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Patterns of motor and non-motor features in Parkinson’s disease
  1. Stephanie M van Rooden (s.m.van_rooden{at}lumc.nl)
  1. Leiden University Medical Center, Netherlands
    1. Martine Visser (m.visser{at}lumc.nl)
    1. Leiden University Medical Center, Netherlands
      1. Dagmar Verbaan (d.verbaan{at}lumc.nl)
      1. Leiden University Medical Center, Netherlands
        1. J Marinus (j.marinus{at}lumc.nl)
        1. Leiden University Medical Center, Netherlands
          1. Bob Van Hilten (j.j.van_hilten{at}lumc.nl)
          1. Leiden University Medical Center, Netherlands

            Abstract

            Objective: To evaluate the presence and nature of patterns of coherency among the motor and non-motor domains in Parkinson’s disease (PD) and to examine which clinical parameters are related to the potential patterns.

            Methods: A cohort of 397 PD patients was randomly divided into two samples. Exploratory factor analysis (EFA) was performed on the motor and non-motor symptoms in PD in the first sample. Findings of the EFA were used to construct a model which was tested in the second sample by confirmatory factor analysis. Multiple regression analyses on the resulting factors were performed to evaluate the influence of clinical parameters upon these factors.

            Results: Four factors were identified. The first and strongest factor (cognitive impairment, autonomic dysfunction, psychotic symptoms, depression, daytime sleepiness, and axial symptoms) reflected advancing disease. Another factor largely reflected motor complications of therapy and was related to dopaminergic medication. The other two factors reflected sleep/depression and tremor/bradykinesia/rigidity, and were only marginally related to disease severity or medication.

            Conclusions: The motor and non-motor features in PD can be characterized by four distinct patterns of coherency, which provide insight in the contributions of the primary disease process and anti-parkinsonian medication to the broad clinical spectrum of PD. One factor, consisting of predominantly non-motor symptoms together with axial features, clearly reflected disease severity and may provide a new basis for monitoring disease progression in PD.

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