Fall Risk Groups Research Articles

Two simple modifications to the World Falls Guidelines algorithm improves its ability to stratify older people into low, intermediate and high fall risk groups.

We conducted a secondary analysis of a cohort study to examine the World Falls Guidelines algorithm's ability to stratify older people into sizable fall risk groups or whether minor modifications were necessary to achieve this. Six hundred and ninety-three community-living people aged 70-90years (52.4% women) were stratified into low, intermediate and high fall risk groups using the original algorithm and a modified algorithm applying broader Timed Up and Go test screening with a >10-s cut point (originally >15s). Prospective fall rates and physical and neuropsychological performance among the three groups were compared. The original algorithm was not able to identify three sizable groups, i.e. only five participants (0.7%) were classified as intermediate risk. The modified algorithm classified 349 participants (50.3%) as low risk, 127 participants (18.3%) as intermediate risk and 217 participants (31.3%) as high risk. The sizable intermediate-risk group had physical and neuropsychological characteristics similar to the high-risk group, but a fall rate similar to the low-risk group. The high-risk group had a significantly higher rate of falls than both the low- [incidence rate ratio (IRR) = 2.52, 95% confidence interval (CI) = 1.99-3.20] and intermediate-risk groups (IRR = 2.19, 95% CI = 1.58-3.03). A modified algorithm stratified older people into three sizable fall risk groups including an intermediate group who may be at risk of transitioning to high fall rates in the medium to long term. These simple modifications may assist in better triaging older people to appropriate and tailored fall prevention interventions.

Associations of Usual and Fast Gait Speed With Physical Performance and Balance Confidence in Community-Dwelling Older Adults: Implications for Assessment.

Gait speed is a robust measure that offers many advantages clinically. However, decisions concerning its utilization exist, including whether to assess usual or fast gait speed. The current study aimed to identify whether usual or fast gait speed was more strongly associated with physical performance measures and balance confidence. A secondary aim was to explore these relationships within subgroups based on fall risk status. This was an observational study with a cross-sectional design involving 57 community-dwelling older adults (77.2% female; mean age = 68.8, SD = 6.5 years, range = 60-87 years) who were assessed on the following variables: usual and fast gait speed, knee extension strength, step execution time, 6-minute walk test (6MWT), and Activities-specific Balance Confidence Scale (ABC-6). Spearman ρ correlations were computed to determine bivariate associations of usual and fast gait speed with physical performance measures and balance confidence for the whole sample and within subgroups based on fall risk [lower fall risk (n = 28) vs higher fall risk (n = 29)]. Multiple linear regression models were estimated with either usual or fast gait speed as key predictors of knee extension strength, step execution time, 6MWT, and ABC-6. Stronger correlations were observed for fast gait speed compared with usual gait speed with all physical performance measures and balance confidence for the entire sample and within the higher fall risk group. Multiple regression results indicated that models with fast rather than usual gait speed as the key predictor explained more of the variance in 6MWT ( R2 = 64.5% vs 45.6%), ABC-6 ( R2 = 28.5% vs 25.4%), step execution time ( R2 = 24.9% vs 19.0%), and knee extension strength ( R2 = 15.7% vs 7.2%). Fast gait speed showed stronger associations and better predictive capabilities compared with usual gait speed with physical performance measures and balance confidence in older adults. Despite being measured less often than usual gait speed, fast gait speed assessment warrants additional consideration.

Effects of robot-assisted walking training on balance, motor function, and ADL depending on severity levels in stroke patients.

Despite the explosive increase in interest regarding Robot-Assisted Walking Training (RAWT) for stroke patients, very few studies have divided groups according to the severity levels of patients and conducted studies on the effects of RAWT. The purpose of this study was to present a definite basis for physical therapy using the robot-assisted walking device through a more detailed comparison and analysis and to select the optimal target of RAWT. This study was designed as a prospective and randomized controlled trial to investigate the effect of RAWT on balance, motor function, and Activities of Daily Living (ADL) depending on severity levels in stroke patients. 100 participants were randomly divided into study and control groups in equal numbers. The study group was 49 and the control group was 47. One from the study group and three from the control group were eliminated. The study period is four weeks in total, and RAWT is performed five times a week for 40 minutes only for study group. During the same period, all group members had 30 minutes of Conventional Physiotherapy (CP) five times a week. The results of this study clearly confirmed that RAWT combined with CP produces more significant improvement in patients with stroke than the CP alone. And they indicated that RAWT had a more considerable effect in the poor or fair trunk control group for trunk balance and in the high fall risk group for balance. In motor function, RAWT showed its value in the severe and marked motor impairment group. The total or severe dependence group in ADL experienced more improvements for RAWT. This study can be concluded that the lower the level of physical functions, the more effective it responds to RAWT. As demonstrated in the results of this study, the potential of current robotic technology appears to be greatest at very low functional levels of stroke patients. Patients with low functional levels among stroke patients may benefit from robot rehabilitation.

