UNASSIGNED: Older adults discharged from the emergency department (ED) face elevated risk of falls and functional decline. Smartphones might enable remote monitoring of mobility after ED discharge, yet their application in this context remains underexplored.
UNASSIGNED: This study aimed to assess the feasibility of having older adults provide weekly accelerometer data from an instrumented Timed Up-and-Go (TUG) test over an 11-week period after ED discharge.
UNASSIGNED: This single-center, prospective, observational, cohort study recruited patients aged 60 years and older from an academic ED. Participants downloaded the GaitMate app to their iPhones that recorded accelerometer data during 11 weekly at-home TUG tests. We measured adherence to TUG test completion, quality of transmitted accelerometer data, and participants\' perceptions of the app\'s usability and safety.
UNASSIGNED: Of the 617 approached patients, 149 (24.1%) consented to participate, and of these 149 participants, 9 (6%) dropped out. Overall, participants completed 55.6% (912/1639) of TUG tests. Data quality was optimal in 31.1% (508/1639) of TUG tests. At 3-month follow-up, 83.2% (99/119) of respondents found the app easy to use, and 95% (114/120) felt safe performing the tasks at home. Barriers to adherence included the need for assistance, technical issues with the app, and forgetfulness.
UNASSIGNED: The study demonstrates moderate adherence yet high usability and safety for the use of smartphone TUG tests to monitor mobility among older adults after ED discharge. Incomplete TUG test data were common, reflecting challenges in the collection of high-quality longitudinal mobility data in older adults. Identified barriers highlight the need for improvements in user engagement and technology design.

UNASSIGNED: Several assessment tools have been developed to estimate a patient\'s likelihood risk of falling. None of these measures estimate the contributions of the visual, vestibular, and somatosensory systems to fall risk, especially in patients with degenerative lumbar spine disease.
UNASSIGNED: Degenerative lumbar spine patients with radiculopathy (LD) and healthy subjects who were 35-70 years old without spine complaints were recruited. Patient reported outcome measures (PROMs) were collected prior to testing. Fall risk assessment was completed using Computer Dynamic Posturography (CDP), a computer-controlled balance machine that allows cone of economy (CoE) and cone of pressure (CoP) measurements. All patients completed Sensory Organization Tests (SOT) which include normal and perturbed stability, both with and without visual cues.
UNASSIGNED: In total, 43 spine patients and 12 healthy controls were included, with mean age 57.8 years, 39.5% females, and mean BMI of 29.3 kg/m2. Nearly all CoE and most CoP dimensions were found to be larger in LD patients compared to controls across nearly all subtests (p<.05), with the largest dimensions generally observed in the surrounding and support sway testing condition. In LD patients, ODI and PROMIS Pain Interference were negatively correlated with CoE and CoP measurements (p<.05).
UNASSIGNED: In this prospective study, body sway was assessed as a function of CoE and CoP using the CDP system and was found to be elevated in spine patients, especially when they experienced increasing levels of visual and vestibular stimulation. The ability to identify the primary drivers of balance disorders is essential in spine patients and may be helpful in the development of a patient-specific treatment plan, which may in the future aid with fall-prevention initiatives.

UNASSIGNED: There are contradictory reports on the effect of cochlear implantation on postural control. Associated vestibular loss, electrode insertion trauma, and electrical stimulus of a cochlear implant can influence postural control. This study focused on the electrical stimulation of the cochlea. We aimed to examine whether a cochlear implant\'s electrical stimulation affects postural control measured by posturography.
UNASSIGNED: Thirty-three patients with unilateral cochlear implants were included. We used three preprogrammed main tests and their nine subtests in posturography. Postural stability [general stability index (GSI)], fall risk index (FRI), and sensory integration [modified clinical test of sensory integration of balance (m-CTSIB)] were calculated. All tests were performed under three conditions: implant off (1), implant on (2), and implant on music (3).
UNASSIGNED: The mean age was 46.29±16.09 years. GSI was above normal limits in 78% of adult cochlear implant users. We found that FRI was high in 30% of patients, and m-CTSIB was defective in 42%. There were no statistically significant differences in GSI, FRI, and m-CTSIB. Cochlear implant stimulation was found to have positively affected postural control when the subject\'s data were visualized individually. GSI, FRI, and m-CTSIB dropped to 39%, 24%, and 24%, respectively, when music was on. There was a significant correlation between age and fall index. But this correlation disappeared when music was playing.
UNASSIGNED: Cochlear implant stimulation affected the vestibular system in almost all patients. The effect was positive in most patients.

