Dataset Information

Dynamic balance and instrumented gait variables are independent predictors of falls following stroke.

ABSTRACT:

Background

Falls are common following stroke and are frequently related to deficits in balance and mobility. This study aimed to investigate the predictive strength of gait and balance variables for evaluating post-stroke falls risk over 12?months following rehabilitation discharge.

Methods

A prospective cohort study was undertaken in inpatient rehabilitation centres based in Australia and Singapore. A consecutive sample of 81 individuals (mean age 63?years; median 24?days post stroke) were assessed within one week prior to discharge. In addition to comfortable gait speed over six metres (6mWT), a depth-sensing camera (Kinect) was used to obtain fast-paced gait speed, stride length, cadence, step width, step length asymmetry, gait speed variability, and mediolateral and vertical pelvic displacement. Balance variables were the step test, timed up and go (TUG), dual-task TUG, and Wii Balance Board-derived centre of pressure velocity during static standing. Falls data were collected using monthly calendars.

Results

Over 12?months, 28% of individuals fell at least once. The faller group had increased TUG time and reduced stride length, gait speed variability, mediolateral and vertical pelvic displacement, and step test scores (P?ConclusionsReduced displacement of the pelvis in the mediolateral direction during walking was the strongest predictor of post-stroke falls compared with other gait variables. Dynamic balance measures, such as the TUG and step test, may better predict falls than gait speed or static balance measures.

SUBMITTER: Bower K

PROVIDER: S-EPMC6322221 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dynamic balance and instrumented gait variables are independent predictors of falls following stroke.

Bower Kelly K Thilarajah Shamala S Pua Yong-Hao YH Williams Gavin G Tan Dawn D Mentiplay Benjamin B Denehy Linda L Clark Ross R

Journal of neuroengineering and rehabilitation 20190107 1

<h4>Background</h4>Falls are common following stroke and are frequently related to deficits in balance and mobility. This study aimed to investigate the predictive strength of gait and balance variables for evaluating post-stroke falls risk over 12 months following rehabilitation discharge.<h4>Methods</h4>A prospective cohort study was undertaken in inpatient rehabilitation centres based in Australia and Singapore. A consecutive sample of 81 individuals (mean age 63 years; median 24 days post st ...[more]

PMID: 30612584

Similar Datasets

Project description:Falls are the leading cause of injury in stroke patients. However, the cause of a fall is complicated, and several types of risk factors are involved. Therefore, a comprehensive model to predict falls with high sensitivity and specificity is needed.This study was a prospective study of 112 inpatients in a rehabilitation ward with follow-up interviews in patients' homes. Evaluations were performed 1 month after stroke and included the following factors: (1) status of cognition, depression, fear of fall and limb spasticity; (2) functional assessments [walking velocity and the Functional Independence Measure (FIM)]; and (3) objective, computerized gait and balance analyses. The outcome variable was the number of accidental falls during the 6-month follow-up period after baseline measurements.The non-faller group exhibited significantly better walking velocity and FIM scale compared to the faller group (P < .001). The faller group exhibited higher levels of spasticity in the affected limbs, asymmetry of gait parameters in single support (P < .001), double support (P = .027), and step time (P = .003), and lower stability of center of gravity in the medial-lateral direction (P = .008). Psychological assessments revealed that the faller group exhibited more severe depression and lower confidence without falling. A multivariate logistic regression model identified three independent predictors of falls with high sensitivity (82.6%) and specificity (86.5%): the asymmetry ratio of single support [adjusted odds ratio, aOR = 2.2, 95% CI (1.2-3.8)], the level of spasticity in the gastrocnemius [aOR = 3.2 (1.4-7.3)], and the degree of depression [aOR = 1.4 (1.2-1.8)].This study revealed depression, in additional to gait asymmetry and spasticity, as another independent factor for predicting falls. These results suggest that appropriate gait training, reduction of ankle spasticity, and aggressive management of depression may be critical to prevent falls in stroke patients.

Project description:Impairments in metabolic capacity and economy (O2cost) are hallmark characteristics of locomotor dysfunction following stroke. High-intensity (aerobic) training has been shown to improve peak oxygen consumption in this population, with fewer reports of changes in O2cost. However, particularly in persons with subacute stroke, inconsistent gains in walking function are observed with minimal associations with gains in metabolic parameters. The purpose of this study was to evaluate changes in aerobic exercise performance in participants with subacute stroke following high-intensity variable stepping training as compared with conventional therapy.A secondary analysis was performed on data from a randomized controlled trial comparing high-intensity training with conventional interventions, and from the pilot study that formed the basis for the randomized controlled trial. Participants 1 to 6 months poststroke received 40 or fewer sessions of high-intensity variable stepping training (n = 21) or conventional interventions (n = 12). Assessments were performed at baseline (BSL), posttraining, and 2- to 3-month follow-up and included changes in submaximal (Equation is included in full-text article.)O2 ((Equation is included in full-text article.)O2submax) and O2cost at fastest possible treadmill speeds and peak speeds at BSL testing.Significant improvements were observed in (Equation is included in full-text article.)O2submax with less consistent improvements in O2cost, although individual responses varied substantially. Combined changes in both (Equation is included in full-text article.)O2submax and (Equation is included in full-text article.)O2 at matched peak BSL speeds revealed stronger correlations to improvements in walking function as compared with either measure alone.High-intensity stepping training may elicit significant improvements in (Equation is included in full-text article.)O2submax, whereas changes in both peak capacity and economy better reflect gains in walking function. Providing high-intensity training to improve locomotor and aerobic exercise performance may increase the efficiency of rehabilitation sessions.Video Abstract available for more insights from the authors (see Supplemental Digital Content, http://links.lww.com/JNPT/A142).

Dataset Information

Dynamic balance and instrumented gait variables are independent predictors of falls following stroke.

Background

Methods

Results

Publications

Dynamic balance and instrumented gait variables are independent predictors of falls following stroke.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets