Dementia Risk Prediction in a Longitudinal Geriatric Parkinson’s Disease Cohort: Evaluation and Application of the Montreal Parkinson Risk of Dementia Scale

Author:

Bohn Linzy,McFall G. Peggy,Gee Myrlene,Postuma Ronald B.,Dixon Roger A.,Camicioli Richard

Abstract

Background Parkinson’s disease (PD) increases risk for dementia and cascading adverse outcomes. The eight-item Montreal Parkinson Risk of Dementia Scale (MoPaRDS) is a rapid, in-office dementia screening tool. We examine predictive validity and other characteristics of the MoPaRDS in a geriatric PD cohort by testing a series of alternative versions and modelling risk score change trajectories. Methods Participants were 48 initially non-demented PD patients (Mage = 71.6 years, range = 65–84) from a three-year, three-wave prospective Canadian cohort study. A dementia diagnosis at Wave 3 was used to stratify two baseline groups: PD with Incipient Dementia (PDID) and PD with No Dementia (PDND). We aimed to predict dementia three years prior to diagnosis using baseline data for eight indicators that harmon-ized with the original report, plus education. Results Three MoPaRDS items (age, orthostatic hypotension, mild cognitive impairment [MCI]) discriminated the groups both independently and as a composite three-item scale (area under the curve [AUC] = 0.88). The eight-item MoPaRDS reliably discriminated PDID from PDND (AUC = 0.81). Education did not improve predictive validity (AUC = 0.77). Performance of the eight-item MoPaRDS varied across sex (AUCfemales = 0.91; AUCmales = 0.74), whereas the three-item configuration did not (AUCfemales = 0.88; AUCmales = 0.91). Risk scores of both configurations increased over time. Conclusions We report new data on the application of the MoPaRDS as a dementia prediction tool for a geriatric PD cohort. Results support the viability of the full MoPaRDS, and indicate that an empirically determined brief version is a promising complement.

Publisher

Canadian Geriatrics Society

Subject

Geriatrics and Gerontology,Gerontology

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