OBJECTIVE: We review the literature about patients 50 years and older with a recent clinical fracture for the presence of skeletal and extra-skeletal risks, their perspectives of imminent subsequent fracture, falls, mortality, and other risks, and on the role of the fracture liaison service (FLS) for timely secondary fracture prevention.
RESULTS: Patients with a recent clinical fracture present with heterogeneous patterns of bone-, fall-, and comorbidity-related risks. Short-term perspectives include bone loss, increased risk of fractures, falls, and mortality, and a decrease in physical performance and quality of life. Combined evaluation of bone, fall risk, and the presence of associated comorbidities contributes to treatment strategies. Since fractures are related to interactions of bone-, fall-, and comorbidity-related risks, there is no one-single-discipline-fits-all approach but a need for a multidisciplinary approach at the FLS to consider all phenotypes for evaluation and treatment in an individual patient.

Introduction Stroke is a major neurological event resulting from reduced or blocked blood flow to the brain, leading to significant morbidity. Immediate medical attention is essential to minimize brain damage and improve outcomes since it leads to many clinical deficits like locomotor impairment, instability in postural control, tonic alterations of the affected musculature, and an array of neurological dysfunctions if left unnoticed. Immersive virtual reality (VR) has emerged as a novel therapeutic tool in stroke rehabilitation, offering engaging and realistic environments for therapy. This study aims to evaluate the effectiveness of immersive VR training combined with functional gait exercises in improving dynamic balance and postural stability in stroke patients, compared to VR training alone. Methods This comparative study included 30 subjects from Madha Medical College and Hospital, Chennai, Tamil Nadu, India, divided into two groups. Group A (n=15) received immersive VR combined with functional gait exercises, while Group B (n=15) received immersive VR alone. Subjects were aged 40-60 years with stable blood pressure and a stroke duration of two weeks to six months. The study spanned 12 weeks, with 30-minute sessions on alternate days. Dynamic balance and postural stability were assessed using the Functional Gait Assessment (FGA) and Falls Efficacy Scale (FES). Pre-test and post-test scores were evaluated using parametric tests. Results Post-test mean values showed significant improvements in both groups. Group A demonstrated greater effectiveness, with lower FES scores (mean 36.66 ± 11.12) than Group B (mean 46.66 ± 9.75). FGA scores were higher in Group A (mean 28.00 ± 0.925) compared to Group B (mean 26.06 ± 1.66). Significant differences were observed in pre-test and post-test values within each group, supporting the hypothesis that combined VR and gait exercises offer superior rehabilitation outcomes. Conclusions Immersive VR combined with functional gait exercises significantly improves dynamic balance and postural stability in stroke patients compared to VR alone. This integrated approach can enhance motor function recovery, increase independence, and improve the quality of life. VR\'s capability to simulate real-life activities and provide immediate feedback allows for personalized rehabilitation programs. Further research is required to validate these findings and optimize VR-based rehabilitation protocols.