Fall-risk assessment of aged workers using wearable inertial measurement units based on machine learning

Falls are the major cause of fatal and nonfatal incidents among aged workers. Estimating individual fall risk is crucial for occupational protection and public health. This study aimed to develop a fall-risk assessment method based on Machine Learning (ML) and Inertial Measurement Units (IMUs). A total of 28 aged workers (60 to 80 years old) participated in this study, recruited from community sanitation workers and janitors. They were categorized into high and low fall-risk groups based on functional gait assessment. Each participant performed 5 sets of motion experiments in the lab, covering 6 daily motions. We gathered their kinematic data with IMUs for training ML-based fall-risk assessment models. Five classic ML classifiers were optimized using grid search, and a Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) hybrid deep neural network was built to recognize walking motion from kinematic data for input into the fall-risk assessment model. The results demonstrated that ML classifiers trained with walking motion data exhibited superior performance. Cross-validation revealed that the optimized Random Forest classifier, with IMU on the right upper leg, reached 91.3 % accuracy. Additionally, the CNN-LSTM models were evaluated using F1-score, which can balance accuracy and coverage of model performance evaluation. The CNN-LSTM achieved a maximum F1-score of 95.18 %, proving their effectiveness in extracting walking motion data. These findings indicate that the developed IMU-based ML method exhibits excellent performance in assessing fall risk, potentially allowing aged workers to assess their fall risk before clinical diagnosis by embedding it in wearable IMUs.

Accurate fall risk classification in elderly using one gait cycle data and machine learning

BackgroundFalls among the elderly are a major societal problem. While observations of medium-distance walking using inertial sensors identified potential fall predictors, classifying individuals at risk based on single gait cycles remains elusive. This challenge stems from individual variability and step-to-step fluctuations, making accurate classification difficult. MethodsWe recruited 44 participants, equally divided into high and low fall-risk groups. A smartphone secured on their second sacral spinous process recorded data during indoor walking. Features were extracted at each gait cycle from a 6-dimensional time series (tri-axial angular velocity and tri-axial acceleration) and classified using the gradient boosting decision tree algorithm. FindingsMean accuracy across five-fold cross-validation was 0.936. “Age” was the most influential individual feature, while features related to acceleration in the gait direction held the highest total relative importance when aggregated by axis (0.5365). InterpretationCombining acceleration, angular velocity data, and the gradient boosting decision tree algorithm enabled accurate fall risk classification in the elderly, previously challenging due to lack of discernible features. We reveal the first-ever identification of three-dimensional pelvic motion characteristics during single gait cycles in the high-risk group. This novel method, requiring only one gait cycle, is valuable for individuals with physical limitations hindering repetitive or long-distance walking or for use in spaces with limited walking areas. Additionally, utilizing readily available smartphones instead of dedicated equipment has potential to improve gait analysis accessibility.

Association between advanced glycation end-products and fall risk in older adults: The Yakumo Study.

Advanced glycation end-products (AGEs) are irreversibly and heterogeneously formed compounds during the non-enzymatic modification of macromolecules, such as proteins. Aging and lifestyle habits, such as high-fat and high-protein diets, and smoking, promote AGEs accumulation. This study aimed to investigate the relationship between fall risk and AGEs in community-dwelling older adults. This cross-sectional study included patients from the 2022 Yakumo Study who were evaluated for fall risk index 5-items version, locomotive syndrome stage and AGEs. AGEs were evaluated using Skin autofluorescence (SAF) measured by the AGE reader (DiagnOptics Technologies BV, Groningen, the Netherlands). We divided the participants into two groups according to the presence or absence of fall risk (fall risk index 5-items version ≥6 or not), and investigated the factors associated with fall risk. The fall risk group had a higher age and SAF, and a higher proportion of locomotive syndrome stage >2 than the without fall risk group in patients aged ≥65 years (P < 0.01). The multivariate logistic regression analysis after adjustment of age, sex and body mass index showed that locomotive syndrome stage ≥2 and SAF were independent associators of fall risk in older adults (odds ratio 3.26, P < 0.01, odds ratio 2.96, P < 0.05, respectively). The optimal cutoff value of the SAF for fall risk was 2.4 (area under the curve 0.631; 95% CI 0.53-0.733; sensitivity 0.415; specificity 0.814; P < 0.05). The accumulation of AGEs in skin tissues can be used to screen for fall risk comprehensively. Geriatr Gerontol Int 2024; 24: 517-522.

