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

26 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
Pages (from-to)960-963
Number of pages4
JournalParkinsonism and Related Disorders
Volume21
Issue number8
DOIs
StatePublished - Aug 1 2015

Keywords

  • Fall prediction
  • Fall risk
  • Falls
  • Parkinson disease

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