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Review Article
Subjective Cognitive Complaints in Cognitively Normal Patients With Parkinson’s Disease: A Systematic Review
Jin Yong Hong, Phil Hyu Lee
J Mov Disord. 2023;16(1):1-12.   Published online November 10, 2022
  • 3,872 View
  • 332 Download
  • 7 Web of Science
  • 9 Crossref
AbstractAbstract PDF
Subjective cognitive complaints (SCCs) refer to self-perceived cognitive decline and are related to objective cognitive decline. SCCs in cognitively normal individuals are considered a preclinical sign of subsequent cognitive impairment due to Alzheimer’s disease, and SCCs in cognitively normal patients with Parkinson’s disease (PD) are also gaining attention. The aim of this review was to provide an overview of the current research on SCCs in cognitively normal patients with PD. A systematic search found a lack of consistency in the methodologies used to define and measure SCCs. Although the association between SCCs and objective cognitive performance in cognitively normal patients with PD is controversial, SCCs appear to be predictive of subsequent cognitive decline. These findings support the clinical value of SCCs in cognitively normal status in PD; however, further convincing evidence from biomarker studies is needed to provide a pathophysiological basis for these findings. Additionally, a consensus on the definition and assessment of SCCs is needed for further investigations.


Citations to this article as recorded by  
  • Daily Emotional Experiences in Persons with Parkinson Disease: Relations to Subjective Cognitive Complaints and Quality of Life
    Karen R. Hebert, Mackenzie Feldhacker
    Physical & Occupational Therapy In Geriatrics.2024; 42(3): 228.     CrossRef
  • Subjective Cognitive Complaints in Parkinson's Disease: A Systematic Review and Meta‐Analysis
    Mattia Siciliano, Alessandro Tessitore, Francesca Morgante, Jennifer G. Goldman, Lucia Ricciardi
    Movement Disorders.2024; 39(1): 17.     CrossRef
  • Mild cognitive impairment in Parkinson's disease: current view
    Kurt A. Jellinger
    Frontiers in Cognition.2024;[Epub]     CrossRef
  • Neurocognitive Impairment and Social Cognition in Parkinson’s Disease Patients
    Triantafyllos Doskas, Konstantinos Vadikolias, Konstantinos Ntoskas, George D. Vavougios, Dimitrios Tsiptsios, Polyxeni Stamati, Ioannis Liampas, Vasileios Siokas, Lambros Messinis, Grigorios Nasios, Efthimios Dardiotis
    Neurology International.2024; 16(2): 432.     CrossRef
  • Cognitive disorders in Parkinson's disease
    Victor Kholin, Iryna Karaban, Sergiy Kryzhanovskiy, Nina Karasevich, Natalia Melnik, Maryna Khodakovska, Hanna Shershanova, Natalia Movchun
    Ageing & Longevity.2024; (2 2024): 51.     CrossRef
  • Unveiling the role of subjective cognitive complaints in predicting cognitive impairment in Parkinson´s Disease– A longitudinal study with 4 year of follow up
    Marta Magriço, Bruna Meira, Marco Fernandes, Manuel Salavisa, Marlene Saraiva, Cláudia Borbinha, João Pedro Marto, Raquel Barbosa, Paulo Bugalho
    Neurological Sciences.2024;[Epub]     CrossRef
  • Association of Neuropsychiatric Symptom Profiles With Cognitive Decline in Patients With Parkinson Disease and Mild Cognitive Impairment
    Young-gun Lee, Mincheol Park, Seong Ho Jeong, Kyoungwon Baik, Sungwoo Kang, So Hoon Yoon, Han Kyu Na, Young H. Sohn, Phil Hyu Lee
    Neurology.2023;[Epub]     CrossRef
  • Subjective cognitive complaints in patients with progressive supranuclear palsy
    Jun Seok Lee, Jong Hyeon Ahn, Jong Mok Ha, Jinyoung Youn, Jin Whan Cho
    Frontiers in Neurology.2023;[Epub]     CrossRef
  • Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks
    Kurt A. Jellinger
    International Journal of Molecular Sciences.2023; 25(1): 498.     CrossRef
Original Articles
Accuracy of Machine Learning Using the Montreal Cognitive Assessment for the Diagnosis of Cognitive Impairment in Parkinson’s Disease
Junbeom Jeon, Kiyong Kim, Kyeongmin Baek, Seok Jong Chung, Jeehee Yoon, Yun Joong Kim
J Mov Disord. 2022;15(2):132-139.   Published online May 26, 2022
  • 3,509 View
  • 140 Download
  • 2 Web of Science
  • 2 Crossref
AbstractAbstract PDFSupplementary Material
The Montreal Cognitive Assessment (MoCA) is recommended for assessing general cognition in Parkinson’s disease (PD). Several cutoffs of MoCA scores for diagnosing PD with cognitive impairment (PD-CI) have been proposed, with varying sensitivity and specificity. This study investigated the utility of machine learning algorithms using MoCA cognitive domain scores for improving diagnostic performance for PD-CI.
In total, 2,069 MoCA results were obtained from 397 patients with PD enrolled in the Parkinson’s Progression Markers Initiative database with a diagnosis of cognitive status based on comprehensive neuropsychological assessments. Using the same number of MoCA results randomly sampled from patients with PD with normal cognition or PD-CI, discriminant validity was compared between machine learning (logistic regression, support vector machine, or random forest) with domain scores and a cutoff method.
Based on cognitive status classification using a dataset that permitted sampling of MoCA results from the same individual (n = 221 per group), no difference was observed in accuracy between the cutoff value method (0.74 ± 0.03) and machine learning (0.78 ± 0.03). Using a more stringent dataset that excluded MoCA results (n = 101 per group) from the same patients, the accuracy of the cutoff method (0.66 ± 0.05), but not that of machine learning (0.74 ± 0.07), was significantly reduced. Inclusion of cognitive complaints as an additional variable improved the accuracy of classification using the machine learning method (0.87–0.89).
Machine learning analysis using MoCA domain scores is a valid method for screening cognitive impairment in PD.


