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JMD : Journal of Movement Disorders

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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
DOI: https://doi.org/10.14802/jmd.22012
  • 629 View
  • 67 Download
AbstractAbstract PDFSupplementary Material
Objective
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.
Methods
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.
Results
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).
Conclusion
Machine learning analysis using MoCA domain scores is a valid method for screening cognitive impairment in PD.
Validation of the Conversion between the Mini-Mental State Examination and Montreal Cognitive assessment in Korean Patients with Parkinson’s Disease
Ryul Kim, Han-Joon Kim, Aryun Kim, Mi-Hee Jang, Hyun Jeong Kim, Beomseok Jeon
J Mov Disord. 2018;11(1):30-34.   Published online January 11, 2018
DOI: https://doi.org/10.14802/jmd.17038
  • 6,891 View
  • 231 Download
  • 13 Citations
AbstractAbstract PDF
Objective
Two conversion tables between the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) have recently been established for Parkinson’s disease (PD). This study aimed to validate them in Korean patients with PD and to evaluate whether they could be influenced by educational level.
Methods
A total of 391 patients with PD who undertook both the Korean MMSE and the Korean MoCA during the same session were retrospectively assessed. The mean, median, and root mean squared error (RMSE) of the difference between the true and converted MMSE scores and the intraclass correlation coefficient (ICC) were calculated according to educational level (6 or fewer years, 7–12 years, or 13 or more years).
Results
Both conversions had a median value of 0, with a small mean and RMSE of differences, and a high correlation between the true and converted MMSE scores. In the classification according to educational level, all groups had roughly similar values of the median, mean, RMSE, and ICC both within and between the conversions.
Conclusion
Our findings suggest that both MMSE-MoCA conversion tables are useful instruments for transforming MoCA scores into converted MMSE scores in Korean patients with PD, regardless of educational level. These will greatly enhance the utility of the existing cognitive data from the Korean PD population in clinical and research settings.
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
DOI: https://doi.org/10.14802/jmd.16020
  • 16,440 View
  • 353 Download
  • 27 Citations
AbstractAbstract PDF
Objective
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).
Methods
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.
Results
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).
Conclusion
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.
Review Articles
Gastrointestinal Autonomic Dysfunction in Patients with Parkinson’s Disease
Joong-Seok Kim, Hye-Young Sung
J Mov Disord. 2015;8(2):76-82.   Published online May 31, 2015
DOI: https://doi.org/10.14802/jmd.15008
  • 38,463 View
  • 246 Download
  • 33 Citations
AbstractAbstract PDF
Currently, gastrointestinal dysfunctions in Parkinson’s disease (PD) are well-recognized problems and are known to be an initial symptom in the pathological process that eventually results in PD. Gastrointestinal symptoms may result from the involvement of either the central or enteric nervous systems, or these symptoms may be side effects of antiparkinsonian medications. Weight loss, excessive salivation, dysphagia, nausea/gastroparesis, constipation, and defecation dysfunction all may occur. Increased identification and early detection of these symptoms can result in a significant improvement in the quality of life for PD patients.
Electrophysiologic Assessments of Involuntary Movements: Tremor and Myoclonus
Hyun-Dong Park, Hee-Tae Kim
J Mov Disord. 2009;2(1):14-17.
DOI: https://doi.org/10.14802/jmd.09004
  • 10,631 View
  • 165 Download
  • 3 Citations
AbstractAbstract PDF

Tremor is defined as a rhythmical, involuntary oscillatory movement of a body part. Although neurological examination reveals information regarding its frequency, regularity, amplitude, and activation conditions, the electrophysiological investigations help in confirming the tremor, in differentiating it from other hyperkinetic disorders like myoclonus, and may provide etiological clues. Accelerometer with surface electromyogram (EMG) can be used to document the dominant frequency of a tremor, which may be useful as certain frequencies are more characteristic of specific etiologies than others hyperkinetic disorders. It may show rhythmic bursts, duration and activation pattern (alternating or synchronous). Myoclonus is a quick, involuntary movement. Electrophysiological studies may helpful in the evaluation of myoclonus, not only for confirming the clinical diagnosis but also for understanding the underlying physiological mechanisms. Electroencephalogram (EEG)-EMG correlates can give us important information about myoclonus. Jerk-locked back-averaging and evoked potentials with recording of the long-latency, long-loop reflexes are currently available to study the pathophysiology of myoclonus.


JMD : Journal of Movement Disorders