Fall-related Injuries Research Articles

Design and Implementation of an Inpatient Fall Risk Management Information System.

Falls had been identified as one of the nursing-sensitive indicators for nursing care in hospitals. With technological progress, health information systems make it possible for health care professionals to manage patient care better. However, there is a dearth of research on health information systems used to manage inpatient falls. This study aimed to design and implement a novel hospital-based fall risk management information system (FRMIS) to prevent inpatient falls and improve nursing quality. This implementation was conducted at a large academic medical center in central China. We established a nurse-led multidisciplinary fall prevention team in January 2016. The hospital's fall risk management problems were summarized by interviewing fall-related stakeholders, observing fall prevention workflow and post-fall care process, and investigating patients' satisfaction. The FRMIS was developed using an iterative design process, involving collaboration among health care professionals, software developers, and system architects. We used process indicators and outcome indicators to evaluate the implementation effect. The FRMIS includes a fall risk assessment platform, a fall risk warning platform, a fall preventive strategies platform, fall incident reporting, and a tracking improvement platform. Since the implementation of the FRMIS, the inpatient fall rate was significantly lower than that before implementation (P<.05). In addition, the percentage of major fall-related injuries was significantly lower than that before implementation. The implementation rate of fall-related process indicators and the reporting rate of high risk of falls were significantly different before and after system implementation (P<.05). The FRMIS provides support to nursing staff in preventing falls among hospitalized patients while facilitating process control for nursing managers.

Fall-related injury among patients with vestibular schwannoma.

Vestibular schwannoma can cause vestibular dysfunction; however, conflicting evidence exists regarding whether this affects the incidence of fall-related injuries in this patient population. This matched cross-sectional and cohort study assess the risk of fall-related injuries in patients with vestibular schwannoma. The study included patients with vestibular schwannoma treated at a tertiary referral hospital in Sweden between 1988 and 2014. Information on fall-related injuries was obtained from the National Patient Register, and matched population comparisons were randomly selected in a 1:25 ratio. Fall-related injuries occurring pre- (within 5 years before the diagnosis of vestibular schwannoma) and post-diagnostically (up to 3 years after diagnosis or intervention) were registered. The association between vestibular schwannoma and fall-related injuries was estimated using logistic regression and Cox proportional hazards analyses. We identified 1153 patients with vestibular schwannoma (569 [49%] women and 584 [51%] men), and 28815 population comparisons. Among the patients, 9% and 7% had pre- and post-diagnostic fall-related injuries, respectively, and among the comparisons, 8% and 6% had pre- and post-diagnostic fall-related injuries, respectively. There was no increased risk of pre- (OR 1.14; CI 0.92-1.41) or post-diagnostic 1 year (HR 1.16; CI 0.87-1.54) or 3 years (HR 1.11; CI 0.89-1.29) fall-related injury among the total patient cohort. In age-stratified analyses, we found an increased risk of pre-diagnostic fall-related injury among patients aged 50-69 years (OR 1.42; CI 1.10-1.88). Patients who underwent middle fossa surgery, regardless of age, had an increased risk of post-surgery fall-related injury within 3 years of follow-up (HR 2.68; CI 1.06-6.81). We conclude that patients with vestibular schwannoma have a low risk of enduring fall-related injuries. Middle-aged patients with dizziness and fall-related injuries should be considered for a vestibular clinical evaluation. Our results highlight the importance of rehabilitation in avoiding future fall-related injuries among patients undergoing middle fossa surgery.

Sedentary Behaviour and Fall-related Injuries in Aging Adults: Results from the Canadian Longitudinal Study on Aging (CLSA).