Impact of sensory reweighting strategies on postural control using the sensory organization test in older adults with and without fall risks.

The Sensory Organization Test (SOT), an integral part of computerized dynamic posturography, plays a crucial role in evaluating postural stability under various altered sensory conditions. Despite its importance, there have been noted inconsistencies in the results pertaining to equilibrium and sensory system evaluations. This study aimed to compare four sensory analysis scores and equilibrium indices between older adults with and without fall risks. The study included 34 participants identified as being at risk of falls and 42 control subjects. To categorize individuals between the two groups, we performed area under the receiver operating characteristic curve analyses. This classification was based on scores from the Modified Falls Efficacy Scale (MFES) and the composite scores obtained from the SOT. In addition, we used the Tampa Scale for Kinesiophobia (TSK) as well as the level of disability. The fall risk group demonstrated significantly higher TSK scores (39.39± 15.24 for control group vs. 54.65±10.70 for fall risk group; t=-5.09, p=0.001). The groups demonstrated a significant interaction on the equilibrium index (F=4.59, p=0.03), which was lower in the fall risk group in Condition 6 with a moving surface and surround and eyes open (t=2.29, p=0.01). The fall risk group demonstrated a higher somatosensory score (t=-1.73, p=0.04). The fall risk group had a lower equilibrium index score in Condition six of the SOT, which was useful for identifying deficits in vestibular function to integrate sensory information under challenging conditions for postural adaptation. This strategy suggested that the fall risk group could compensate for their risk of falls by utilizing more effective somatosensory reweighting strategies compared with the control group.

Risk of falls is associated with 30-day mortality among older adults in the emergency department

ObjectiveFalls in older adults correlate with heightened morbidity and mortality. Assessing fall risk in the emergency department (ED) not only aids in identifying candidates for prevention interventions but may also offer insights into overall mortality risk. We sought to examine the link between fall risk and 30-day mortality in older ED adults. MethodsObservational cohort study of adults aged ≥ 75years who presented to an academic ED and who were assessed for fall risk using the Memorial Emergency Department Fall Risk Assessment Tool (MEDFRAT), a validated, ED-specific screening tool. The fall risk was classified as low (0–2 points), moderate (3–4 points), or high (≥5) risk. The primary outcome was 30-day mortality. Hazard ratios (HR) with 95% confidence intervals (CIs) were calculated. ResultsA total of 941 patients whose fall risk was assessed in the ED were included in the study. Median age was 83.7 years; 45.6% were male, 75.6% lived in private residences, and 62.7% were admitted. Mortality at 30 days among the high fall risk group was four times that of the low fall risk group (11.8% vs 3.1%; HR 4.00, 95% CI 2.18 to 7.34, p < 0.001). Moderate fall risk individuals had nearly double the mortality rate of the low-risk group (6.0% vs 3.1%), but the difference was not statistically significant (HR 1.98, 95% CI 0.91 to 4.32, p = 0.087). ConclusionED fall risk assessments are linked to 30-day mortality. Screening may facilitate the stratification of older adults at risk for health deterioration.

Stair-Fall Risk Parameters in a Controlled Gait Laboratory Environment and Real (Domestic) Houses: A Prospective Study in Faller and Non-Faller Groups.

