Literature DB >> 32651296

Factor analysis-derived cognitive profile predicting early dementia conversion in PD.

Seok Jong Chung1,2, Hye Sun Lee3, Hang-Rai Kim4,5, Han Soo Yoo1, Yang Hyun Lee1, Jin Ho Jung1, KyoungWon Baik1, Byoung Seok Ye1, Young H Sohn1, Phil Hyu Lee6,7.   

Abstract

OBJECTIVES: To investigate which baseline neuropsychological profile predicts the risk of developing dementia in early-stage Parkinson's disease (PD).
METHODS: We retrospectively reviewed detailed medical records of 350 drug-naïve patients with early-stage PD (follow-up > 3 years), who underwent a detailed neuropsychological test at initial assessment. Factor analysis was conducted to determine cognitive profiles which yielded four cognitive function factors: Factor 1 (visual memory/visuospatial), Factor 2 (verbal memory), Factor 3 (frontal/executive), and Factor 4 (attention/working memory/language). Subsequently, we assessed the effect of these cognitive function factors on the risk for dementia conversion. We also constructed a nomogram to calculate the risk for developing dementia over a 5-year follow-up period based on these cognitive profiles.
RESULTS: Cox regression analysis demonstrated that a higher composite score of Factor 1 (hazard ratio [HR], 0.558; 95% confidence interval [CI], 0.427-0.730), Factor 2 (HR, 0.768; 95% CI, 0.596-0.991), and Factor 3 (HR, 0.425; 95% CI, 0.305-0.593) was associated with a lower risk for dementia conversion, while Factor 3 had the most predictive power. The nomogram had a fair ability (Heagerty's integrated area under the curve, 0.763) to estimate the risk for dementia conversion within 5 years. The composite scores of Factor 3 contributed more to the occurrence of dementia in PD than those of the other cognitive function factors.
CONCLUSIONS: These findings suggest that these factor analysis-derived cognitive profiles can be used to predict dementia conversion in early-stage PD. Additionally, frontal/executive dysfunction contributes most to the occurrence of dementia in PD.
© 2020 American Academy of Neurology.

Entities:  

Year:  2020        PMID: 32651296     DOI: 10.1212/WNL.0000000000010347

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  5 in total

1.  Baseline cognitive profile is closely associated with long-term motor prognosis in newly diagnosed Parkinson's disease.

Authors:  Seok Jong Chung; Han Soo Yoo; Hye Sun Lee; Yang Hyun Lee; KyoungWon Baik; Jin Ho Jung; Byoung Seok Ye; Young H Sohn; Phil Hyu Lee
Journal:  J Neurol       Date:  2021-05-04       Impact factor: 4.849

Review 2.  Parkinson disease-associated cognitive impairment.

Authors:  Dag Aarsland; Lucia Batzu; Glenda M Halliday; Gert J Geurtsen; Clive Ballard; K Ray Chaudhuri; Daniel Weintraub
Journal:  Nat Rev Dis Primers       Date:  2021-07-01       Impact factor: 52.329

3.  Internetwork Connectivity Predicts Cognitive Decline in Parkinson's and Is Altered by Genetic Variants.

Authors:  Xiangyu Wei; Qian Shen; Irene Litvan; Mingxiong Huang; Roland R Lee; Deborah L Harrington
Journal:  Front Aging Neurosci       Date:  2022-03-28       Impact factor: 5.750

4.  Metabolite changes in prefrontal lobes and the anterior cingulate cortex correlate with processing speed and executive function in Parkinson disease patients.

Authors:  Chentao He; Siming Rong; Piao Zhang; Ruitao Li; Xiaohong Li; Yan Li; Lijuan Wang; Yuhu Zhang
Journal:  Quant Imaging Med Surg       Date:  2022-08

5.  Application of the Chinese Version of the Montreal Cognitive Assessment-Basic for Assessing Mild Cognitive Impairment in Parkinson's Disease.

Authors:  Qian Xu; Mengxi Zhou; Chunyan Jiang; Li Wu; Qing He; Lei Zhao; Yourong Dong; Jianren Liu; Wei Chen
Journal:  Brain Sci       Date:  2021-11-28
  5 in total

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