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1.
Article in English | WPRIM | ID: wpr-1043835

ABSTRACT

Objective@#The Montreal Cognitive Assessment (MoCA) is recommended for general cognitive evaluation in Parkinson’s disease (PD) patients. However, age- and education-adjusted cutoffs specifically for PD have not been developed or systematically validated across PD cohorts with diverse education levels. @*Methods@#In this retrospective analysis, we utilized data from 1,293 Korean patients with PD whose cognitive diagnoses were determined through comprehensive neuropsychological assessments. Age- and education-adjusted cutoffs were formulated based on 1,202 patients with PD. To identify the optimal machine learning model, clinical parameters and MoCA domain scores from 416 patients with PD were used. Comparative analyses between machine learning methods and different cutoff criteria were conducted on an additional 91 consecutive patients with PD. @*Results@#The cutoffs for cognitive impairment decrease with increasing age within the same education level. Similarly, lower education levels within the same age group correspond to lower cutoffs. For individuals aged 60–80 years, cutoffs were set as follows: 25 or 24 years for those with more than 12 years of education, 23 or 22 years for 10–12 years, and 21 or 20 years for 7–9 years. Comparisons between age- and education-adjusted cutoffs and the machine learning method showed comparable accuracies. The cutoff method resulted in a higher sensitivity (0.8627), whereas machine learning yielded higher specificity (0.8250). @*Conclusion@#Both the age- and education-adjusted cutoff methods and machine learning methods demonstrated high effectiveness in detecting cognitive impairment in PD patients. This study highlights the necessity of tailored cutoffs and suggests the potential of machine learning to improve cognitive assessment in PD patients.

2.
Article in English | WPRIM | ID: wpr-1000851

ABSTRACT

Background@#and Purpose This study aimed to determine the neuropsychological differences between patients with early-stage Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB) with a Clinical Dementia Rating (CDR) score of ≤1. @*Methods@#We examined 168 patients with AD (126 with CDR score=0.5, 42 with CDR score=1) and 169 patients with DLB (104 with CDR score=0.5, 65 with CDR score=1) whose diagnoses were supported by 18F-flobetaben positron-emission tomography (PET) and 18F-N-(3-fluoropropyl)-2β-carbon ethoxy-3β-(4-iodophenyl) nortropane PET. Neuropsychological test scores were compared after controlling for age, sex, and education duration. Using a cutoff motor score on the Unified Parkinson’s Disease Rating Scale of 20, patients with AD were further divided into AD with parkinsonism (ADP+ , n=86) and AD without parkinsonism (ADP− , n=82). @*Results@#At CDR scores of both 0.5 and 1, the DLB group had lower scores on the attention (digit-span forward at CDR score=0.5 and backward at CDR score=1), visuospatial, and executive (color reading Stroop test at CDR score=0.5 and phonemic fluency test, Stroop tests, and digit symbol coding at CDR score=1) tests than the AD group, but higher scores on the memory tests. The ADP− and ADP+ subgroups had comparable scores on most neuropsychological tests, but the ADP+ subgroup had lower scores on the color reading Stroop test. @*Conclusions@#Patients with DLB had worse attention, visuospatial, and executive functions but better memory function than patients with AD. Parkinsonism was not uncommon in the patients with AD and could be related to attention and executive dysfunction.

3.
Article in Korean | WPRIM | ID: wpr-1001730

ABSTRACT

A 35-year-old male presented with atypical aphasia following left anterior choroidal artery infarction associated with distal internal carotid artery dissection. He presented with 1) lexical-semantic deficit without semantic impairment, 2) frequent surface errors (both surface dyslexia and dysgraphia), and 3) intact non-word reading/repetition (preserved sub-lexical route), suggesting deficit in the phonological output lexicon. Diffusion-tensor tractography analysis revealed disruption in the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus, which might serve as potential subcortical neural correlates for phonological output lexicon.

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