Falls, and more specifically, fall-related injuries, are costly to the healthcare system and can harm one's autonomy. To study the impact of sedentary behaviour associated with fall-related injuries and how a change in sedentary behaviour may impact the risk of a fall-related injury. From baseline to the first follow-up, cross-sectional and longitudinal data analysis from the Canadian Longitudinal Study of Aging (CLSA) cohort. CLSA data from 43,558 Canadians aged 45-85 were included in this study. At baseline and follow-up, sedentary behaviour time was categorized as low (<1,080 minutes/week), moderate (1,080-1,440), or high (>1,440). Sedentary behaviour was estimated via the Physical Activity Scale for the Elderly (PASE). At follow-up, participants were dichotomized as either increased or decreased/no change in sedentary behaviour according to their categorical change between time points. Sedentary behaviour was associated with fall-related injuries independently of age, sex, number of chronic conditions, and total physical activity levels OR (95%CI) 1.10 (1.05-1.15). In contrast, a change in sedentary behaviour was not associated with the risk of fall-related injury 1.00 (0.92-1.01). A higher level of sedentary behaviour is associated with injurious falls for people between 40 and 80 years old. However, a short-term change in sedentary behaviour does not influence the risk of injury-related falls. Despite the results, a more precise measure of sedentary behaviour is needed for epidemiology studies to capture changes over time better.

Severity of Fall-Related Injuries and Older Persons' Hospital Admission in Kuwait: A Cross-Sectional Study.

Falls among the older population have attracted global attention, with a specific emphasis on the regional contexts of falls. This study reports the incidence and characteristics of falls in the State of Kuwait, where there is currently no national fall prevention strategy. A prospective, cross-sectional study reported on 420 individuals aged 55 years and above admitted to Alrazi Orthopaedic Hospital in Kuwait City due to falls between March 2022 and February 2023. ICD-10 codes were used to classify the fall causes. The National Database of Nursing Quality Indicators injury severity classification was used to classify the fall-related injuries. Structured interviews were used to identify 10 main fall risk factors. Annual fall-rate was calculated and fall-related injuries were reported in frequencies and percentages. Chi-square tests and multinomial logistic regression models were used to examine the cross-sectional associations between fall severity and risk factors to determine the factors that could predict more severe fall-related injuries. Fall-related injuries comprised 24.1% of the total hospital admissions, with 4% mortality rate. Around 31.6% of the falls led to temporary impairment injuries, 23.5% resulted in long-term impairment injuries, and 44.8% created potentially fatal injuries. The results of this study show that being between 55 and 74 years of age, having no history of falls, suffering from at least one illness, with no polypharmacy effect, and possessing fair vision are significantly associated with the severity of fall injuries. Being male (odds ratio [OR] = 3.38), being over 65 years of age (OR = 3.46), having a history of falls (OR = 2.49), and limitations in visual acuity predict more severe fall injuries among older individuals. The severity of fall injuries is significantly associated with more capable older people. Government officials should immediately design and implement culture-specific fall-prevention strategies tailored to the targeted population.

Gender differences in the incidence, characteristics and hospital admission outcomes of fall-related injuries in older adults in Victoria, Australia, over 5 years from 2018/19 to 2022/23.

Falls are the leading cause of injury morbidity and mortality in older adults. This study aimed to: (1) Explore gender differences in falls injury incidence and outcomes in Victoria, Australia; and (2) Test if these differences are explained by patient demographics and clinical complexity. Fall-related injury admissions records from 1-JULY-2018 to 30-JUNE-2023 were extracted from the Victorian Admitted Episodes Dataset. Admissions for injury (S00-T98) caused by a fall (W00-W19), in males and females aged 60+ years, were selected using ICD-10-AM codes. Incidence was calculated as annual falls admissions per 100,000 population. Gender differences in terms of demographics, falls details, injury types, complexity and admission outcomes were tested using logistic regression models. There were 187,878 fall-related injury admissions: 67,635 (36.0%) by males and 120,243 (64.0%) by females. The incidence rate ratio peaked at 1.52 (female: male) at 70-79 years. Compared to males, female fall injuries were more likely due to same-level falls and to occur at home. Female sex was associated with fractures and male sex was associated with head injuries. Although female sex was associated with surgery and longer hospital stay, death-in-hospital was associated with male sex, with and without adjustment for patient demographics, fall details, injury type and clinical complexity. This contemporary gender-stratified study provides important evidence relevant to falls prevention and management. The findings suggest that same-level falls prevention is of particular relevance to females while in males, improved hospital outcomes and fall-related injury survivability, and any underlying frailty, should be prioritized.

Memory Loss and Missteps: Investigating Fall Risks in Alzheimer's and Dementia Patients.

