Lorena R S Almeida1,2,3, Catherine Sherrington4, Natalie E Allen3, Serene S Paul4, Guilherme T Valenca1, Jamary Oliveira-Filho2, Colleen G Canning3. 1. Movement Disorders and Parkinson's Disease Clinic, Roberto Santos General Hospital, Salvador, BA, Brazil. 2. Postgraduate Program in Health Sciences, Federal University of Bahia School of Medicine, Salvador, BA, Brazil. 3. Clinical and Rehabilitation Sciences Research Group, Faculty of Health Sciences, The University of Sydney, Lidcombe, NSW, Australia. 4. The George Institute for Global Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia.
Abstract
BACKGROUND: Predictors of falls in people with Parkinson's disease (PD) who have not previously fallen are yet to be identified. OBJECTIVES: We aimed to identify predictors of all falls and recurrent falls in people with PD who had not fallen in the previous year and to explore the timing of falls in a 12-month follow-up period. METHODS: Participants with PD (n = 130) were assessed by disease-specific, self-report and balance measures. Falls were recorded prospectively for 12 months. Univariate and multivariate analyses were performed. Kaplan-Meier survival analysis was used to investigate time to falling. RESULTS: Forty participants (31%) had ≥1 fall during follow-up and 21 (16%) had ≥2 falls. Disability, reduced balance confidence and greater concern about falling were associated with ≥1 fall in univariate analyses. Additionally, PD duration and severity, freezing of gait and impaired balance were associated with ≥2 falls (p < 0.05). Disability (Schwab and England scale, Odds Ratio [OR] = 0.56 per 10 points increase; 95% confidence interval [CI] 0.39-0.80; p = 0.002) was associated with ≥1 fall in the final multivariate model (area under the receiver operating characteristic curve [AUC] = 0.65; 95% CI 0.55-0.76; p = 0.005). Disability (Unified Parkinson's Disease Rating Scale activities of daily living, OR = 1.20; 95% CI 1.07-1.34; p = 0.001) and levodopa equivalent dose (OR = 1.11 per 100 mg increase; 95% CI 0.95-1.30; p = 0.19) were associated with ≥2 falls in the final multivariate model (AUC = 0.72; 95% CI 0.60-0.84; p = 0.001). Recurrent fallers experienced their first fall earlier than single fallers (p < 0.05). CONCLUSIONS: Self-reported disability was the strongest single predictor of all falls and recurrent falls.
BACKGROUND: Predictors of falls in people with Parkinson's disease (PD) who have not previously fallen are yet to be identified. OBJECTIVES: We aimed to identify predictors of all falls and recurrent falls in people with PD who had not fallen in the previous year and to explore the timing of falls in a 12-month follow-up period. METHODS:Participants with PD (n = 130) were assessed by disease-specific, self-report and balance measures. Falls were recorded prospectively for 12 months. Univariate and multivariate analyses were performed. Kaplan-Meier survival analysis was used to investigate time to falling. RESULTS: Forty participants (31%) had ≥1 fall during follow-up and 21 (16%) had ≥2 falls. Disability, reduced balance confidence and greater concern about falling were associated with ≥1 fall in univariate analyses. Additionally, PD duration and severity, freezing of gait and impaired balance were associated with ≥2 falls (p < 0.05). Disability (Schwab and England scale, Odds Ratio [OR] = 0.56 per 10 points increase; 95% confidence interval [CI] 0.39-0.80; p = 0.002) was associated with ≥1 fall in the final multivariate model (area under the receiver operating characteristic curve [AUC] = 0.65; 95% CI 0.55-0.76; p = 0.005). Disability (Unified Parkinson's Disease Rating Scale activities of daily living, OR = 1.20; 95% CI 1.07-1.34; p = 0.001) and levodopa equivalent dose (OR = 1.11 per 100 mg increase; 95% CI 0.95-1.30; p = 0.19) were associated with ≥2 falls in the final multivariate model (AUC = 0.72; 95% CI 0.60-0.84; p = 0.001). Recurrent fallers experienced their first fall earlier than single fallers (p < 0.05). CONCLUSIONS: Self-reported disability was the strongest single predictor of all falls and recurrent falls.
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