Date: Monday, June 5, 2017
Session Title: Parkinsonism, MSA, PSP (Secondary and Parkinsonism-Plus)
Session Time: 1:45pm-3:15pm
Location: Exhibit Hall C
Objective: To determine predictors of cognitive impairment in patients with multiple system atrophy (MSA).
Background: Although dementia is not a diagnostic criteria for MSA, an increasing number of studies are investigating cognitive impairment in MSA. The clinical and radiological features predicting cognitive impairment in MSA thus remain to be more fully investigated.
Methods: We prospectively recruited 59 consecutive patients with probable MSA according to the consensus criteria, and analyzed their clinical and MRI findings (Fazekas grade). We analyzed predictive factors related to decline in mini-mental state examination (MMSE) and frontal assessment battery (FAB) scores, using simple linear regression analysis for continuous data and ANOVA for discrete data. Then, we drew a regression line relating the MMSE scores to the disease duration and categorized patients that were below the 68% prediction interval as belonging to the severe cognitive impairment (SCI) group. We compared clinical and radiological findings between the SCI group and non-SCI group with simple and multiple logistic regression analysis.
Results: The MMSE scores negatively correlated with disease duration (p = 0.03), unified MSA rating scale (UMSARS) part 1 score (p = 0.02), part 4 score (p = 0.004), and residual urine volume (p = 0.002) and positively with CVRR (p = 0.01). The FAB scores negatively correlated with UMSARS part 2 score (p = 0.03), periventricular hyperintensity grade (p = 0.02), and deep white matter hyperintense signals grade (p = 0.01). Simple logistic regression analysis revealed that predictors for SCI were MSA with predominant Parkinsonian features (MSA-P) (p = 0.03), high UMSARS part 1 score (p = 0.03), high UMSARS part 4 score (p = 0.03), and high residual urine volume (p = 0.006). Stepwise multiple logistic regression analysis including these four factors revealed that a significant predictor for SCI was high residual urine volume (odds ratio, 1.006; 95% confidence interval, 1.0003-1.0112, p = 0.04).
Conclusions: This study demonstrated that high residual urine volume might be a predictor for SCI in patients with MSA. Findings in the present study may facilitate the development of better management protocols for patients with MSA.
To cite this abstract in AMA style:M. Hatakeyama, T. Sato, T. Takahashi, M. Kanazawa, O. Onodera, M. Nishizawa. Predictors of cognitive impairment in multiple system atrophy [abstract]. Mov Disord. 2017; 32 (suppl 2). https://www.mdsabstracts.org/abstract/predictors-of-cognitive-impairment-in-multiple-system-atrophy/. Accessed December 2, 2023.
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