Is Fall Risk Systematically Evaluated in Memory Clinics? A National Survey of Practice in France

2021 ◽  
pp. 1-9
Author(s):  
Victoire Leroy ◽  
Yaohua Chen ◽  
Naiara Demnitz ◽  
Florence Pasquier ◽  
Pierre Krolak-Salmon ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Standardized Tests ◽  
Fall Risk ◽  
Routine Practice ◽  
Cross Sectional Survey ◽  
Online Questionnaire ◽  
Timed Up And Go ◽  
Major Health Problem ◽  
Fall Risk Assessment ◽  
Memory Clinics

Background: Falls are a major health problem in older persons but are still under-diagnosed and challenging to prevent. Current guidelines do not target high-risk populations, especially people living with dementia. In France, people with neurocognitive disorders are mainly referred to memory clinics (MCs). Objective: We aimed to survey the routine practice of physicians working in MCs regarding fall risk assessment. Methods: We conducted a cross-sectional survey in France from January to May 2019 among physicians working in MCs, through an anonymous online questionnaire: twenty-seven questions about the physician’s background and their practice of fall risk assessment, especially use of clinical and paraclinical tools. We compared the results according to the age and the specialty of the physician. Results: We obtained 171 responses with a majority of women (60%) and geriatricians (78%). All age classes and all French regions were represented. Most of respondents (98.8%) stated that they address gait and/or falls in outpatient clinic and 95.9%in day hospitals. When asked about how they assess fall risk, fall history (83%) and gait examination (68.4%) were the most widely used, while orthostatic hypotension (24%) and clinical standardized tests (25.7%) were less common. Among standardized tests, One-leg Balance, Timed Up and Go Test, and gait speed measurements were the most used. Geriatricians had more complete fall risk assessment than neurologists (e.g., 56%versus 13%for use of standardized tests, p <  0.0001). Conclusion: Almost all physicians addressed the question of fall in MC, but practices are widely heterogeneous. Further investigations are needed to standardize fall risk assessment in MCs.

scholarly journals Fully Automatic Fall Risk Assessment Based on a Fast Mobility Test

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1338
Author(s):  
Wojciech Tylman ◽  
Rafał Kotas ◽  
Marek Kamiński ◽  
Paweł Marciniak ◽  
Sebastian Woźniak ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fall Risk ◽  
Low Cost ◽  
Body Movement ◽  
Sole Source ◽  
Timed Up And Go ◽  
True Negative ◽  
Fall Risk Assessment ◽  
Positive Ratio ◽  
Mobility Test

This paper presents a fall risk assessment approach based on a fast mobility test, automatically evaluated using a low-cost, scalable system for the recording and analysis of body movement. This mobility test has never before been investigated as a sole source of data for fall risk assessment. It can be performed in a very limited space and needs only minimal additional equipment, yet provides large amounts of information, as the presented system can obtain much more data than traditional observation by capturing minute details regarding body movement. The readings are provided wirelessly by one to seven low-cost micro-electro-mechanical inertial measurement units attached to the subject’s body segments. Combined with a body model, these allow segment rotations and translations to be computed and for body movements to be recreated in software. The subject can then be automatically classified by an artificial neural network based on selected values in the test, and those with an elevated risk of falls can be identified. Results obtained from a group of 40 subjects of various ages, both healthy volunteers and patients with vestibular system impairment, are presented to demonstrate the combined capabilities of the test and system. Labelling of subjects as fallers and non-fallers was performed using an objective and precise sensory organization test; it is an important novelty as this approach to subject labelling has never before been used in the design and evaluation of fall risk assessment systems. The findings show a true-positive ratio of 85% and true-negative ratio of 63% for classifying subjects as fallers or non-fallers using the introduced fast mobility test, which are noticeably better than those obtained for the long-established Timed Up and Go test.

scholarly journals Automated fall risk assessment of elderly using wearable devices

