Document Type

Article

Publication Date

9-16-2025

Publication Title

Clinical Parkinsonism and Related Disorders

Abstract

Background: Parkinson’s Disease (PD) can include physical signs and possibly cognitive impairment, resulting from the convergence of pathologicalprocesses involving dopaminergic dysfunction, accumulation ofalpha-synuclein, cholinergic deficits, and disruption of otherneurotransmitter systems. We used screening tests to evaluate thecharacteristics of cognitive performance in patients with PD and to assess their validity compared tothe Montreal Cognitive Assessment (MoCA). Methods: This is a natural history study of participants with PD and controls screened for possible cognitive impairment using the MoCA, Symbol Digit Modalities Test (SDMT), and King-Devick (KD). The groups were compared on performance and then factors associated with cognitive performance (age, diagnosis, and level of education) were analyzed to determine which best predicted test scores. Results: SDMT scores were lower in the PD group (Mean = 36.7 ± 12.4) compared to controls (Mean = 47.2 ± 11.0, p < 0.001), but the MoCA (PD = 23.8 ± 3.5; Control = 25.5 ± 3.6, p = 0.02) and KD (PD = 70.1 ± 23.4 s; Control = 61.6 ± 17.5, p = 0.048) did not differentiate between groups after controlling for multiple comparisons. Age and diagnosis predicted SDMT raw scores and, as expected, only diagnosis remained significant after calculating T-scores based on published test norms. Age, education, and diagnosis predicted MoCA scores. Conclusions: The SDMT emerged as a promising screening tool to detect cognitive impairment in PD. The test’s age and education corrected norms controlled for those variables and left diagnosis as the only predictor of performance. The MoCA scores were predicted by age, education, and diagnosis suggesting the education correction of the MoCA did not fully account for the influence of demographic variables.

PubMed ID

41049313

Volume

13

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Download

Share

COinS