BACKGROUND: Falls in older adults are a common and serious threat to health and functional independence. It can cause psychological distress, inability to participate in activities of daily living, brain injury, fractures, and even death. The aim was to analyze the psychometric properties of the self-assessed fall risk scale (FRS) that measures the risk of falls in older adults in a central region of Chile, as well as to verify the concurrent validity against functional fitness tests.
METHODS: A descriptive cross-sectional study was carried out in 222 older adults (OA) [34 males and 188 females] with an age range of 65 to 85 years. The 13-item self-perceived fall risk scale (FRS) was validated. Anthropometric measures (weight, height and waist circumference) were assessed. Five functional fitness tests were measured (right and left hand grip strength, biceps curl, up-and-go, agility and 6-minute walk test). Validation was performed by construct validation [(exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)] and concurrent validity.
RESULTS: The EFA revealed 4 factors in the FRS scale [1: fear of falling (variance 27.1%), 2: use of assistive devices (variance 10.6%), 3: loss of sensation (variance 9.3%), and 4: limited mobility (variance 8.3%)]. Factor loadings ranged from ∼ 0.50 to 0.83 across the 4 components. The Kaiser-Meyer Olkin sample adequacy test (KMO) reflected adequate adequacy (KMO = 0.79, chi-square (X2) = 498.806, gl = 78, p = 0.00). The CFA showed a satisfactory final fit [chi-square (X2) = 126.748, Root mean squared error of approximation (RMSEA) = 0.042, Tucker-Lewis Index (TLI) = 0.946, Comparative fit index (CFI) = 0.935 y Normed fit index (NFI) = 0.90. The relationships between the FRS scale and functional fitness tests (right and left hand grip strength, biceps curl, up-and-go, agility and 6-minute walk test) ranged from low to moderate (r= -0.23 to 0.41).
CONCLUSIONS: The FRS scale showed acceptable validity and reliability in older adults in central region of Chile. It is expected that this scale will be useful for assessing fall risk in clinical and epidemiological settings in the aging Chilean population.

Designing appropriate diagnostic and treatment methods to reduce fall risk and improve quality of life, as well as reduce the cost of care in elderlies. Our findings have potential for early diagnosis of those with a high probability of falling based on fairly simple clinical measures of hyperkyphosis, forward head, and lordosis.
BACKGROUND: Poor balance is an underlying cause of falling in the elderly, for which a change in the natural curvature of the spine plays a major role. Little is known about the relationship between spinal curvatures and fall incidence in this population. We primarily aimed to investigate the relationship between sagittal plane spinal curvatures and fall incidence over 1 year among nursing facility residents. Secondarily, we aim to determine associations of sagittal plane spinal curvatures with participants\' perception of fall risk and balance capability.
METHODS: Participants (100 residents mean age 70.17 ± 6.01 years) underwent standing measures of sagittal plane spinal curvatures (flexible ruler technique) and forward displacement of the head relative to the cervical spine. The Tinetti Performance Oriented Mobility Assessment (POMA) and Fall Efficacy Scale assessed participants\' perception of balance and fear of falling. Incident falls were self-reported monthly and tracked across 1 year. Spearman\'s correlations and logistic regression evaluated associations between fall incidence and spinal curvature. Predictive performance of spinal curvature and fall risk was determined by the corresponding ROC for defining a cut-off for variables of spinal curvature and fall risk indicators.
RESULTS: Predictive performance of spinal curvature and fall risk factors indicated 84% and 77% of participants were correctly classified using models of kyphosis and head angle, respectively.
CONCLUSIONS: Our study adds new data on spinal curvatures and incident falls among nursing facility residents. Efforts are needed to intervene to counter progression of spinal curvatures and improve fall prevention practices.