Citations to this article as recorded by  
  • Comparing Montreal Cognitive Assessment Performance in Parkinson’s Disease Patients: Age- and Education-Adjusted Cutoffs vs. Machine Learning
    Kyeongmin Baek, Young Min Kim, Han Kyu Na, Junki Lee, Dong Ho Shin, Seok-Jae Heo, Seok Jong Chung, Kiyong Kim, Phil Hyu Lee, Young H. Sohn, Jeehee Yoon, Yun Joong Kim
    Journal of Movement Disorders.2024; 17(2): 171.     CrossRef
  • Machine learning for the detection and diagnosis of cognitive impairment in Parkinson’s Disease: A systematic review
    Callum Altham, Huaizhong Zhang, Ella Pereira, Farzin Hajebrahimi
    PLOS ONE.2024; 19(5): e0303644.     CrossRef
Constipation is Associated With Mild Cognitive Impairment in Patients With de novo Parkinson’s Disease
Sung Hoon Kang, Jungyeun Lee, Seong-Beom Koh
J Mov Disord. 2022;15(1):38-42.   Published online November 17, 2021
  • 4,544 View
  • 321 Download
  • 2 Web of Science
  • 3 Crossref
AbstractAbstract PDF
The association between gastrointestinal (GI) symptoms and cognitive profile in patients with Parkinson’s disease (PD) at diagnosis remains unclear, although GI symptoms and cognitive impairment are highly prevalent in patients with PD. We investigated the relationship between constipation and cognitive status. We also aimed to identify the correlation between constipation and each neuropsychological dysfunction.
A total of 427 patients with de novo Parkinson’s disease with normal cognition (PD-NC, n = 170) and Parkinson’s disease with mild cognitive impairment (PD-MCI, n = 257) at Korea University Guro Hospital in Seoul, Korea were included. All patients underwent comprehensive neuropsychological tests and completed the Non-Motor Symptoms Scale (NMSS). The frequency and severity of constipation were assessed using the NMSS GI symptoms scale, we used logistic regression analysis and partial correlation analysis to determine the associations between constipation score, MCI, and each neuropsychological dysfunction.
Frequent and severe constipation was associated with MCI in patients with PD at diagnosis regardless of disease severity. Specifically, constipation was related to poor performance in frontal-executive and visuospatial functions after controlling for age and sex.
Our findings may provide an understanding of constipation as a marker associated with cognitive impairment in individuals with PD. Therefore, the evaluation of cognitive function is warranted in PD patients with constipation, while further studies are necessary to investigate the detailed mechanism of our results.


Citations to this article as recorded by  
  • Defecation after magnesium supplementation enhances cognitive performance in triathletes
    Chen-Chan Wei, M. Brennan Harris, Mengxin Ye, Andrew Nicholls, Ahmad Alkhatib, Luthfia Dewi, Chi-Yang Huang, Chia-Hua Kuo
    Sports Medicine and Health Science.2024;[Epub]     CrossRef
  • Constipation in Parkinson's Disease
    Eamonn M. M. Quigley
    Seminars in Neurology.2023; 43(04): 562.     CrossRef
  • Interactions between gut microbiota and Parkinson's disease: The role of microbiota-derived amino acid metabolism
    Wang Wang, Shujun Jiang, Chengcheng Xu, Lili Tang, Yan Liang, Yang Zhao, Guoxue Zhu
    Frontiers in Aging Neuroscience.2022;[Epub]     CrossRef
The MMSE and MoCA for Screening Cognitive Impairment in Less Educated Patients with Parkinson’s Disease
Ji In Kim, Mun Kyung Sunwoo, Young H. Sohn, Phil Hyu Lee, Jin Y. Hong
J Mov Disord. 2016;9(3):152-159.   Published online September 21, 2016
  • 21,266 View
  • 410 Download
  • 38 Web of Science
  • 38 Crossref
AbstractAbstract PDF
To explore whether the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) can be used to screen for dementia or mild cognitive impairment (MCI) in less educated patients with Parkinson’s disease (PD).
We reviewed the medical records of PD patients who had taken the Korean MMSE (K-MMSE), Korean MoCA (K-MoCA), and comprehensive neuropsychological tests. Predictive values of the K-MMSE and K-MoCA for dementia or MCI were analyzed in groups divided by educational level.
The discriminative powers of the K-MMSE and K-MoCA were excellent [area under the curve (AUC) 0.86–0.97] for detecting dementia but not for detecting MCI (AUC 0.64–0.85). The optimal screening cutoff values of both tests increased with educational level for dementia (K-MMSE < 15 for illiterate, < 20 for 0.5–3 years of education, < 23 for 4–6 years, < 25 for 7–9 years, and < 26 for 10 years or more; K-MoCA < 7 for illiterate, < 13 for 0.5–3 years, < 16 for 4–6 years, < 19 for 7–9 years, < 20 for 10 years or more) and MCI (K-MMSE < 19 for illiterate, < 26 for 0.5–3 years, < 27 for 4–6 years, < 28 for 7–9 years, and < 29 for 10 years or more; K-MoCA < 13 for illiterate, < 21 for 0.5–3 years, < 23 for 4–6 years, < 25 for 7–9 years, < 26 for 10 years or more).
Both MMSE and MoCA can be used to screen for dementia in patients with PD, regardless of educational level; however, neither test is sufficient to discriminate MCI from normal cognition without additional information.