Degenerative diseases such as Alzheimer's disease and dementia are significant health concerns among older adults in the United States, contributing substantially to the high incidence of falls in this population. This study aims to investigate the incidence and prevalence of falls among older adults diagnosed with Alzheimer's disease and dementia and explore the association between these conditions and the occurrence of traumatic brain injuries (TBIs). A retrospective cohort study was conducted using data from 17,000 older adults aged 65 and above, arrived at the hospital with fall related injuries, obtained from the TriNetX network at Virginia Commonwealth University Health System (VCUHS) between January 1, 2019, and December 31, 2023. Data included demographic information, diagnosis codes (ICD-10), and details on falls, Alzheimer's disease, dementia, and TBIs. Descriptive statistics and logistic regression analyses were performed using TriNetX analytical tools. Older adults with Alzheimer's disease (incidence proportion: 3.11%, prevalence: 4.81%) and dementia (incidence proportion: 12.46%, prevalence: 17.06%) had a significantly higher incidence of falls compared to those without these conditions. Females showed a slightly higher incidence of falls than males. Logistic regression analysis indicated that patients with Alzheimer's disease had a reduced risk of TBIs (OR = 0.765, 95% CI: 0.588-0.996, p = 0.047), while those with unspecified dementia had an increased risk (OR = 1.161, 95% CI: 1.002-1.346, p = 0.047). Our study reveals a higher risk of falls and traumatic brain injuries (TBIs) in older adults with dementia compared to those with Alzheimer's disease. These findings underscore the need for targeted fall prevention strategies and educational programs for caregivers.

Ab. No. 73 Effect of Otago Exercise Program Via Tele Rehabilitation on Fall Risk and Balance in Older People

Introduction: To find the effect of Otago exercise program via telerehabilitation on fall risk and balance in older people. Older people’s falls and fall-related injuries have grown to be major health issue. Otago Exercise Program (OEP) consists of 17 strength and balance exercises and walking program at home, outpatient or community setting that is effective in preventing falls. Telerehabilitation is newer technique of delivery of rehabilitation services over telecommunication networks. Methods: 44 gender-matched participants aged 65-80 (71 + 4.3) years were divided into two groups using simple random sampling. People unwilling to participate were excluded. Ethics approval was obtained. A prospective follow-up study was carried out in community of Ahmedabad. Participants were explained the study. Fall risk was measured using Timed Up and Go(TUG) test and balance was measured using Berg Balance Scale(BBS). Group A (n=22) was given telerehabilitation-based OEP via zoom calls and Group B (n=22) was given unsupervised OEP at home. A total of 12 sessions (3 sessions/week) of OEP and (2 times/week) walking for 4 weeks was administered. Within group analysis for TUG was done using Paired samples T-test and for BBS using Wilcoxon signed rank test. Between group analysis was carried out using Mann-Whitney U test. Level of significance was kept at 5%. Results: Within group analysis showed statistically significant difference in group A TUG (t=14.96, p&lt;0.0001), BBS (Z=-4.135, p&lt;0.0001), in group B TUG (t=3.375, p=0.003), BBS(Z=-3.71, p&lt;0.0001). Between group analysis showed statistically significant difference in BBS (U=34.5, p&lt;0.0001) but not in TUG (U=191.5, p=0.211). Conclusion: Otago Exercise program is effective via telerehabilitation and as home-based program to improve balance and reduce fall risk. Tele-rehabilitation group was more effective in improving balance. Implications: Tele-rehabilitation can be used for older people by providing convenient, one-to-one, accessible healthcare services at home reducing travel.

Nomogram for Predicting the Risk Factors for Falls in Older People: A Secondary Data Analysis Based on the 2021 Community Health Survey.

