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|Title:||Cognitive profiles and optimal cut-offs for routine cognitive tests in elderly individuals with Parkinson's disease, Parkinson's disease dementia, Alzheimer's disease, and normal cognition|
Faculty of Medicine, Siriraj Hospital, Mahidol University
|Citation:||Psychogeriatrics. Vol.20, No.1 (2020), 20-27|
|Abstract:||© 2019 Japanese Psychogeriatric Society Aim: The cognitive impairment seen in Parkinson's disease (PD) results in patient disability and reduced quality of life. However, using cognitive screening scales specific to PD in routine clinical practice is difficult because of limited time, resources, and skills. We studied the ability of routine cognitive tests to differentiate between Parkinson's disease dementia (PDD) and PD and among the neuropsychological profiles of elderly individuals with PD, PDD, Alzheimer's disease (AD), and normal cognition. Methods: This cross-sectional study involved 124 subjects. Subjects were 35 cognitively normal elderly and 37 elderly individuals with PD, 22 with PDD, and 30 with AD. All subjects were diagnosed by a specialist using standard criteria. Clinically relevant data and scores from the Montreal Cognitive Assessment and the Thai Mental State Examination were collected. Cognitive test scores were compared among groups. Receiver operating characteristic curves were constructed for a range of cut-off points to explore the sensitivity and specificity of the screening tools to detect PDD. Results: There were 74 female subjects (59.7%), and the average age of all subjects was 75.6 years. The median score on the modified Hoehn and Yahr scale was 2.5 in subjects with PD and 4 in those with PDD (P < 0.001). The cut-offs for differentiating PDD from PD were 25 on the Thai Mental State Examination and 14 on the Montreal Cognitive Assessment. The sensitivity of the Thai Mental State Examination was 78.4%, and the specificity was 66.7% (area under the curve: 0.828). The sensitivity of the Montreal Cognitive Assessment was 81.1%, and the specificity was 75% (area under the curve: 0.876). There was a significant difference in the memory and language subdomains between AD and PDD (P < 0.05). Conclusions: The cut-offs used to differentiate PDD from PD were not the same as routine cut-offs in distinguishing AD from normal elderly. The cognitive profile deficit in PDD differed from that in AD. Interpretations of positive screenings test should take this finding into consideration.|
|Appears in Collections:||Scopus 2020|
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