Falling on stairs is a major health hazard for older people. Risk factors for stair falls have been identified, but these are mostly examined in controlled biomechanics/gait laboratory environments, on experimental stairs with a given set of step dimensions. It remains unknown whether the conclusions drawn from these controlled environments would apply to the negotiation of other domestic staircases with different dimensions in real houses where people live. The aim of this paper is to investigate whether selected biomechanical stepping behavior determined through stair gait parameters such as foot clearance, foot contact length and cadence are maintained when the staircase dimensions are different in real houses. Twenty-five older adults (>65 years) walked on a custom-made seven-step laboratory staircase. Older adults were classified into two groups (fallers and non-fallers) based on recent fall history. Among the 25 participants, 13 people had at least one fall, trip, or slip in the last six months and they were assigned to the fallers group; 12 people did not experience any fall in the last six months, so they were assigned to the non-fallers group. In addition, these participants walked on the stairs in three different real exemplar houses wearing a novel instrumented shoe sensor system that could measure the above stair gait parameters. MATLAB was used to extract fall risk parameters from the collected data. One-way ANOVA was used to compare fall risk parameters on the different staircases. In addition, the laboratory-based fall risk parameters were compared to those derived from the real house stairs. There was a significant difference in selected stair-fall biomechanical risk factors among the house and laboratory staircases. The fall risk group comparisons suggest that high-risk fallers implemented a biomechanically riskier strategy that could increase overall falling risk. The significant differences due to the main effects of the fallers and non-fallers groups were obtained. For example, when ascending, the fallers group had less foot clearance on the entry (p = 0.016) and middle steps (p = 0.003); in addition, they had more foot clearance variability on the entry steps (p = 0.003). This suggests that the fallers group in this present study did not adopt more conservative stepping strategies during stair ascent compared to low-risk older adults. By showing less foot clearance and more variability in foot clearance, the risk for a trip would be increased.

A multifactorial fall risk assessment system for older people utilizing a low-cost, markerless Microsoft Kinect

Falls among older people are a major health concern. This study aims to develop a multifactorial fall risk assessment system for older people using a low-cost, markerless Microsoft Kinect. A Kinect-based test battery was designed to comprehensively assess major fall risk factors. A follow-up experiment was conducted with 102 older participants to assess their fall risks. Participants were divided into high and low fall risk groups based on their prospective falls over a 6-month period. Results showed that the high fall risk group performed significantly worse on the Kinect-based test battery. The developed random forest classification model achieved an average classification accuracy of 84.7%. In addition, the individual’s performance was computed as the percentile value of a normative database to visualise deficiencies and targets for intervention. These findings indicate that the developed system can not only screen out ‘at risk’ older individuals with good accuracy, but also identify potential fall risk factors for effective fall intervention. Practitioner summary: Falls are the leading cause of injuries in older people. We newly developed a multifactorial fall risk assessment system for older people utilising a low-cost, markerless Kinect. Results showed that the developed system can screen out ‘at risk’ individuals and identify potential risk factors for effective fall intervention.

The effects of optic flow on postural stability: Influence of age and fall risk

BackgroundOptic flow provides dynamic information relating to body position and motion with respect to visual frames of reference. This study investigated the effects of optic flow stimuli presented in four directions on postural stability in young and older adults. MethodsTwenty-five young (20–40 years) and 51 older (≥65 years) people participated in this study, with the older group classified into low fall risk (n = 27), and high fall risk (n = 24) sub-groups. While standing in a dark room, participants viewed static scattered white dots for 30 s, followed by 30 s periods of optic flow consisting of white dots “moving” in one of four flow directions, randomised: radial expansion and contraction, circular anti-clockwise and clockwise. Centre of pressure (CoP) position, postural sway in anteroposterior (AP) and mediolateral (ML) axes, and muscle activity of tibialis anterior (TA), gastrocnemius medialis (GM) and tensor fascia latae (TFL) were recorded. ResultsAcross groups, the four optic flow stimuli induced increased AP sway and three of the four optic flow stimuli induced increased ML sway, with concomitant increases in muscle activity, indicating optic flow stimuli induced a generalised destabilising, rather than a direction-specific, effect. Only one optic flow condition (radial contraction) induced a change in average CoP position, and this may reflect the adoption of a protective stance position to avoid a backward fall. Optic flow destabilised postural control more in older people compared with younger people, and radial expansion stimuli destabilised ML postural control more in the older high fall risk group compared with the older low fall risk group. ConclusionOptic flow stimuli have a generalised destabilising effect on postural control across groups as shown by non-directional specific increases in postural sway and muscular activity. Optic flow stimuli have a greater impact on postural stability in older compared with younger adults and this is more pronounced in the ML plane for older people at increased risk of falls.

Revealing the tension: The relationship between high fall risk categorization and low patient mobility.