OBJECTIVE: There are currently no models for predicting hip fractures after stroke. This study wanted to investigate the risk factors leading to hip fracture in stroke patients and to establish a risk prediction model to visualize this risk.
METHODS: We reviewed 439 stroke patients with or without hip fractures admitted to the Affiliated Hospital of Xuzhou Medical University from June 2014 to June 2017 as the training set, and collected 83 patients of the same type from the First Affiliated Hospital of Harbin Medical University and the Affiliated Hospital of Xuzhou Medical University from June 2020 to June 2023 as the testing set. Patients were divided into fracture group and non-fracture group based on the presence of hip fractures. Multivariate logistic regression analysis was used to screen for meaningful factors. Nomogram predicting the risk of hip fracture occurrence were created based on the multifactor analysis, and performance was evaluated using receiver operating characteristic curve (ROC), calibration curves, and decision curve analysis (DCA). A web calculator was created to facilitate a more convenient interactive experience for clinicians.
RESULTS: In training set, there were 35 cases (7.9 %) of hip fractures after stroke, while in testing set, this data was 13 cases (15.6 %). In training set, univariate analysis showed significant differences between the two groups in the number of falls, smoking, hypertension, glucocorticoids, number of strokes, Mini-Mental State Examination (MMSE), visual acuity level, National Institute of Health stroke scale (NIHSS), Berg Balance Scale (BBS), and Stop Walking When Talking (SWWT) (P<0.05). Multivariate analysis showed that number of falls [OR=17.104, 95 % CI (3.727-78.489), P = 0.000], NIHSS [OR=1.565, 95 % CI (1.193-2.052), P = 0.001], SWWT [OR=12.080, 95 % CI (2.398-60.851), P = 0.003] were independent risk factors positively associated with new fractures. BMD [OR = 0.155, 95 % CI (0.044-0.546), P = 0.012] and BBS [OR = 0.840, 95 % CI (0.739-0.954), P = 0.007] were negatively associated with new fractures. The area under the curve (AUC) of nomogram were 0.939 (95 % CI: 0.748-0.943) and 0.980 (95 % CI: 0.886-1.000) in training and testing sets, respectively, and the calibration curves showed a high agreement between predicted and actual status with an area under the decision curve of 0.034 and 0.109, respectively.
CONCLUSIONS: The number of falls, fracture history, low BBS score, high NIHSS score, and positive SWWT are risk factors for hip fracture after stroke. Based on this, a nomogram with high accuracy was developed and a web calculator (https://stroke.shinyapps.io/DynNomapp/) was created.

There is no effective fall risk screening tool for the elderly that can be integrated into clinical practice. Developing a system that can be easily used in primary care services is a current need. Current studies focus on the use of multiple sensors or activities to achieve higher accuracy. However, multiple sensors and activities reduce the availability of these systems. This study aims to develop a system to perform fall prediction for the elderly by using signals recorded from a single sensor during a short-term activity. A total of 168 features in the time and frequency domains were created using acceleration signals obtained from 71 elderly people. The features were weighted based on the ReliefF algorithm, and the artificial neural networks model was developed using the most important features. The best classification result was obtained using the 17 most important features of those weighted for K = 20 nearest neighbors. The highest accuracy was 82.2% (82.9% Sensitivity, 81.6% Specificity). The partially high accuracy obtained in our study shows that falling can be detected early with a sensor and a simple activity by determining the right features and can be easily applied in the assessment of the elderly during routine follow-ups.

In older populations, sensitive fall risk assessment tools are important to timely intervene and prevent falls. Instrumented assessments have shown to be superior to standardized fall risk assessments such as the Timed Up and Go Test (TUG) and should capture both motor and cognitive functions. Therefore, the aim was to test novel instrumented assessments with and without a cognitive component. One hundred thirty-seven older adults aged 73.1 ± 7.3 years, 38 categorized as fallers and 99 as non-fallers, conducted five instrumented assessments on the Dividat Senso, a pressure sensitive stepping platform, and three standardized geriatric assessments (TUG, TUG-dual task, 30-s Sit-to-Stand Test (STS)). T-tests were applied to compare the test performance of fallers versus non-fallers. Furthermore, logistic regression analyses and area under the curve (AUC) analyses were performed. Statistically significant differences between fallers and non-fallers were found in the Go/No-Go test (p = .001, d = .72), the TUG (p = .014, d = .48), and the STS (p = .008, d = .51). Only the Go/No-Go test contributed significantly to all regression models. Significant AUC values were found for the Reaction Time Test (RTT) (AUC = .628, p = .023), Go/No-Go (AUC = .673, p = .002), TUG (AUC = .642, p = .012), and STS (AUC = .690, p = .001). The Go/No-Go test measuring inhibition showed the best discriminative ability suggesting added value of instrumented assessments with a cognitive component for clinical fall risk assessment in relatively healthy older adults. The study should be extended with a frailer population, in which TUG and the other instrumented assessments are possibly good predictors as well.