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Purpose: To verify the psychometric properties of the Brazilian-Portuguese version of the Falls Behavioral (FaB-Brazil) Scale in Parkinson's disease (PD)., Material and Methods: Participants ( n  = 96) were assessed by disease-specific, self-report and functional mobility measures. Internal consistency of the FaB-Brazil scale was evaluated using Cronbach's alpha and inter-rater and test-retest reliability using intraclass correlation coefficients (ICC). The standard error of measurement (SEM), minimal detectable change (MDC), ceiling and floor effects, and convergent and discriminative validity were evaluated., Results: Internal consistency was moderate (α = 0.77). Excellent inter-rater (ICC = 0.90; p  < 0.001) and test-retest (ICC = 0.91; p  < 0.001) reliability were found. The SEM was 0.20 and MDC was 0.38. Ceiling and floor effects were not found. Convergent validity was established by the positive correlations between the FaB-Brazil scale and age, modified Hoehn and Yahr, PD duration, Movement Disorders Society-Unified Parkinson's Disease Rating Scale, Motor Aspects of Experiences of Daily Living, Timed Up & Go and 8-item Parkinson's Disease Questionnaire, and negative correlations between the FaB-Brazil scale and community mobility, Schwab & England, and Activities-specific Balance Confidence scale. Females showed greater protective behaviors than males; recurrent fallers showed greater protective behaviors than non-recurrent fallers ( p  < 0.05)., Conclusions: The FaB-Brazil scale is reliable and valid for assessing people with PD.

Background: Previous investigations of falls predictors in people with Parkinson's disease (PD) have used various statistical methods and categorization of falls outcomes. The impact of methodological differences on falls predictors has not been investigated., Objectives: To describe similarities and differences in predictors modelled for fall rates [negative binomial (NB), Poisson Inverse Gaussian (PIG) and quantile regression] and previously-reported predictors of time to second fall (Cox regression), i.e. past falls, motor fluctuations, disability, levodopa dose and balance impairment. To investigate whether predictors from quantile regression vary across subsets of fallers based on fall frequency., Methods: Participants with PD (n = 229) were followed-up for 12 months. NB and PIG regression were used to determine predictors of fall rates, with the best fitting model reported. Quantile regression was used to determine predictors at higher (62nd, 70th, 80th) percentiles of the falls distribution. Univariate and multivariate analyses were performed., Results: Predictors of fall rates were the same in NB and PIG multivariate models, with the PIG model fitting our data better. Past falls, disability and levodopa dose were associated with fall rates from PIG and quantile regression. Freezing of gait was associated with fall rates from PIG regression. Disease severity predicted less (70th percentile, approximately 2-4) and more (80th percentile, approximately ≥ 5) frequent falls, and anteroposterior stability also predicted less frequent falls (p < 0.05), from quantile regression., Conclusions: Not all predictors of time to second fall were predictors of fall rates. Quantile regression revealed some divergent predictors depending on the percentile of fall frequency examined.

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.

Objectives: This study aimed to determine risk factors related to the occurrence of falls in stroke patients and to propose a new predictive scale for falls., Methods: Demographic and clinical data were collected and the following scales were applied: Barthel Index, Timed Up and Go Test (TUG), and National Institutes of Health Stroke Scale (NIHSS). Subjects were followed prospectively for 2 years for the occurrence of recurrent (≥2) falls. Kaplan-Meier curves were constructed and univariable associations were tested using log-rank test. Two separate multivariable models were then used: the first used Cox proportional hazards regression and the second used Poisson regression. In each model, significant associations were considered present with a P value less than .05., Results: We evaluated 150 individuals and the final analysis included 131 patients; the average age of the patients was 55.8 ± 13 years, 52% were women, and the median NIHSS score was 2 (interquartile range = 1-5). Falls occurred in 17% of patients, with a median of 23 months of follow-up (interquartile range = 16-26 months). In the multivariable Cox regression model, only TUG quartile, female gender, and posterior circulation territory involvement remained significant predictors of recurrent falls. We used the predictors from the Cox regression model to propose a new recurrent fall risk scale. The area under the receiver operating characteristic curve was 73%, 95% confidence interval = 62%-83%, P = .001, with 81.3% sensitivity and 41.8% specificity., Conclusions: The new predictive scale for recurrent risk (including TUG, posterior circulation territory involvement, and female gender) is presented as an instrument for monitoring the risk of recurrent falls., (Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.)