Using an inpatient fall risk assessment tool helps categorize patients into risk groups which can then be targeted with fall prevention strategies. While potentially important in preventing patient injury, fall risk assessment may unintentionally lead to reduced mobility among hospitalized patients. Here we examined the relationship between fall risk assessment and ambulatory status among hospitalized patients. We conducted a retrospective cohort study of consecutively admitted adult patients (n=48,271) to a quaternary urban hospital that provides care for patients of broad socioeconomic and demographic backgrounds. Non-ambulatory status, the primary outcome, was defined as a median Johns Hopkins Highest Level of Mobility <6 (i.e., patient walks less than 10 steps) throughout hospitalization. The primary exposure variable was the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) category (Low, Moderate, High). The capacity to ambulate was assessed using the Activity Measure for Post-Acute Care (AM-PAC). Multivariable regression analysis controlled for clinical demographics, JHFRAT items, AM-PAC, comorbidity count, and length of stay. 8% of patients at low risk for falls were non-ambulatory, compared to 25% and 54% of patients at moderate and high risk for falls, respectively. Patients categorized as high risk and moderate risk for falls were 4.6 (95% CI: 3.9-5.5) and 2.6 (95% CI: 2.4-2.9) times more likely to be non-ambulatory compared to patients categorized as low risk, respectively. For patients with high ambulatory potential (AM-PAC 18-24), those categorized as high risk for falls were 4.3 (95% CI: 3.5-5.3) times more likely to be non-ambulatory compared to patients categorized as low risk. Patients categorized into higher fall risk groups had decreased mobility throughout their hospitalization, even when they had the functional capacity to ambulate.

Recurrence quantification analysis of center of pressure trajectories for balance and fall-risk assessment in young and older adults.

The prevalence and impact of balance impairments and falls in older adults have motivated several studies on the characterization of human balance. This study aimed to determine the ability of recurrence quantification analysis (RQA) measures to characterize balance control during quiet standing in young and older adults and to discriminate between different fall risk groups. We analyze center pressure trajectories in the medial-lateral and anterior-posterior directions from a publicly available static posturography dataset that contains tests acquired under four vision-surface testing conditions. Participants were retrospectively classified as young adults (age<60, n=85), non-fallers (age≥60, falls=0, n=56), and fallers (age≥60, falls≥1, n=18). Mixed ANOVA and post hoc analyzes were performed to test for differences between groups. For CoP fluctuations in the anterior-posterior direction, all RQA measures showed significantly higher values for young than older adults when standing on a compliant surface, indicating less predictable and stable balance control among seniors under testing conditions where sensory information is restricted or altered. However, no significant differences between non-fallers and fallers were observed. These results support the use of RQA to characterize balance control in young and old adults, but not to discriminate between different fall risk groups.

Plantar pressure and falling risk in older individuals: a cross-sectional study

BackgroundFalls are commonplace among elderly people. It is urgent to prevent falls. Previous studies have confirmed that there is a difference in plantar pressure between falls and non-falls in elderly people, but the relationship between fall risk and foot pressure has not been studied. In this study, the differences in dynamic plantar pressure between elderly people with high and low fall risk were preliminarily discussed, and the characteristic parameters of plantar pressure were determined.MethodsTwenty four high-fall-risk elderly individuals (HR) and 24 low-fall-risk elderly individuals (LR) were selected using the Berg Balance Scale 40 score. They wore wearable foot pressure devices to walk along a 20-m-long corridor. The peak pressure (PP), pressure time integral (PTI), pressure gradient (maximum pressure gradient (MaxPG), minimum pressure gradient (MinPG), full width at half maximum (FWHM)) and average pressure (AP) of their feet were measured for inter-group and intra-group analysis.ResultsThe foot pressure difference comparing the high fall risk with low fall risk groups was manifested in PP and MaxPG, concentrated in the midfoot and heel (p < 0.05), while the only time parameter, FWHM, was manifested in the whole foot (p < 0.05). The differences between the left and right foot were reflected in all parameters. The differences between the left and right foot in LR were mainly reflected in the heel (p < 0.05), while it in the HR was mainly reflected in the forefoot (p < 0.05).ConclusionsThe differences comparing the high fall risk with low fall risk groups were mostly reflected in the midfoot and heel. The HR may have been more cautious when landing. In the intra-group comparison, the difference between the right and left foot of the LR was mainly reflected during heel striking, while it was mainly reflected during pedalling in the HR. The sensitivity of PP, PTI and AP was lower and the newly introduced pressure gradient could better reflect the difference in foot pressure between the two groups. The pressure gradient can be used as a new foot pressure parameter in scientific research.

