Abstract
Introduction and objectiveSeveral prediction models for falls/near falls in Parkinson’s disease (PD) have been proposed. However, longitudinal predictors of frequency of falls/near falls are poorly investigated. Therefore, we aimed to identify short- and long-term predictors of the number of falls/near falls in PD.MethodsA prospective cohort of 58 persons with PD was assessed at baseline (mean age and PD duration, 65 and 3.2 years, respectively) and 3.5 years later. Potential predictors were history of falls and near falls, comfortable gait speed, freezing of gate, dyskinesia, retropulsion, tandem gait (TG), pain, and cognition (Mini-Mental State Exam, MMSE). After each assessment, the participants registered a number of falls/near falls during the following 6 months. Multivariate Poisson regression was used to identify short- and long-term predictors of a number of falls/near falls.ResultsBaseline median (q1–q3) motor (UPDRS) and MMSE scores were 10 (6.75–14) and 28.5 (27–29), respectively. History of falls was the only significant short-time predictor [incidence rate ratio (IRR), 15.17] for the number of falls/near falls during 6 months following baseline. Abnormal TG (IRR, 3.77) and lower MMSE scores (IRR, 1.17) were short-term predictors 3.5 years later. Abnormal TG (IRR, 7.79) and lower MMSE scores (IRR, 1.49) at baseline were long-term predictors of the number of falls/near falls 3.5 years later.ConclusionAbnormal TG and MMSE scores predict the number of falls/near falls in short and long term, and may be indicative of disease progression. Our observations provide important additions to the evidence base for clinical fall prediction in PD.
Highlights
Introduction and objectiveSeveral prediction models for falls/near falls in Parkinson’s disease (PD) have been proposed
Final model goodness-of-fit (Omnibus test), P < 0.001; R2 deviance, 0.369. In this prospective cohort study with persons with PD (PwPD), we found history of falls to be a strong short-term predictor of the number of falls and/or near falls in earlier stages of PD, whereas abnormal tandem gait (TG) and cognition were identified as both shortand long-term predictors in later stages of the disease
The data generated 3.5 years later yielded a prediction model with abnormal TG as a strongest predictor followed by cognitive decline, whereas history of falls did not contribute to the prediction of the number of falls/near falls over the 6 months, once TG and cognition were taken into account
Summary
Introduction and objectiveSeveral prediction models for falls/near falls in Parkinson’s disease (PD) have been proposed. We aimed to identify short- and long-term predictors of the number of falls/near falls in PD. The participants registered a number of falls/near falls during the following 6 months. Multivariate Poisson regression was used to identify short- and long-term predictors of a number of falls/near falls. History of falls was the only significant short-time predictor [incidence rate ratio (IRR), 15.17] for the number of falls/near falls during 6 months following baseline. Abnormal TG (IRR, 3.77) and lower MMSE scores (IRR, 1.17) were short-term predictors 3.5 years later. Abnormal TG (IRR, 7.79) and lower MMSE scores (IRR, 1.49) at baseline were long-term predictors of the number of falls/near falls 3.5 years later. Conclusion Abnormal TG and MMSE scores predict the number of falls/near falls in short and long term, and may be indicative of disease progression.
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