2020 ◽  
Vol 7 ◽  
pp. 205566832094620
Author(s):  
Marian Haescher ◽  
Wencke Chodan ◽  
Florian Höpfner ◽  
Gerald Bieber ◽  
Mario Aehnelt ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fall Risk ◽  
Human Error ◽  
Visual Analysis ◽  
Ground Truth ◽  
Wearable Devices ◽  
Healthcare Sector ◽  
Observational Assessment ◽  
Timed Up And Go ◽  
Fall Risk Assessment

Introduction Falls cause major expenses in the healthcare sector. We investigate the ability of supporting a fall risk assessment by introducing algorithms for automated assessments of standardized fall risk-related tests via wearable devices. Methods In a study, 13 participants conducted the standardized 6-Minutes Walk Test, the Timed-Up-and-Go Test, the 30-Second Sit-to-Stand Test, and the 4-Stage Balance Test repeatedly, producing 226 tests in total. Automated algorithms computed by wearable devices, as well as a visual analysis of the recorded data streams, were compared to the observational results conducted by physiotherapists. Results There was a high congruence between automated assessments and the ground truth for all four test types (ranging from 78.15% to 96.55%), with deviations ranging all well within one standard deviation of the ground truth. Fall risk (assessed by questionnaire) correlated with the individual tests. Conclusions The automated fall risk assessment using wearable devices and algorithms matches the validity of the ground truth, thus providing a resourceful alternative to the effortful observational assessment, while minimizing the risk of human error. No single test can predict overall fall risk; instead, a much more complex model with additional input parameters (e.g., fall history, medication etc.) is needed.

scholarly journals Using a Stacked Autoencoder for Mobility and Fall Risk Assessment via Time–Frequency Representations of the Timed Up and Go Test

2021 ◽  
Vol 12 ◽  
Author(s):  
Shih-Hai Chen ◽  
Chia-Hsuan Lee ◽  
Bernard C. Jiang ◽  
Tien-Lung Sun
Keyword(s):  
Risk Assessment ◽  
Fall Risk ◽  
Learning Algorithm ◽  
The Elderly ◽  
Developed Countries ◽  
Mobility Impairment ◽  
Timed Up And Go ◽  
Fall Risk Assessment ◽  
Time Frequency ◽  
Stacked Autoencoder

Fall risk assessment is very important for the graying societies of developed countries. A major contributor to the fall risk of the elderly is mobility impairment. Timely detection of the fall risk can facilitate early intervention to avoid preventable falls. However, continuous fall risk monitoring requires extensive healthcare and clinical resources. Our objective is to develop a method suitable for remote and long-term health monitoring of the elderly for mobility impairment and fall risk without the need for an expert. We employed time–frequency analysis (TFA) and a stacked autoencoder (SAE), which is a deep neural network (DNN)-based learning algorithm, to assess the mobility and fall risk of the elderly according to the criteria of the timed up and go test (TUG). The time series signal of the triaxial accelerometer can be transformed by TFA to obtain richer image information. On the basis of the TUG criteria, the semi-supervised SAE model was able to achieve high predictive accuracies of 89.1, 93.4, and 94.1% for the vertical, mediolateral and anteroposterior axes, respectively. We believe that deep learning can be used to analyze triaxial acceleration data, and our work demonstrates its applicability to assessing the mobility and fall risk of the elderly.

scholarly journals Validity of the GAITRite Walkway Compared to Functional Balance Tests for Fall Risk Assessment in Geriatric Outpatients

Geriatrics ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 77
Author(s):  
Johannes Riis ◽  
Stephanie M. Byrgesen ◽  
Kristian H. Kragholm ◽  
Marianne M. Mørch ◽  
Dorte Melgaard
Keyword(s):  
Risk Assessment ◽  
Dual Task ◽  
Fall Risk ◽  
Timed Up And Go ◽  
Balance Test ◽  
Fall Risk Assessment ◽  
Functional Balance ◽  
Balance Tests ◽  
Gait Parameters ◽  
Task Conditions

