Session Time: 12:00pm-1:30pm
Location: Exhibit Hall located in Hall B, Level 2
Objective: To identify predictors of recurrent falls in people with Parkinson’s disease (PD); and to develop a predictive tool for identifying individuals at different categories of falls risk.
Background: Several predictors of recurrent falls have been identified in people with PD. However, to date no clinical predictive tool for recurrent falls has been reported.
Methods: Participants with PD (n = 229) were enrolled in this study. Besides demographic and clinical data, participants were assessed with the Unified Parkinson’s disease Rating Scale (UPDRS)- activities of daily living (ADL) and motor sections, modified Hoehn and Yahr Scale, Schwab and England Scale, Falls Efficacy Scale-International (FES-I), Activities-specific Balance Confidence Scale (ABC), Berg Balance Scale (BBS), Dynamic Gait Index (DGI), Functional Reach and Timed Up and Go (TUG). Predictor variables were grouped into nine domains (i.e. demographic, PD severity, PD symptoms, co-morbidities, PD-specific and non-PD specific medications, disability, balance/mobility and self-efficacy). Participants were followed up for 12 months to record the incidence of falls. Area under the receiver operating characteristic curves (AUC), Kaplan-Meier curves and log-rank test were performed. Selected predictors with p < 0.10 in univariate analysis within each domain were chosen to be entered into the Cox regression model.
Results: Eighty-four (37%) participants had ≥2 falls. The full Cox model included recurrent falls in the past year, UPDRS- ADL and motor sections, dyskinesia, motor fluctuations, levodopa equivalent dose (LED), polypharmacy, BBS and FES-I. The final Cox model included recurrent falls in the past year (Hazard ratio [HR] = 3.94; 95% confidence interval [CI] 2.26-6.86; p < 0.001), motor fluctuations (HR = 1.91; 95% CI 1.12-3.26; p = 0.017), UPDRS ADL (HR = 1.10 per 1 point increase; 95% CI 1.06-1.14; p < 0.001) and LED (HR = 1.09 per 100 mg increase; 95% CI 1.02-1.16; p = 0.011). The predictive tool included recurrent falls in the past year, motor fluctuations and UPDRS ADL > 12 points (AUC = 0.84; 95% CI 0.78-0.90).
Conclusions: We found three predictors that can identify people at low, medium and high risk of falling recurrently in the next 12 months. A simple prediction tool can predict recurrent falls in people with PD with moderate to high accuracy.
To cite this abstract in AMA style:L.R.S. Almeida, G.T. Valenca, N.N. Negreiros, E.B. Pinto, J. Oliveira-Filho. Predictors of recurrent falls in people with Parkinson’s disease and development of a predictive tool [abstract]. Mov Disord. 2016; 31 (suppl 2). https://www.mdsabstracts.org/abstract/predictors-of-recurrent-falls-in-people-with-parkinsons-disease-and-development-of-a-predictive-tool/. Accessed September 28, 2023.
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MDS Abstracts - https://www.mdsabstracts.org/abstract/predictors-of-recurrent-falls-in-people-with-parkinsons-disease-and-development-of-a-predictive-tool/