Importance of Balance-Gait Disorder As a Risk Factor for Cognitive Impairment, Dementia and Related Non-Motor Symptoms in Parkinson's Disease

Background: In Parkinson's disease (PD), postural instability-gait disorder (PIGD) has been associated with more rapid cognitive decline, dementia, and greater non-motor symptom (NMS) burden.

Objective: To assess the importance of balance-gait disorder, relative to and in combination with other clinical measures, as a risk factor for cognitive impairment, dementia and NMS burden in PD.

Methods: 164 PD subjects were evaluated in a retrospective cross-sectional study using the MDS-UPDRS scale, MMSE and Clinical Dementia Rating Scale. Using univariate comparisons followed by multiple stepwise regression, we identified factors most closely associated with NMS burden and concurrent dementia. Nominal logistic regression and linear discriminant analysis was used to compute receiver operating characteristic curves and to measure sensitivity and specificity of predictors of dementia.

Results: Dementia was more frequent in those with the PIGD phenotype (χ2 = 11.49, p = 0.003). The MDS-UPDRS balance-gait measure, excluding freezing of gait, was the single best predictor not only of concurrent cognitive impairment and dementia (F = 37.16, p < 0.001) but also of NMS burden, predicting 29% of the MDS-UPDRS total non-motor experiences of daily living score (F = 67.14, p < 0.0001). This measure, together with combined severity of hallucinations/psychosis, daytime sleepiness and urinary problems, a closely correlated symptom cluster (r = 0.63 p < 0.0001), accurately classified 84% of patients with dementia.

Conclusions: In PD, balance-gait impairment is closely associated with dementia and NMS burden, particularly the linked symptoms of cognitive impairment, psychosis, daytime sleepiness and urinary dysfunction. This phenotype characterizes patients likely to require closer surveillance and more comprehensive care. Confirmation of these findings in prospective longitudinal studies might help refine predictive algorithms designed to identify PD patients more likely to progress from mild cognitive impairment to dementia.