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    npj Parkinson's Disease.2024;[Epub]     CrossRef
  • Influence of cognitive reserve on cognitive and motor function in α-synucleinopathies: A systematic review and multilevel meta-analysis
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    Neuroscience & Biobehavioral Reviews.2024; 161: 105672.     CrossRef
  • Comparing Montreal Cognitive Assessment Performance in Parkinson’s Disease Patients: Age- and Education-Adjusted Cutoffs vs. Machine Learning
    Kyeongmin Baek, Young Min Kim, Han Kyu Na, Junki Lee, Dong Ho Shin, Seok-Jae Heo, Seok Jong Chung, Kiyong Kim, Phil Hyu Lee, Young H. Sohn, Jeehee Yoon, Yun Joong Kim
    Journal of Movement Disorders.2024; 17(2): 171.     CrossRef
  • Comparison of mini nutritional assessment tool and geriatric nutrition risk index in predicting 12-year mortality among community-dwelling older persons
    Tsai-Chung Li, Chia-Ing Li, Chiu-Shong Liu, Chih-Hsueh Lin, Shing-Yu Yang, Cheng-Chieh Lin
    The Journal of Nutrition.2024;[Epub]     CrossRef
  • Association between executive and physical functions in people with Parkinson’s disease
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    Somatosensory & Motor Research.2023; : 1.     CrossRef
  • Effect of Education on Discriminability of Montreal Cognitive Assessment Compared to Mini-Mental State Examination
    Haeyoon Kim, Seonyeong Yang, Jaesel Park, Byeong Chae Kim, Kyung-Ho Yu, Yeonwook Kang
    Dementia and Neurocognitive Disorders.2023; 22(2): 69.     CrossRef
  • Altered connectivity in the cognitive control-related prefrontal cortex in Parkinson’s disease with rapid eye movement sleep behavior disorder
    Jinjing Liu, Xiaoya Zou, Jinming Gu, Qian Yu, Zhaoying Dong, Hongzhou Zuo, Xiaocui Chen, Xinyi Du, Dezhi Zou, Yu Han, Juan Peng, Oumei Cheng
    Brain Imaging and Behavior.2023; 17(6): 702.     CrossRef
  • Resting-state electroencephalographic characteristics related to mild cognitive impairments
    Seong-Eun Kim, Chanwoo Shin, Junyeop Yim, Kyoungwon Seo, Hokyoung Ryu, Hojin Choi, Jinseok Park, Byoung-Kyong Min
    Frontiers in Psychiatry.2023;[Epub]     CrossRef
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    Brain Sciences.2022; 12(2): 165.     CrossRef
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    Frontiers in Neurology.2022;[Epub]     CrossRef
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    Journal of Movement Disorders.2022; 15(2): 132.     CrossRef
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    Movement Disorders.2022; 37(12): 2355.     CrossRef
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    Psychogeriatrics.2021; 21(1): 24.     CrossRef
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Mild Cognitive Impairment in Parkinson’s Disease
Jae Woo Kim, Hee Young Jo, Min Jeong Park, Sang-Myung Cheon
J Mov Disord. 2008;1(1):19-25.
  • 9,635 View
  • 94 Download
  • 8 Web of Science
  • 6 Crossref
AbstractAbstract PDF

To determine the frequency of mild cognitive impairment (MCI) of Parkinson’s disease (PD, PDMCI) and its subtypes among non-demented PD patients, and to identify the influence of the age and presenting symptom on the development of PDMCI.


A total 141 non-demented PD patients underwent a comprehensive neuropsychological assessment including attention, language, visuospatial, memory and frontal functions. PDMCI was defined by neuropsychological testing and was classified into five subtypes. Patients were divided into two groups (tremor vs. akinetic-rigid type) for presenting symptom and three groups according to the age. Neuropsychological performance of patients was compared with normative data.


Almost half (49.6%) of non-demented PD patients had impairment in at least one domain and can be considered as having PDMCI. Executive type of PDMCI was the most frequent and amnestic, visuospatial, linguistic and attention types followed in the order of frequency. The population of PDMCI was increasing as the age of disease onset was higher. Whereas the frequency of executive and amnestic types of PDMCI was comparable in younger group, executive type was the most frequent in older group. The patients with tremor dominant type performed worse on tests, particularly on attention test.


MCI was common even in the early stage of PD and the subtype was diverse. Unlike MCI developing Alzheimer’s disease later, executive type of PDMCI was the most common. Age was an important risk factor for development of MCI in PD. The concept of MCI should be introduced in PD.


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