Objective: Use standardized measures to characterize disease severity, progression, and outcomes in Parkinson’s disease (PD).

Background: Subjective and objective standardized measures are usually performed in the context of clinical trials with small sample sizes and subject selection. At the point of care, use of these measures is limited due to lack of time and discrete data capture by the electronic medical record (EMR). Little is known about correlations of PD score tests in real-world patients, or how multiple score tests co-vary longitudinally. To address these issues we developed structured clinical documentation support (SCDS) tools iwithin the EMR.

Methods: Descriptive analysis included age at onset and diagnosis, disease duration, Montreal Cognitive Assessment (MoCA), Short Test of Mental Status (STMS), Epworth Sleepiness Scale (ESS), Geriatric Depression Scale (GDS), 9-Hole Peg Test, UPDRS parts I-III, H&Y stage, S&E scale, dopaminergic therapy and complications of therapy. Statistical analysis included Q-Q plots to assess score distribution, medians, range, means and standard deviations, pair-wise correlations of eleven score tests using Spearman rank correlation coefficients with Bonferroni correction both unadjusted and adjusted for possible confounders. Principal component analysis (PCA) was used to explore multidimensional variance between score tests.

Results: 586 patients (65% male, 92% Caucasian) were enrolled using the Bower diagnostic criteria. Medians (and range) were: age at diagnosis, 67 yr (30-92); disease duration, 3 yr (0-43); MoCA score, 26 (7-30): GDS score, 3 (0-14); ESS score, 6 (0-23); UPDRS part III score, 22 (3-57); H&Y stage, 2 (1-5). 50% were on dopaminergic therapy with a good response. Median duration without dyskinesias was 8 yr (1-18) and motor fluctuations 6 yr (1-18). Pair-wise correlations and PCA demonstrate a separation of subjective from objective measures.

Conclusions: The SCDS demonstrates a detailed characterization of a large PD cohort in a clinical practice setting that allows accurate longitudinal characterization of disease progression and outcomes. Statistical analysis suggests that variance between tests is better explained by the source of the measures than the measure domain (motor vs.non-motor). We are disseminating SDCS toolkits and sharing data to create a Neurology Practice Based Research Network¹.

References: 1. Maraganore DM, Frigerio R, Kazmi N, Meyers SL, Sefa M, Walters SA, Silverstein JC. Quality improvement and practice-based research in neurology using the electronic medical record. Neurol Clin Pract. 2015 Oct;5(5):419-429.

« Back to 2017 International Congress

MDS Abstracts - https://www.mdsabstracts.org/abstract/segregation-of-subjective-and-objective-clinical-measures-in-parkinsons-disease/