This study examined the concurrent validity between gait parameters from the GAITRite walkway and functional balance test commonly used in fall risk assessment. Patients were sampled from one geriatric outpatient clinic. One physiotherapist evaluated the patients on the GAITRite walkway with three repetitions in both single- and dual-task conditions. Patients were further evaluated with Bergs Balance scale (BBS), Dynamic Gait index (DGI), Timed Up and Go (TUG), and Sit To Stand test (STS). Correlations between quantitative gait parameters and functional balance test were analyzed with Spearman’s rank correlations. Correlations strength was considered as follows: negligible <0.1, weak 0.10–0.39, moderate 0.40–0.69, and strong ≥0.70. We included 24 geriatric outpatients in the study with a mean age of 80.6 years (SD: 5.9). Patients received eight (SD: 4.5) different medications on average, and seven (29.2%) patients used walkers during ambulation. Correlations between quantitative gait parameters and functional balance test ranged from weak to moderate in both single- and dual-task conditions. Moderate correlations were observed for DGI, TUG, and BBS, while STS showed weak correlations with all GAITRite parameters. For outpatients analyzed on the GAITRite while using walkers, correlations showed no clear pattern across parameters with large variation within balance tests.

scholarly journals Validity of balance and mobility screening tests for assessing fall risk in COPD

2020 ◽  
Vol 17 ◽  
pp. 147997312092253
Author(s):  
Rachel McLay ◽  
Renata Noce Kirkwood ◽  
Ayse Kuspinar ◽  
Julie Richardson ◽  
Joshua Wald ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fall Risk ◽  
Functional Limitation ◽  
Forced Expiratory Volume ◽  
Screening Tools ◽  
Screening Tests ◽  
Chronic Obstructive ◽  
Timed Up And Go ◽  
Fall Risk Assessment ◽  
Increased Risk

People with chronic obstructive pulmonary disease (COPD) have balance impairments and an increased risk of falls. The psychometric properties of short balance tests to inform fall risk assessment in COPD are unknown. Our objective was to determine the validity (concurrent, convergent, and known-groups) of short balance and mobility tests for fall risk screening. Participants with COPD aged ≥ 60 years attended a single assessment. Correlation coefficients described the relationships between the Brief Balance Evaluation Systems Test (Brief BESTest), Single-Leg Stance (SLS), Timed Up and Go (TUG), and Timed Up and Go Dual-Task (TUG-DT) tests, with the comprehensive Berg Balance Scale (BBS), chair-stand test, and measures of exercise tolerance, functional limitation, disability, and prognosis. Independent t-tests or Mann–Whitney U tests were used to examine differences between groups with respect to fall risk. Receiver operating characteristic curves examined the ability of the screening tests to identify individuals with previous falls. A total of 86 patients with COPD completed the study (72.9 ± 6.8 years; forced expiratory volume in 1 second: 47.3 ± 20.3% predicted). The Brief BESTest identified individuals who reported a previous fall (area under the curve (AUC) = 0.715, p = 0.001), and the SLS showed borderline acceptable accuracy in identifying individuals with a fall history (AUC = 0.684, p = 0.004). The strongest correlations were found for the Brief BESTest and SLS with the BBS ( r = 0.80 and r = 0.72, respectively) and between the TUG and TUG-DT with the chair-stands test ( r = 0.73 and r = 0.70, respectively). The Brief BESTest and SLS show the most promise as balance screening tools for fall risk assessment in older adults with COPD. These tests should be further evaluated prospectively.

Effectiveness of the “Timed Up and Go” (TUG) and the Chair test as screening tools for geriatric fall risk assessment in the ED

2019 ◽  
Vol 37 (3) ◽  
pp. 457-460 ◽  
Author(s):  
Richard B. Chow ◽  
Andre Lee ◽  
Bryan G. Kane ◽  
Jeanne L. Jacoby ◽  
Robert D. Barraco ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fall Risk ◽  
Screening Tools ◽  
Timed Up And Go ◽  
Fall Risk Assessment

scholarly journals Mobility Screening for Fall Risk Assessment in a Population-Based Sample of Older Adults: An Analysis From the CLSA

