Affiliations: [a] Movement Disorders and Parkinson’s Disease Clinic, Roberto Santos General Hospital/SESAB, Salvador, Bahia, Brazil
| [b] Postgraduate Program in Health Sciences, Federal University of Bahia School of Medicine, Salvador, Bahia, Brazil
| [c] Motor Behavior and Neurorehabilitation Research Group, Bahiana School of Medicine and Public Health, Salvador, Bahia, Brazil
| [d] Health Sciences Center, Federal University of Recôncavo of Bahia, Santo Antônio de Jesus, Bahia, Brazil
| [e] Movement Disorders Clinic, State of Bahia Health Attention Center for the Elderly/SESAB, Salvador, Bahia, Brazil
Correspondence:
[*]
Correspondence to: Lorena R.S. Almeida, Movement Disorders and Parkinson’s Disease Clinic, Roberto Santos General Hospital/SESAB, Rua Direta do Saboeiro, s/n Cabula, 41180-780, Salvador, Bahia, Brazil. Tel.: +55 71 3103 8900; E-mail: lorenasantos@gmail.com.
Abstract: Background: Falls are a debilitating problem for people with Parkinson’s disease (PD). Objectives: To compare clinical and functional characteristics of non-fallers, single and recurrent fallers (≥2 falls); to determine predictors of time to second fall; and to develop a predictive tool for identifying people with PD at different categories of falls risk. Methods: Participants (n = 229) were assessed by disease-specific, self-report and balance measures and followed up for 12 months. 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 were chosen to be entered into the Cox regression model. Results: Eighty-four (37%) participants had ≥2 falls during the follow-up. Recurrent fallers significantly differed from single fallers. The final Cox model included history of ≥2 falls in the past year (Hazard Ratio [HR] = 3.94; 95% confidence interval [CI] 2.26–6.86), motor fluctuations (HR = 1.91; 95% CI 1.12–3.26), UPDRS activities of daily living (ADL) (HR = 1.10 per 1 point increase; 95% CI 1.06–1.14) and levodopa equivalent dose (LED) (HR = 1.09 per 100 mg increase; 95% CI 1.02–1.16). A 3-predictor tool included history of ≥2 falls in the past year, motor fluctuations and UPDRS ADL >12 points (AUC = 0.84; 95% CI 0.78–0.90). By adding LED >700 mg/day and Berg balance scale ≤49 points, a 5-predictor tool was developed (AUC = 0.86; 95% CI 0.81–0.92). Conclusions: Two predictive tools with moderate-to-high accuracy may identify people with PD at low, medium and high risk of falling recurrently within the next year. However, future studies to address external validation are required.
Keywords: Parkinson disease, accidental falls, postural balance, risk factors
