External validation of a simple clinical tool used to predict falls in people with Parkinson disease

  • Ryan P. Duncan
  • , James T. Cavanaugh
  • , Gammon M. Earhart
  • , Terry D. Ellis
  • , Matthew P. Ford
  • , K. Bo Foreman
  • , Abigail L. Leddy
  • , Serene S. Paul
  • , Colleen G. Canning
  • , Anne Thackeray
  • , Leland E. Dibble

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Background: Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1m/s was developed and accurately predicted future falls in a sample of individuals with PD. METHODS: We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. RESULTS: The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC]=0.83; 95% CI 0.76-0.89), comparable to the developmental study. CONCLUSION: The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual's risk of an impending fall.

Original languageEnglish (US)
Pages (from-to)960-963
Number of pages4
JournalParkinsonism and Related Disorders
Volume21
Issue number8
DOIs
StatePublished - Aug 1 2015
Externally publishedYes

Keywords

  • Fall prediction
  • Fall risk
  • Falls
  • Parkinson disease

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology
  • Geriatrics and Gerontology

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