Three simple clinical tests to accurately predict falls in people with Parkinson's disease

Falls are a major cause of morbidity in Parkinson's disease (PD). The objective of this study was to identify predictors of falls in PD and develop a simple prediction tool that would be useful in routine patient care. Potential predictor variables (falls history, disease severity, cognition, leg muscle strength, balance, mobility, freezing of gait [FOG], and fear of falling) were collected for 205 community‐dwelling people with PD. Falls were monitored prospectively for 6 months using monthly falls diaries. In total, 125 participants (59%) fell during follow‐up. A model that included a history of falls, FOG, impaired postural sway, gait speed, sit‐to‐stand, standing balance with narrow base of support, and coordinated stability had high discrimination in identifying fallers (area under the receiver‐operating characteristic curve [AUC], 0.83; 95% confidence interval [CI], 0.77–0.88). A clinical tool that incorporated 3 predictors easily determined in a clinical setting (falling in the previous year: odds ratio [OR], 5.80; 95% CI, 3.00–11.22; FOG in the past month: OR, 2.39; 95% CI, 1.19–4.80; and self‐selected gait speed < 1.1 meters per second: OR, 1.86; 95% CI, 0.96–3.58) had similar discrimination (AUC, 0.80; 95% CI, 0.73–0.86) to the more complex model (P = 0.14 for comparison of AUCs). The absolute probability of falling in the next 6 months for people with low, medium, and high risk using the simple, 3‐test tool was 17%, 51%, and 85%, respectively. In people who have PD without significant cognitive impairment, falls can be predicted with a high degree of accuracy using a simple, 3‐test clinical tool. This tool enables individualized quantification of the risk of falling. © 2013 Movement Disorder Society