Falls are a common, serious threat to the health and self-confidence of the elderly. Assessment of fall risk is an important aspect of effective fall prevention programs.
In order to test whether it ...is possible to outperform current prognostic tools for falls, we analyzed 1010 variables pertaining to mobility collected from 976 elderly subjects (InCHIANTI study). We trained and validated a data-driven model that issues probabilistic predictions about future falls. We benchmarked the model against other fall risk indicators: history of falls, gait speed, Short Physical Performance Battery (Guralnik et al. 1994), and the literature-based fall risk assessment tool FRAT-up (Cattelani et al. 2015). Parsimony in the number of variables included in a tool is often considered a proxy for ease of administration. We studied how constraints on the number of variables affect predictive accuracy.
The proposed model and FRAT-up both attained the same discriminative ability; the area under the Receiver Operating Characteristic (ROC) curve (AUC) for multiple falls was 0.71. They outperformed the other risk scores, which reported AUCs for multiple falls between 0.64 and 0.65. Thus, it appears that both data-driven and literature-based approaches are better at estimating fall risk than commonly used fall risk indicators. The accuracy-parsimony analysis revealed that tools with a small number of predictors (~1-5) were suboptimal. Increasing the number of variables improved the predictive accuracy, reaching a plateau at ~20-30, which we can consider as the best trade-off between accuracy and parsimony. Obtaining the values of these ~20-30 variables does not compromise usability, since they are usually available in comprehensive geriatric assessments.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Objective
To compare the effectiveness of single, multiple, and multifactorial interventions to prevent falls and fall‐related fractures in community‐dwelling older persons.
Methods
MEDLINE, Embase, ...and Cochrane Central Register of Controlled Trials were systematically searched for randomized controlled trials (RCTs) evaluating the effectiveness of fall prevention interventions in community‐dwelling adults aged ≥65 years, from inception until February 27, 2019. Two large RCTs (published in 2020 after the search closed) were included in post hoc analyses. Pairwise meta‐analysis and network meta‐analysis (NMA) were conducted.
Results
NMA including 192 studies revealed that the following single interventions, compared with usual care, were associated with reductions in number of fallers: exercise (risk ratio RR 0.83; 95% confidence interval CI 0.77–0.89) and quality improvement strategies (e.g., patient education) (RR 0.90; 95% CI 0.83–0.98). Exercise as a single intervention was associated with a reduction in falls rate (RR 0.79; 95% CI 0.73–0.86). Common components of multiple interventions significantly associated with a reduction in number of fallers and falls rate were exercise, assistive technology, environmental assessment and modifications, quality improvement strategies, and basic falls risk assessment (e.g., medication review). Multifactorial interventions were associated with a reduction in falls rate (RR 0.87; 95% CI 0.80–0.95), but not with a reduction in number of fallers (RR 0.95; 95% CI 0.89–1.01). The following single interventions, compared with usual care, were associated with reductions in number of fall‐related fractures: basic falls risk assessment (RR 0.60; 95% CI 0.39–0.94) and exercise (RR 0.62; 95% CI 0.42–0.90).
Conclusions
In keeping with Tricco et al. (2017), several single and multiple fall prevention interventions are associated with fewer falls. In addition to Tricco, we observe a benefit at the NMA‐level of some single interventions on preventing fall‐related fractures.
The prevalence of risk factors for falls increases during middle-age, but the prevalence of falls in this age-range is often overlooked and understudied. The aim was to calculate the prevalence of ...falls in middle-aged adults (aged 40-64 years) from four countries. Data were from four population-based cohort studies from Australia (Australian Longitudinal Study on Women's Health, n = 10556, 100% women, 51-58 years in 2004), Ireland (The Irish Longitudinal Study on Ageing, n = 4968, 57.5% women, 40-64 years in 2010), the Netherlands (Longitudinal Aging Study Amsterdam, n = 862, 51.6% women, 55-64 years in 2012-13) and Great Britain (MRC National Survey of Health and Development, n = 2821, 50.9% women, 53 years in 1999). In each study, falls assessment was based on recall of any falls in the past year. The prevalence of falls was calculated for the total group, for each country, for men and women separately, and for 5-year age-bands. The prevalence was higher in Australia (27.8%, women only) and the Netherlands (25.1%) than in Ireland (17.6%) and Great Britain (17.8%, p<0.001). Women (27.0%) had higher prevalences than men (15.2%, p<0.001). The prevalence increased from 8.7% in 40-44 year olds to 29.9% in 60-64 year olds in women, and from 14.7% in 45-49 year olds to 15.7% in 60-64 year olds in men. Even within 5-year age-bands, there was substantial variation in prevalence between the four cohorts. Weighting for age, sex and education changed the prevalence estimates by less than 2 percentage points. The sharp increase in prevalence of falls in middle-age, particularly among women supports the notion that falls are not just a problem of old age, and that middle-age may be a critical life stage for preventive interventions.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Background
At least one‐third of community‐dwelling people over 65 years of age fall each year. Exercises that target balance, gait and muscle strength have been found to prevent falls in these ...people. An up‐to‐date synthesis of the evidence is important given the major long‐term consequences associated with falls and fall‐related injuries
Objectives
To assess the effects (benefits and harms) of exercise interventions for preventing falls in older people living in the community.
Search methods
We searched CENTRAL, MEDLINE, Embase, three other databases and two trial registers up to 2 May 2018, together with reference checking and contact with study authors to identify additional studies.
