, 2022
Volume
14
Identifiers
DOI: 10.3389/fnagi.2022.913958
Source
Frontiers
Keywords
Disciplines
  • Neuroscience
  • Original Research
License
Green

Abstract

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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