Background: Balance confidence and fear of falling are factors associated with recurrent falls in people with Parkinson disease (PD). However, the accuracy for predicting falls on the basis of self-report measures has not been widely investigated., Objective: The study objectives were: (1) to compare the accuracy of the Activities-specific Balance Confidence Scale (ABC) and the Falls Efficacy Scale-International (FES-I) with that of the Berg Balance Scale (BBS), Dynamic Gait Index (DGI), Functional Reach Test (FRT), and Timed "Up & Go" Test (TUG) for predicting recurrent falls in people with PD and (2) to explore the ability of combinations of up to 3 tests to predict recurrent falls., Design: This was a prospective cohort study involving 225 people with PD., Methods: Participants were assessed with the ABC, FES-I, BBS, FRT, TUG, and DGI. Participants who reported 2 or more falls in the 12-month follow-up period were classified as recurrent fallers. Areas under the receiver operating characteristic curves were determined, and the Akaike information criterion was used to select the best predictive model., Results: Eighty-four participants (37.3%) were classified as recurrent fallers. Areas under the receiver operating characteristic curves for the ABC, FES-I, TUG, FRT, DGI, and BBS were 0.73, 0.74, 0.72, 0.74, 0.76, and 0.79, respectively. Two-test models provided additional discriminating ability compared with individual measures and had Akaike information criterion values similar to those of 3-test models, particularly the combination of the BBS with the FES-I., Limitations: The lack of an external validation sample was a limitation of this study., Conclusions: The ABC and FES-I demonstrated moderate accuracy in predicting recurrent falls and a predictive ability similar to that of performance-based balance measures, especially the FRT and the TUG. Two-test models showed performance similar to that of 3-test models, suggesting that a combination of 2 measures may improve the ability to predict recurrent falls in people with PD. Specifically, the combination of the BBS with the FES-I may be considered., (© 2016 American Physical Therapy Association.)

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: Individuals with stroke have a high risk of falling, and their fall predictors may differ from those of other populations., Purpose: To estimate fall frequency and identify factors related to fall occurrence in a sample of patients with stroke residing in the community., Methods: Clinical data were collected from 150 consecutive stroke patients with independent gait, and the following scales were applied: modified Barthel Index (mBI), Timed Up & Go Test (TUG), and National Institutes of Health Stroke Scale (NIHSS). Univariate analysis was performed; variables with possible association (P < .1) were included in a logistic regression model. Receiver operating characteristic curves were used to identify the best cutoff point for TUG., Results: Falls occurred in 37% of patients. In multivariate analysis, right hemisphere injury (odds ratio [OR], 2.621; 95% CI, 1.196-5.740; P = .016), time in TUG (OR, 1.035 for every increase in 1 second; 95% CI, 1.003-1.069; P = .034), and longer time since stroke onset (OR, 1.012 for every month increase; 95% CI, 1.002-1.021; P = .015) remained predictors. When we grouped individuals according to affected cerebral hemisphere, both hemispheres had similar accuracy, but TUG cutoff point was lower in individuals with right- versus left-hemisphere lesions., Conclusions: Patients with poor TUG performance, longer times since stroke onset, and right-hemisphere injury have particularly high fall rates, and TUG cutoff points for fall prediction vary according to cerebral hemisphere.

Background: Falls are frequent in Parkinson's disease (PD), but there is lack of information about predictors of injurious falls. Objectives: To determine predictors of falls with injuries in people with PD; to compare circumstances and consequences of falls in single and recurrent fallers. Methods: Participants (n = 225) were assessed by disease‐specific, self‐report, and balance measures, and followed‐up for 12 months with a diary to record falls, their circumstances, and injuries. Univariate and multivariate analyses were performed. Circumstances and consequences of falls presented by single and recurrent fallers were compared. Results: A total of 805 falls were analyzed, 107 (13%) were falls with injuries. Multivariate logistic regression model revealed that greater PD duration and higher balance confidence were protective factors; better balance during gait, outdoor falls, and falls related to extrinsic factors were risk factors for falls with injuries, when compared to falls with no injuries. Multivariate multinomial regression model revealed that, when compared to zero fall, past falls and daily levodopa equivalent dose were predictors of falls with injuries; these predictors together with disability were predictors of falls with no injuries. Single falls (n = 27; 3%) were more common outdoors because of extrinsic factors, whereas recurrent falls (n = 778; 97%) were more common indoors because of intrinsic factors. Single falls led to more injuries than recurrent falls (P < 0.05). Conclusions: Different predictors of falls with injuries were obtained when different outcomes were compared. It should be noted that falls with injuries might be influenced by fall‐related activities and environmental factors. Single and recurrent falls differed on circumstances and consequences. [ABSTRACT FROM AUTHOR]