Association between locomotive syndrome and fall risk in the elderly individuals in Japan: The Yakumo study

BackgroundPatients with locomotive syndrome (LS) are poor ambulatory status and a high risk of requiring nursing care. The purpose of this study is to investigate the relationship between LS and fall risk among community-dwelling elderly individuals. MethodsThe subjects were Japanese elderly individuals aged 65 and over who participated in Yakumo study 2019 (N = 189). We defined the fall risk index 5 items version (FRI-5) ≥6 points as the fall risk group. LS was evaluated by stand-up test, two-step test, and 25-Geriatric Locomotive Function Scale (GLFS-25). We divided the subjects into two groups according to the presence or absence of fall risk, and investigated factors associated with fall risk. ResultsThe fall risk group (30 patients, 15.9%) had higher GLSF-25 (P = 0.001). The results of logistic regression analysis adjusted for age, sex, BMI, and knee osteoarthritis revealed that GLFS-25 (OR: 1.052; 95%CI: 1.009–1.097) was independent factor associated with fall risk. In the ROC analysis, the optimal cut-off value of the GLFS-25 to predict fall risk was 12, which is equivalent to LS stage 1 (AUC 0.688; 95% CI: 0.588–0.787; sensitivity: 0.467, specificity: 0.836). ConclusionsGLFS-25 was associated with fall risk among community-dwelling elderly individuals aged 65 and over.

Development of an effective clustering algorithm for older fallers.

Falls are common and often lead to serious physical and psychological consequences for older persons. The occurrence of falls are usually attributed to the interaction between multiple risk factors. The clinical evaluation of falls risks is time-consuming as a result, hence limiting its availability. The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. Data from the Malaysian Elders Longitudinal Research (MELoR), comprising 1411 subjects aged ≥55 years, were utilized. The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. A total of 1279 subjects and 9 variables were selected for clustering after the data pre-possessing stage. Using feature extraction with the t-SNE and the K-means clustering algorithm, subjects were clustered into low, intermediate A, intermediate B and high fall risk groups which corresponded with fall occurrence of 13%, 19%, 21% and 31% respectively. Slower gait, poorer balance, weaker muscle strength, presence of cardiovascular disorder, poorer cognitive performance, and advancing age were the key variables identified. The proposed fall risk clustering algorithm grouped the subjects according to features. Such a tool could serve as a case identification or clinical decision support tool for clinical practice to enhance access to falls prevention efforts.

Physical Activity and Fall Prevention in Geriatric Inpatients in an Acute Care Unit (AGIR Study): Protocol for a Usability Study

BackgroundFalls are one of the world’s top 10 risks associated with disability in people older than 60 years. They also represent more than two-thirds of adverse events in hospitals, mainly affecting patients older than 65 years. Physical activity is a central intervention in fall prevention for older people. Whatever the details of the prevention strategy that is adopted (ie, how a mono- or multifactorial intervention is evaluated, the category of person the intervention targets, and where it is used), it is important to ensure that the proposed intervention is feasible and usable for the patient and the health care team.ObjectiveThe primary objective is to study the usability of carrying out a physical activity intervention, including 3 types of exercises, in older patients hospitalized in a geriatric acute care unit and categorized according to 3 fall risk levels: low, moderate, and high. The secondary objectives are to determine the difficulty of the physical exercise for patients with different fall risk levels, to study the health care team’s perceptions of the intervention’s feasibility, and to study the benefits for patients.MethodsThis is an open-label, unicenter, nonrandomized, usability prospective clinical trial. The intervention tested is a daily physical activity program. It consists of 3 types of physical exercise: staying out of bed for at least 3 hours, performing balance exercises while standing for 2 minutes, and the Five Times Sit to Stand transfer exercise. These exercises are carried out under the supervision of the health care team. Fall risk in the patients is classified with the Brief Geriatric Assessment tool. The exercise program starts on the second day of hospitalization after inclusion in the study. Patient assessment continues until the last day of hospitalization or the 20th day of hospitalization, whichever is earlier. For each fall-risk group and each type of exercise, the intervention will be defined as usable if at least 80% of the participants complete 75% or more of the exercises (ie, the ratio between the number of days when the patient completes a type of exercise and the total number of hospitalization days). The perceived feasibility by the health care team is measured with 2 scales, measuring perceived difficulty and time spent with the patient. The intervention benefit is evaluated using the performance of the Five Times Sit to Stand test before and after the intervention.ResultsThe first patient was recruited on March 16, 2015. The study enrolled 266 patients, including 75 with low fall risk, 105 with moderate risk, and 85 with high risk.ConclusionsWe have not yet analyzed the results, but our observations suggest that the usability of each type of exercise for a given patient will depend on their fall risk level.Trial RegistrationClinicalTrials.gov NCT02393014; https://clinicaltrials.gov/ct2/show/NCT02393014International Registered Report Identifier (IRRID)DERR1-10.2196/32288

The role of comprehensive geriatric assessment in predicting fall risk.

