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Neurology. 2010 Jul 13;75(2):116-24. doi: 10.1212/WNL.0b013e3181e7b688. Epub 2010 Jun 23.

Predictors of future falls in Parkinson disease.

Author information

  • 1School of Human Movement Studies, Institute of Health and Biomedical Innovation, Royal Brisbane and Women's Hospital, Queensland, Australia. g.kerr@qut.edu.au

Abstract

BACKGROUND:

Falls are a major health and injury problem for people with Parkinson disease (PD). Despite the severe consequences of falls, a major unresolved issue is the identification of factors that predict the risk of falls in individual patients with PD. The primary aim of this study was to prospectively determine an optimal combination of functional and disease-specific tests to predict falls in individuals with PD.

METHODS:

A total of 101 people with early-stage PD undertook a battery of neurologic and functional tests in their optimally medicated state. The tests included Tinetti, Berg, Timed Up and Go, Functional Reach, and the Physiological Profile Assessment of Falls Risk; the latter assessment includes physiologic tests of visual function, proprioception, strength, cutaneous sensitivity, reaction time, and postural sway. Falls were recorded prospectively over 6 months.

RESULTS:

Forty-eight percent of participants reported a fall and 24% more than 1 fall. In the multivariate model, a combination of the Unified Parkinson's Disease Rating Scale (UPDRS) total score, total freezing of gait score, occurrence of symptomatic postural orthostasis, Tinetti total score, and extent of postural sway in the anterior-posterior direction produced the best sensitivity (78%) and specificity (84%) for predicting falls. From the UPDRS items, only the rapid alternating task category was an independent predictor of falls. Reduced peripheral sensation and knee extension strength in fallers contributed to increased postural instability.

CONCLUSIONS:

Falls are a significant problem in optimally medicated early-stage PD. A combination of both disease-specific and balance- and mobility-related measures can accurately predict falls in individuals with PD.

PMID:
20574039
[PubMed - indexed for MEDLINE]
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