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 269-269
Author(s):  
Marla Beauchamp ◽  
Ayse Kuspinar ◽  
Nazmul Sohel ◽  
Alexandra Mayhew ◽  
Lauren Griffith ◽  
...  
Keyword(s):  
Older Adults ◽  
Risk Assessment ◽  
Fall Risk ◽  
Population Based ◽  
Community Dwelling ◽  
Receiver Operating Curve ◽  
Inclusion Criteria ◽  
Timed Up And Go ◽  
Fall Risk Assessment ◽  
Acceptable Accuracy

Abstract Existing guidelines for fall prevention in older adults recommend mobility screening for fall risk assessment; however, there is no consensus on which test to use and at what cut-off. This study aimed to determine the accuracy and optimal cut-off values of commonly used mobility tests for predicting falls in the Canadian Longitudinal Study on Aging (CLSA). Mobility tests at baseline included the Timed Up and Go (TUG), Single Leg Stance (SLS), chair-rise, and gait speed test. Inclusion criteria were: age ≥ 65 years and history of a fall or mobility problem at baseline. Accuracy of fall prediction at 18-months for each mobility test was measured by the area under the receiver operating curve (AUC). Of 1,121 participants that met inclusion criteria (mean age 75.2 ± 5.9 years; 66.6% women), 218 (19.4%) participants reported ≥1 fall at 18-months. None of the mobility tests achieved acceptable accuracy for identifying individuals with ≥1 fall at follow-up. Among women 65-74 and 75-85 years, the TUG identified recurrent fallers (≥2 falls) with optimal cut-off scores of 14.1 and 12.9 seconds (both AUCs 0.70), respectively. Among men 65-74 years, only the SLS showed acceptable accuracy (AUC 0.85) for identifying recurrent fallers with an optimal cut-off of 3.6 seconds. Our findings indicate that for a population-based sample of community-dwelling older adults, commonly used mobility tests do not have sufficient accuracy for identifying fallers. The TUG and SLS can identify older adults at risk for recurrent falls, however their accuracy and cut-off values vary by age and sex.

scholarly journals ASSOCIATION BETWEEN COGNITION AND FALL RISK BASED ON THE STEADI ALGORITHM: PROJECT VIBE

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S290-S290
Author(s):  
Tiffany F Hughes ◽  
Cara Carramusa ◽  
Daniel J Van Dussen
Keyword(s):  
Older Adults ◽  
Risk Assessment ◽  
Fall Risk ◽  
Cognitive Status ◽  
Community Dwelling ◽  
Risk Level ◽  
Timed Up And Go ◽  
Fall Risk Assessment ◽  
Risk Of Death ◽  
Lower Likelihood

Abstract Falls are a growing concern among older adults with estimates that one in four fall each year. Older adults who experience a fall are at higher risk for poor health outcomes that threaten independence and increase risk of death. Impairment in cognitive function is known to be associated with greater fall occurrence; however, cognitive testing is not an integral part of clinical fall risk assessment. The purpose of this study is to examine cognitive performance in relation to fall risk level and its components determined using the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) algorithm. One hundred eight community dwelling older adults (mean age 79(SD 7.3) years, 76% women, and 56% college or higher education) were included. Cognition was assessed with the Montreal Cognitive Assessment (MoCA; &gt;= 26 normal). The STEADI algorithm was used to assess fall risk (low vs. moderate/high) based on the Stay Independent screening (&gt;= 4), impairment in gait (Timed Up and Go (TUG)), strength (30-second chair stand), and balance (4-stage balance), and number of falls (&gt;= 2). Associations between cognition and fall risk and its components were assessed using logistic regression adjusting for age, gender, and education. Normal cognitive status was marginally associated with lower likelihood of moderate/high compared to low fall risk (OR 0.42, 95% CI 0.17-1.04), and with a lower likelihood of TUG impairment (OR 0.22, 95% CI 0.07-0.66). These results suggest cognitive status may contribute important information about older adults’ fall risk and should be considered an integral part of fall risk assessment.

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