This study aimed to identify the risk factors for falls among older individuals living at home in a community and develop a nomogram to predict falls. This study included 74 492 people aged 65 years or older who participated in the 2021 Community Health Survey conducted in Korea. The data analysis methods used included the Rao-Scott χ2 test, a complex sample t-test, and complex binary logistic regression using SPSS 26.0. Using logistic regression analysis, a fall-risk prediction nomogram was created based on regression coefficients, and the reliability of the nomogram was calculated using a receiver operating characteristic (ROC) curve and values of the area under the curve (AUC). The fall incidence rate among older adults was 16.4%. Factors affecting the subject's fall experience included being more than 85 years old (OR = 1.40); living alone (OR = 1.13); receiving basic welfare (OR = 1.18); subjective health status (OR = 1.72); number of days spent walking (OR = 0.98); obesity (OR = 1.08); severe depression (OR = 2.84); sleep duration time (OR = 1.11); experiencing cognitive decline (OR = 1.34); and diabetes (OR = 1.12). In the nomogram, the depression score exhibited the greatest discriminatory power, followed by subjective health status, gender, experience of cognitive decline, age, basic livelihood security, adequacy of sleep, living alone, diabetes, and number of days of walking. The AUC value was 0.66. An intervention plan that comprehensively considers physical, psychological, and social factors is required to prevent falls in older adults. The nomogram developed in this study will help local health institutions assess all these risk factors for falling and create and implement systematic education and intervention programs to prevent falls and fall-related injuries among older individuals.

Design and Testing of an Active Balancing Board for Exergames

In recent years, there has been a growing recognition of the importance of balance and coordination in maintaining overall health, particularly among the elderly population. As societies around the world experience demographic shifts with an increasing number of elderly individuals, age-related declines in balance and coordination can lead to an elevated risk of falls and fall-related injuries, making it a significant public health concern. The need for effective balance rehabilitation and fall prevention strategies has become paramount. This paper presents a motion platform designed for balance rehabilitation exercises using exergames. The system consists of a 3 degrees of freedom (3DOF) platform actuated by four servomotors controlled by Omron-DeltaTau real-time motion controller. As a novelty with respect to other State of Art (SoA) actuated platforms, in the present work the movements of the user's body, which determine the platform motion, are tracked by exploiting a markerless motion capture system with an RGB camera and pose-estimation algorithm MediaPipe. The human displacement is used to generate the input for the roll rotation of the platform according to a one d.o.f. transfer function, whose parameters can be set to get different levels of difficulties in the exercise. The device offers therefore the flexibility to set different parameters to modify the level of the users’ training. The proposed device has the potential for a larger variety of rehabilitation activities and exergames. This paper describes the elements adopted for the implementation of this human-in-the-loop system, presents some preliminary tests to explore the influence of transfer function parameters on human and platform movements, and concludes with future development possibilities.

A robust multimodal detection system: physical exercise monitoring in long-term care environments.

Falls are a major cause of accidents that can lead to serious injuries, especially among geriatric populations worldwide. Ensuring constant supervision in hospitals or smart environments while maintaining comfort and privacy is practically impossible. Therefore, fall detection has become a significant area of research, particularly with the use of multimodal sensors. The lack of efficient techniques for automatic fall detection hampers the creation of effective preventative tools capable of identifying falls during physical exercise in long-term care environments. The primary goal of this article is to examine the benefits of using multimodal sensors to enhance the precision of fall detection systems. The proposed paper combines time-frequency features of inertial sensors with skeleton-based modeling of depth sensors to extract features. These multimodal sensors are then integrated using a fusion technique. Optimization and a modified K-Ary classifier are subsequently applied to the resultant fused data. The suggested model achieved an accuracy of 97.97% on the UP-Fall Detection dataset and 97.89% on the UR-Fall Detection dataset. This indicates that the proposed model outperforms state-of-the-art classification results. Additionally, the proposed model can be utilized as an IoT-based solution, effectively promoting the development of tools to prevent fall-related injuries.

