Introduction: Cognitive impairment is a common complication of Parkinson's disease (PD) and identifying risk factors for progression to Parkinson's disease dementia (PDD) is important. However, little research has been done comparing the utility of commonly used cognitive screening tests in predicting cognitive progression in PD. Methods: We retrospectively reviewed data from patients with PD enrolled in the Pacific Udall Center who had baseline and longitudinal neuropsychological and global cognitive screening tests. The diagnostic accuracies of 3 common screening tests were compared: Montreal Cognitive Assessment (MoCA), Mattis Dementia Rating Scale (DRS-2), and Mini Mental Status Examination (MMSE). Cognitive diagnoses of PD with mild cognitive impairment (PD-MCI) and PDD were based on full neuropsychological testing and established Movement Disorder Society criteria. Logistic regression and Cox proportional hazards regression models were used to examine predictors of cognitive decline. Results: Four hundred seventy patients for whom scores on all 3 screening tests were available from the same assessment were included in a cross-sectional analysis. The MoCA demonstrated the best overall diagnostic accuracy for PD-MCI (AUC = 0.79, sensitivity = 76.4%) and for PDD (AUC = 0.89, sensitivity = 81.0%) compared to the DRS-2 and MMSE. A longitudinal analysis was performed on the subset of patients (316/470; 67.2%) who were nondemented at baseline and had undergone two or more assessments. After controlling for covariates, the MoCA was the only test associated with progression to PDD (OR = 1.27 95% CI 1.1–1.5, p = 0.001) and faster time to dementia (HR = 1.3, 95% CI 1.1–1.4, p < 0.0001). Conclusions: This study provides additional support for the use of the MoCA as a primary screening tool for cognitive impairment in PD and is the first to show that the MoCA is a predictor of conversion to PDD.
- Mild cognitive impairment
- Parkinson's disease
ASJC Scopus subject areas
- Clinical Neurology
- Cellular and Molecular Neuroscience