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Incidence and prediction of falls in Parkinson's disease: a prospective multidisciplinary study

Open access
Wood, B H·2002·Journal of Neurology, Neurosurgery & Psychiatry

Abstract

OBJECTIVES: To accurately establish the incidence of falls in Parkinson's disease (PD) and to investigate predictive risk factors for fallers from baseline data. METHODS: 109 subjects with idiopathic PD diagnosed according to the brain bank criteria underwent a multidisciplinary baseline assessment comprising demographic and historical data, disease specific rating scales, physiotherapy assessment, tests of visual, cardiovascular and autonomic function, and bone densitometry. Patients were then prospectively followed up for one year using weekly prepaid postcards along with telephone follow up. RESULTS: Falls occurred in 68.3% of the subjects. Previous falls, disease duration, dementia, and loss of arm swing were independent predictors of falling. There were also significant associations between disease severity, balance impairment, depression, and falling. CONCLUSIONS: Falls are a common problem in PD and some of the major risk factors are potentially modifiable. There is a need for future studies to look at interventions to prevent falls in PD.

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Metadata

Authors
Wood, B. H.
Venue
Journal of Neurology, Neurosurgery & Psychiatry
Publisher
BMJ
Published
2002-06-01
Volume
72
Issue
6
Pages
721-725
ISSN
0022-3050 (ISSN-L)
OpenAlex
W2129240684
Cited by
700
References
2
FWCI
33.78
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Incidence and prediction of falls in Parkinson's disease: a prospective multidisciplinary study. https://app.cochat.ai/papers/10.1136/jnnp.72.6.721
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Wood, B. H. (2002). Incidence and prediction of falls in Parkinson's disease: a prospective multidisciplinary study. Journal of Neurology, Neurosurgery & Psychiatry. https://doi.org/10.1136/jnnp.72.6.721

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.