ASSOCIATION AND RISK PREDICTION OF PAIN AND FALL-RELATED INJURIES AMONG COMMUNITY-DWELLING OLDER ADULTS IN CHINA

Abstract Background Pain is common in older adults and has also been identified as a fall risk factor, whereas the impact and mechanism of fall-related injuries are still unknown. This study aims to examine the association and risk prediction of pain and fall-related injuries among Chinese older adults. Method This study enrolled 5,721 older adults from the China Health and Retirement Longitudinal Study (wave 2011-2015). Logistic regression was used to analyze the associations between pain characteristics and fall-related injuries. Furthermore, 2022 older adults with pain at baseline were further used to build a fall-related injury prediction model, using five machine learning algorithms (logistic regression, naive bayesian, random forest, adaptive boosting and artificial neural network) with 118 input variables as candidate features, and SHapley Additive exPlanations was used for the prediction model explanation. Results Logistic regression models showed that whether pain (OR=1.35) or pain severity (ORmoderate=1.37, ORsevere =1.48) and multisite pain (OR=1.41) independently predicted fall-related injuries. The Random forest model achieved the best performance among the prediction model with an area under the receiver operating characteristic curve of 0.764. Interpretable results showed that the top 10 significant predictors were: experience of falling, frailty, sex, short physical performance battery, received inpatient care, estimated glomerular filtration rate, lung function, pain quantity, White Blood Cell and Age. Conclusions Pain is associated with fall-related injuries among Chinese older adults. Fall-related injury prevention strategies for older adults with pain should specifically focus on fall history, frailty, and women.

A SCOPING REVIEW OF SYSTEMS-LEVEL INTERVENTIONS FOR FALL PREVENTION IN LONG-TERM CARE

Abstract Older adults residing in long-term care facilities (LTCFs) are at high risk for falls. In addition to individual resident-level interventions to prevent falls and fall-related injury (FRI), system-focused interventions are also necessary to adequately address fall prevention. Relatively little attention has been given to research involving systems-focused interventions. We aimed to synthesize studies on the effects of system-focused interventions for fall and FRI prevention in LTCFs with the goal of identifying promising strategies and gaps. We searched Medline, CINAHL, and EMBASE databases from 2017 to 2022 following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews guideline. We conducted a narrative synthesis to summarize included studies. In the initial review, 301 studies were identified and underwent title and abstract screening resulting in 98 articles were retrieved for full-text review. Fifteen studies were included in data extraction. Fall prevention interventions evaluated in LTCF settings include: (1) multicomponent fall prevention programs, (2) staff education programs, (3) training in safe handling/transfers, (4) environmental adaptations, (5) electronic health record algorithms and prompts, (6) local culture change, (7) video analysis of falls to change local interventions, and (8) facility-level physical activity programs. About half of reported studies reported significant effects of system-focused interventions to reduce fall and FRI in LTCFs. Multicomponent fall prevention programs and physical activity interventions are the most effective systems-level interventions, while electronic health record interventions were the least effective. Overall, little attention has been given in the literature to evaluation of environmental adaptations at the systems level.

A SCOPING REVIEW FOR PERSON-FOCUSED FALL PREVENTIVE INTERVENTIONS IN LONG-TERM CARE FACILITIES

Abstract Falls are a significant concern in long-term care facilities (LTCFs) as fall-related injuries (FRI) can result in functional impairment, disability, and death. Older adults living in LTCFs are at greater risk for falls than those in the community. Using scoping review methodology, we aimed to synthesize evidence examining intervention effects of person-focused interventions for risk assessment and prevention in LTCFs to identify evidence-based practices. Databases searched included Medline, CINAHL, and EMBASE to identify original research from 2017 to April 2022 in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline. Following the removal of duplicates, 888 articles were identified for possible review, following title and abstract screening 84 studies underwent full-text review against inclusion/exclusion criteria, with 30 studies remaining for analysis. We conducted a narrative synthesis to summarize the included studies. Evidence-based interventions for fall prevention identified include (1) exercise programs (e.g., high-intensity functional exercise, aerobic exercise, short stick exercises, etc.); (2) balance training programs (e.g., Wii Fit); (3) multifaceted, nurse-led education; and (4) others (e.g., whole body vibration, and lavender olfactory stimulation). Outcomes of included studies included the number of falls, fall rate, risk of falls, and fear of falls before and after interventions. Overall, most studies reported significant effects of person-focused interventions in LTCFs. Available evidence supports that well-designed person-focused interventions can reduce falls and fear of falls for individuals in LTCFs.

