OBJECTIVES: Clinicians often base the implementation of therapies on the presence of postural instability in subjects with Parkinson's disease (PD). These decisions are frequently based on the pull test from the Unified Parkinson's Disease Rating Scale (UPDRS). We sought to determine whether combining the pull test, the one-leg stance test, the functional reach test, and UPDRS items 27-29 (arise from chair, posture, and gait) predicts balance confidence and falling better than any test alone. METHODS: The study included 67 subjects with PD. Subjects performed the one-leg stance test, the functional reach test, and the UPDRS motor exam. Subjects also responded to the Activities-specific Balance Confidence (ABC) scale and reported how many times they fell during the previous year. Regression models determined the combination of tests that optimally predicted mean ABC scores or categorised fall frequency. RESULTS: When all tests were included in a stepwise linear regression, only gait (UPDRS item 29), the pull test (UPDRS item 30), and the one-leg stance test, in combination, represented significant predictor variables for mean ABC scores (r2 = 0.51). A multinomial logistic regression model including the one-leg stance test and gait represented the model with the fewest significant predictor variables that correctly identified the most subjects as fallers or non-fallers (85% of subjects were correctly identified). CONCLUSIONS: Multiple balance tests (including the one-leg stance test, and the gait and pull test items of the UPDRS) that assess different types of postural stress provide an optimal assessment of postural stability in subjects with PD.
OBJECTIVES: Clinicians often base the implementation of therapies on the presence of postural instability in subjects with Parkinson's disease (PD). These decisions are frequently based on the pull test from the Unified Parkinson's Disease Rating Scale (UPDRS). We sought to determine whether combining the pull test, the one-leg stance test, the functional reach test, and UPDRS items 27-29 (arise from chair, posture, and gait) predicts balance confidence and falling better than any test alone. METHODS: The study included 67 subjects with PD. Subjects performed the one-leg stance test, the functional reach test, and the UPDRS motor exam. Subjects also responded to the Activities-specific Balance Confidence (ABC) scale and reported how many times they fell during the previous year. Regression models determined the combination of tests that optimally predicted mean ABC scores or categorised fall frequency. RESULTS: When all tests were included in a stepwise linear regression, only gait (UPDRS item 29), the pull test (UPDRS item 30), and the one-leg stance test, in combination, represented significant predictor variables for mean ABC scores (r2 = 0.51). A multinomial logistic regression model including the one-leg stance test and gait represented the model with the fewest significant predictor variables that correctly identified the most subjects as fallers or non-fallers (85% of subjects were correctly identified). CONCLUSIONS: Multiple balance tests (including the one-leg stance test, and the gait and pull test items of the UPDRS) that assess different types of postural stress provide an optimal assessment of postural stability in subjects with PD.
Authors: Martine Visser; Johan Marinus; Bastiaan R Bloem; Hannah Kisjes; Barbara M van den Berg; Jacobus J van Hilten Journal: Arch Phys Med Rehabil Date: 2003-11 Impact factor: 3.966
Authors: T Keränen; S Kaakkola; K Sotaniemi; V Laulumaa; T Haapaniemi; T Jolma; H Kola; A Ylikoski; O Satomaa; J Kovanen; E Taimela; H Haapaniemi; H Turunen; A Takala Journal: Parkinsonism Relat Disord Date: 2003-01 Impact factor: 4.891
Authors: W F Abdo; G F Borm; M Munneke; M M Verbeek; R A J Esselink; B R Bloem Journal: J Neurol Neurosurg Psychiatry Date: 2006-07-17 Impact factor: 10.154
Authors: M B Aerts; R A J Esselink; W F Abdo; F J A Meijer; G Drost; N Norgren; M J R Janssen; G F Borm; B R Bloem; M M Verbeek Journal: J Neurol Date: 2014-11-09 Impact factor: 4.849