The prevention of falls among older adults is one of the most important public health issues in today's aging society. There are many factors significantly affecting the risk of falls. This study aimed to investigate the factors on fall risk in older adults. A total of 335 elderly outpatients aged 65 and over were included in this cross-sectional study. Comprehensive geriatric assessment was performed on the participants. Tinetti Balance and Gait Assessment Tool (TBGA) and Mini-Mental State Examination (MMSE) were used to assess fall risk and cognitive functions, respectively. The mean age of 335 participants was 72.1 ± 6.0years and 55.2% was female. Of the participants, 40.6% had a moderate-high fall risk according to TBGA and 31.6% had a history of falls within the last year. Although there was no significant difference in MMSE results between the medium-high fall risk group and the low fall risk group, higher MMSE attention and calculation domain score was found to be an independent variable for decreased fall risk and sarcopenia for increased fall risk (p = 0.039, OR = 0.70 and p = 0.037, OR = 3.43, respectively). The role of sarcopenia in fall risk is well established. In this study, we also showed that attention and calculation play important roles in fall risk. Elderly individuals with low scores in attention and calculation domains need a more detailed assessment in terms of fall risk, even if cognitive functions are considered normal according to the MMSE.

The Fall Risk Screening Scale Is Suitable for Evaluating Adult Patient Fall.

(1) Background: This study aimed to test the feasibility of utilizing the screening tool for fall risk assessment in adult inpatient and verify its accuracy in a medical center in Taiwan. (2) Methods: This study retrospectively collected all adult fall cases among inpatients occurring in the general wards of a medical center between 1 January 2013 and 31 December 2015. This inpatient fall risk screening scale was measured by the sensitivity, specificity, and accuracy. (3) Results: There were 1331 (0.4%) falls among a total of 357,395 inpatients during this period. Factors predictive of falling risk included: age, consciousness, body shift assistance, use of fall risk medications, fall history, dizziness or weakness, toileting, and impaired mobility. Using the eight-factor assessment, two was the best cutoff point for identifying the fall risk group, with area under Receiver Operating Characteristic (ROC) curve (AUC) = 0.817, sensitivity = 80.93%, specificity = 73.0%, accuracy = 73.03%, and likelihood ratio = 11.48. (4) Conclusions: The accuracy of the eight-item fall risk assessment tool created for this study was validated. These results can serve as a reference for institutions to develop more effective fall risk assessment scale for inpatients, enabling clinical nurses to identify and more comprehensively assess the groups at highest risk for falling during their hospital stay.

Risk Factors according to Fall Risk Level in General Hospital Inpatients

Purpose: This study was conducted to identify the predictors of falls according to the fall risk level in general hospital inpatients.Methods: Data were extracted from electronic medical records from January 2017 to December 2019. This study included 170 fallers and 340 non-fallers, who were matched for gender, age, clinical department, and length of stay before falls among inpatients aged 18 years and over. The collected data were analyzed with the x2 test, Fisher exact test, independent t-test, and logistic regression analysis using SPSS for Windows version 24.0.Results: In the low-risk group, defecation disorder (odds ratio [OR]=12.49, 95% confidence interval [CI]=1.16~134.33, p=.037) and laxative use (OR=9.62, 95% CI=2.14~43.22, p=.003) were statistically significant risk factors for falls. In the medium-risk group, disorientation (OR=2.40, 95% CI=1.11~5.19, p=.026) was a statistically significant risk factor for falls. In the high-risk group, disorientation (OR=12.54, 95% CI=1.39~113.26, p=.024) and hypoglycemic agent use (OR=5.39, 95% CI=1.58~18.44, p=.007) were statistically significant risk factors for falls.Conclusion: The results of this study show that risk factors for falls differed among the fall risk groups. It is necessary to use fall prevention strategies tailored to fall risk groups and fall risk assessment tools that have been revised accordingly.