A TECHNOLOGY SUPPORTED FALL PREVENTION INTERVENTION FOR OLDER ADULTS WITH MILD COGNITIVE IMPAIRMENT

Abstract Falls and fall-related injuries are significant public health issues for adults 65 years of age and older. Over a third of older adults (OA) fall each year and 10-20% of falls result in serious injuries. Cognitive impairment has been identified as a leading risk factor with over 60% of OA living with mild cognitive impairment (MCI) falling annually. Housing conditions are also a risk factor for falls. We have developed Sense4Safety, a technology-enhanced intervention that includes multiple components: 1) in-home assessment and action; 2) education and regular communication with a coach; 3) passive monitoring facilitated by depth sensors in the home; and 4) alerts. The goal of this study was to access the feasibility of Sense4Safety and its acceptability. We recruited 10 low-income OA with MCI; each participant received the intervention for 3 months. All participants completed all study procedures. The Short Physical Performance Battery (SPPB) scores which provide an objective assessment of lower extremity functioning based on clinical experts’ observation showed high correlation to the sensor system assessment (r=0.94, p&amp;lt; 0.01). Two fall alerts were generated during the study period that triggered a timely response. Participants and their family members found the intervention to provide peace of mind and empower OA to proactively address changes in fall risk through exercise and home modifications. The combination of passive sensing and personalized coaching offers an innovative ecological approach to continuously assess functional mobility and gait in the home and captures changes that provide an early warning for fall risk.

ADHERENCE TO INTERVENTIONS AT A FALL CLINIC: PRELIMINARY DESCRIPTIVE DATA FROM A SINGLE ACADEMIC INSTITUTION

Abstract Background Falls and fall-related injuries are major public health concerns. Approximately 50 billion dollars are spent on annual medical costs related to falls. Fall prevention is a priority for promoting active and healthy aging in older adults. Fall prevention clinics enable focused evaluation, identification, and treatment of modifiable risk factors, specifically for falls; however, their effectiveness is dependent upon patient adherence to preventive interventions. Methods We analyzed patients aged &amp;gt; 65 years who visited our fall clinic between February 2021 and February 2023. We took an interdisciplinary approach to improve adherence to recommendations, including follow-up phone calls by a dedicated nurse to confirm adherence, nurse-directed interventions such as Tai Chi sessions, and home environment assessments by a social worker. Results 48 patients were included in this analysis, with a mean age of 84 (65-99), and 85% were female. Fall-specific risk factors identified included impairment of strength, gait, or balance (96%); use of fall-risk-increasing medications (54%); problems with feet affecting gait (40%); visual impairment (29%); and postural hypotension (6%). The adherence rates for our interventions were 48% for physical therapy referrals, 28% for podiatry referrals, 36% for ophthalmology referrals, 47% for other referrals, 75% for vitamin D prescriptions, and 50% for assistive device prescriptions. Conclusions There is room for improvement in adherence to referrals. A larger sample size and longer follow-up period are required to investigate factors related to non-adherence. The delivery of both verbal and written recommendations, the identification of each patient’s barriers, and same-day referrals may help improve adherence.

Influence of falls, fall-related injuries, and fear of falling on social participation in people aging with long-term physical disability: a cross-sectional study

Purpose This study examined prevalence and relationships among falls, injuries, fear of falling, and social participation in people aging with long-term physical disability (PAwLTPD). Materials and methods A convenience sample of 474 PAwLTPD recruited from community agencies and social media as baseline of a longitudinal cohort study. Inclusion criteria: 45–65 years, self-reported physical disability for ≥5 years, and English-speaking. Self-report surveys of physical/mental health, falls in the past year, fear of falling, and Patient-Reported Outcomes Measurement Information System (PROMIS) ability and satisfaction with participation in social roles and activities measures were collected. Results Mean age 56.8 years; participants were mostly female (66.7%) and White (61.4%). Nearly 65% reported a fall; 56.6% of falls resulted in injury. Falls and fall-related injuries were associated with worse physical/mental health and presence of >5 health conditions. Seventy-five percent of participants reported fear of falling. Lower ability and satisfaction with participation were found in participants who fell and worried about falls. Conclusions PAwLTPD are at increased risk of falls, fall-related injuries, and fear of falling, which affects their ability to engage in social activities. Future research is needed to understand circumstances associated with falls and to develop effective interventions to address falls in PAwLTPD.

