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

doi:10.1016/j.parkreldis.2015.05.008

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

Parkinsonism Relat Disord. 2015 Aug;21(8):960-3. doi: 10.1016/j.parkreldis.2015.05.008. Epub 2015 May 16.

Authors

Affiliations

¹ Washington University School of Medicine in St. Louis, Program in Physical Therapy, USA; Washington University School of Medicine in St. Louis, Department of Neurology, USA.
² University of New England, Department of Physical Therapy, USA.
³ Washington University School of Medicine in St. Louis, Program in Physical Therapy, USA; Washington University School of Medicine in St. Louis, Department of Neurology, USA; Washington University School of Medicine in St. Louis, Department of Anatomy & Neurobiology, USA.
⁴ Boston University, Department of Physical Therapy and Athletic Training, USA.
⁵ University of Alabama at Birmingham School of Health Professions, Department of Physical Therapy, USA.
⁶ University of Utah, Department of Physical Therapy, USA.
⁷ Washington University School of Medicine in St. Louis, Program in Physical Therapy, USA.
⁸ University of Utah, Department of Physical Therapy, USA; The George Institute for Global Health, The University of Sydney, Sydney Medical School, Australia.
⁹ The University of Sydney, Faculty of Health Sciences, Australia.
¹⁰ University of Utah, Department of Physical Therapy, USA. Electronic address: [email protected].

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 <1.1 m/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.

Keywords: Fall prediction; Fall risk; Falls; Parkinson disease.

Publication types

Multicenter Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Validation Study

MeSH terms

Accidental Falls*
Aged
Aged, 80 and over
Decision Support Techniques*
Female
Gait Disorders, Neurologic / diagnosis*
Gait Disorders, Neurologic / etiology
Humans
Longitudinal Studies
Male
Middle Aged
Parkinson Disease / complications
Parkinson Disease / diagnosis*
Predictive Value of Tests
Risk Assessment

Abstract

Publication types

MeSH terms

Grants and funding