title: Subtle motor disturbances in PREDICT-PD participants.
abstract: The PREDICT-PD study aims to identify increased risk of Parkinson''s disease (PD) using online assessments of previously identified risk and early features of PD and an evidence-based scoring algorithm. We sought to determine whether higher risk participants (defined as those above the 15th centile of risk estimates) were more likely to have mild parkinsonian signs compared with lower risk participants.
  
  
  
  Video recordings of neurological examinations, including the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III, of 208 individuals who had previously completed an online risk assessment were scored blindly and independently by two movement-disorders experts. Higher risk and lower risk subjects were compared for MDS-UPDRS part III score (and derivations of this) to identify subclinical parkinsonism, and association of risk estimates with MDS-UPDRS III scores assessed.
  
  
  
  Higher risk subjects had significantly higher median UPDRS part III scores (3, IQR 1-5.5) than lower risk subjects (1, IQR 0-3.0; p<0.001), and there was a significantly greater proportion of individuals classified as having subclinical parkinsonism. 18% of the higher risk subjects and 6% of the lower risk subjects exceeded the most stringent published cut-off for subtle parkinsonism of three definitions examined (p=0.027). Linear regression analysis demonstrated a continuous relationship of log-transformed risk estimates with UPDRS part III scores (increase in MDS-UPDRS per doubling of odds 0.52, 95% CI 0.31 to 0.72; p<0.001), which remained after adjustment for multiple vascular risk factors and scores on the Montreal Cognitive Assessment (0.58, 95% CI 0.30 to 0.87; p<0.001).
  
  
  
  The PREDICT-PD algorithm identifies a population with an increased rate of motor disturbances.
authors.affiliation: Department of Molecular Neuroscience, Reta Lila Weston Institute, UCL Institute of Neurology, London, UK.|Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
authors.forename: Alastair J
authors.initials: AJ
authors.lastname: Noyce
authors.affiliation: Department of Clinical Neuroscience, UCL Institute of Neurology, London, UK.
authors.forename: Anette
authors.initials: A
authors.lastname: Schrag
authors.affiliation: Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
authors.forename: Joseph M
authors.initials: JM
authors.lastname: Masters
authors.affiliation: Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK.
authors.forename: Jonathan P
authors.initials: JP
authors.lastname: Bestwick
authors.affiliation: Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
authors.forename: Gavin
authors.initials: G
authors.lastname: Giovannoni
authors.affiliation: Department of Molecular Neuroscience, Reta Lila Weston Institute, UCL Institute of Neurology, London, UK.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Lees
mesh_terms: D000368:Aged; D000465:Algorithms; D004185:Disability Evaluation; D005260:Female; D006801:Humans; D020407:Internet; D008297:Male; D008875:Middle Aged; D009460:Neurologic Examination / Q000379:methods*; D010300:Parkinson Disease / Q000175:diagnosis*; D011597:Psychomotor Performance / Q000502:physiology*; D012307:Risk Factors; D012720:Severity of Illness Index; D011795:Surveys and Questionnaires