Finite Element Analysis of Energy-Absorbing Floors for Reducing Head Injury Risk during Fall Accidents

Energy-absorbing floor (EAF) has been proposed as one of several biomechanically effective strategies to mitigate the risk of fall-related injuries by decreasing peak loads and enhancing system energy absorption. This study aims to compare the protective capacity of four commercially available EAF products (Igelkott Floor, Kradal, SmartCells, and OmniSports) in terms of head impacts using the finite element (FE) method. The stress–strain curves acquired from mechanical tests were applied to material models in LS-Dyna. The established FE models were then validated using Hybrid III or hemispheric drop tests to compare the acceleration–time curves between experiments and simulations. Finally, the validated FE models were utilized to simulate a typical pedestrian fall accident scenario. It was demonstrated that EAFs can substantially reduce the peak forces, acceleration, and velocity changes during fall-related head impacts. Specifically, in the accident reconstruction scenario, SmartCells provided the largest reduction in peak linear acceleration and skull fracture risk, while Igelkott Floor provided the largest reduction in peak angular velocity and concussion risk. This performance was caused by different energy absorption mechanisms. Consequently, the results can contribute to supporting the implementation of EAFs and determine the effectiveness of various protective strategies for fall-related head injury prevention.

Posture analysis in predicting fall-related injuries during French Navy Special Forces selection course using machine learning: a proof-of-concept study

IntroductionInjuries induced by falls represent the main cause of failure in the French Navy Special Forces selection course. In the present study, we made the assumption that probing the posture...

Development and validation of a machine learning-based fall-related injury risk prediction model using nationwide claims database in Korean community-dwelling older population

BackgroundFalls impact over 25% of older adults annually, making fall prevention a critical public health focus. We aimed to develop and validate a machine learning-based prediction model for serious fall-related injuries (FRIs) among community-dwelling older adults, incorporating various medication factors.MethodsUtilizing annual national patient sample data, we segmented outpatient older adults without FRIs in the preceding three months into development and validation cohorts based on data from 2018 and 2019, respectively. The outcome of interest was serious FRIs, which we defined operationally as incidents necessitating an emergency department visit or hospital admission, identified by the diagnostic codes of injuries that are likely associated with falls. We developed four machine-learning models (light gradient boosting machine, Catboost, eXtreme Gradient Boosting, and Random forest), along with a logistic regression model as a reference.ResultsIn both cohorts, FRIs leading to hospitalization/emergency department visits occurred in approximately 2% of patients. After selecting features from initial set of 187, we retained 26, with 15 of them being medication-related. Catboost emerged as the top model, with area under the receiver operating characteristic of 0.700, along with sensitivity and specificity rates around 65%. The high-risk group showed more than threefold greater risk of FRIs than the low-risk group, and model interpretations aligned with clinical intuition.ConclusionWe developed and validated an explainable machine-learning model for predicting serious FRIs in community-dwelling older adults. With prospective validation, this model could facilitate targeted fall prevention strategies in primary care or community-pharmacy settings.

Evaluation of a concise fall risk stratification among older adults with cataracts in day surgery settings: A historically controlled study.

This study aimed to evaluate the use of a concise fall risk stratification in assessing and predicting falls compared with the Morse Falls Scale among older adults with cataracts in day surgery settings. A historically controlled study conducted from July 2020 to June 2022 was used in a municipal ophthalmic hospital in China. The concise fall risk stratification which directly graded fall risk by multifactorial judgment was used during the intervention period, while the Morse Falls Scale which graded fall risk by scale scores was used during the control period. The fall risk levels, fall assessment time, fall rates, fall-related injuries, predictive validity, and patient satisfaction with day surgery care were extracted. Propensity score matching was performed to balance baselines. After matching, 4132 patients were included in the final analysis. Compared with the control group, the intervention group had significantly higher assessment results for fall risk level, a significantly shorter (by 48.15%) fall assessment time, and higher patient satisfaction. There were no differences in fall rates and fall-related injuries. Compared with the Morse Falls Scale, the concise fall risk stratification had higher sensitivity and negative predictive validity, and lower specificity and positive predictive validity, while the area under curve did not differ significantly. The use of the concise fall risk stratification reduced fall assessment time, improved patient satisfaction, and is unlikely to impact falls with an overall predictive performance comparable to that of the Morse Falls Scale for older cataract adults in day surgery settings.