Selection criteria
We included randomised controlled trials (RCTs) evaluating the effects of any form of exercise as a single intervention on falls in people aged 60+ years living in the community. We excluded trials focused on particular conditions, such as stroke.
Data collection and analysis
We used standard methodological procedures expected by Cochrane. Our primary outcome was rate of falls.
Main results
We included 108 RCTs with 23,407 participants living in the community in 25 countries. There were nine cluster‐RCTs. On average, participants were 76 years old and 77% were women. Most trials had unclear or high risk of bias for one or more items. Results from four trials focusing on people who had been recently discharged from hospital and from comparisons of different exercises are not described here.
Exercise (all types) versus control
Eighty‐one trials (19,684 participants) compared exercise (all types) with control intervention (one not thought to reduce falls). Exercise reduces the rate of falls by 23% (rate ratio (RaR) 0.77, 95% confidence interval (CI) 0.71 to 0.83; 12,981 participants, 59 studies; high‐certainty evidence). Based on an illustrative risk of 850 falls in 1000 people followed over one year (data based on control group risk data from the 59 studies), this equates to 195 (95% CI 144 to 246) fewer falls in the exercise group. Exercise also reduces the number of people experiencing one or more falls by 15% (risk ratio (RR) 0.85, 95% CI 0.81 to 0.89; 13,518 participants, 63 studies; high‐certainty evidence). Based on an illustrative risk of 480 fallers in 1000 people followed over one year (data based on control group risk data from the 63 studies), this equates to 72 (95% CI 52 to 91) fewer fallers in the exercise group. Subgroup analyses showed no evidence of a difference in effect on both falls outcomes according to whether trials selected participants at increased risk of falling or not.
The findings for other outcomes are less certain, reflecting in part the relatively low number of studies and participants. Exercise may reduce the number of people experiencing one or more fall‐related fractures (RR 0.73, 95% CI 0.56 to 0.95; 4047 participants, 10 studies; low‐certainty evidence) and the number of people experiencing one or more falls requiring medical attention (RR 0.61, 95% CI 0.47 to 0.79; 1019 participants, 5 studies; low‐certainty evidence). The effect of exercise on the number of people who experience one or more falls requiring hospital admission is unclear (RR 0.78, 95% CI 0.51 to 1.18; 1705 participants, 2 studies, very low‐certainty evidence). Exercise may make little important difference to health‐related quality of life: conversion of the pooled result (standardised mean difference (SMD) ‐0.03, 95% CI ‐0.10 to 0.04; 3172 participants, 15 studies; low‐certainty evidence) to the EQ‐5D and SF‐36 scores showed the respective 95% CIs were much smaller than minimally important differences for both scales.
Adverse events were reported to some degree in 27 trials (6019 participants) but were monitored closely in both exercise and control groups in only one trial. Fourteen trials reported no adverse events. Aside from two serious adverse events (one pelvic stress fracture and one inguinal hernia surgery) reported in one trial, the remainder were non‐serious adverse events, primarily of a musculoskeletal nature. There was a median of three events (range 1 to 26) in the exercise groups.
Different exercise types versus control
Different forms of exercise had different impacts on falls (test for subgroup differences, rate of falls: P = 0.004, I² = 71%). Compared with control, balance and functional exercises reduce the rate of falls by 24% (RaR 0.76, 95% CI 0.70 to 0.81; 7920 participants, 39 studies; high‐certainty evidence) and the number of people experiencing one or more falls by 13% (RR 0.87, 95% CI 0.82 to 0.91; 8288 participants, 37 studies; high‐certainty evidence). Multiple types of exercise (most commonly balance and functional exercises plus resistance exercises) probably reduce the rate of falls by 34% (RaR 0.66, 95% CI 0.50 to 0.88; 1374 participants, 11 studies; moderate‐certainty evidence) and the number of people experiencing one or more falls by 22% (RR 0.78, 95% CI 0.64 to 0.96; 1623 participants, 17 studies; moderate‐certainty evidence). Tai Chi may reduce the rate of falls by 19% (RaR 0.81, 95% CI 0.67 to 0.99; 2655 participants, 7 studies; low‐certainty evidence) as well as reducing the number of people who experience falls by 20% (RR 0.80, 95% CI 0.70 to 0.91; 2677 participants, 8 studies; high‐certainty evidence). We are uncertain of the effects of programmes that are primarily resistance training, or dance or walking programmes on the rate of falls and the number of people who experience falls. No trials compared flexibility or endurance exercise versus control.
Authors' conclusions
Exercise programmes reduce the rate of falls and the number of people experiencing falls in older people living in the community (high‐certainty evidence). The effects of such exercise programmes are uncertain for other non‐falls outcomes. Where reported, adverse events were predominantly non‐serious.
Exercise programmes that reduce falls primarily involve balance and functional exercises, while programmes that probably reduce falls include multiple exercise categories (typically balance and functional exercises plus resistance exercises). Tai Chi may also prevent falls but we are uncertain of the effect of resistance exercise (without balance and functional exercises), dance, or walking on the rate of falls.
Falls are common health events that cause discomfort and disability for older adults and stress for caregivers. Using the case of an older man who has experienced multiple falls and a hip fracture, ...this article, which focuses on community-living older adults, addresses the consequences and etiology of falls; summarizes the evidence on predisposing factors and effective interventions; and discusses how to translate this evidence into patient care. Previous falls; strength, gait, and balance impairments; and medications are the strongest risk factors for falling. Effective single interventions include exercise and physical therapy, cataract surgery, and medication reduction. Evidence suggests that the most effective strategy for reducing the rate of falling in community-living older adults may be intervening on multiple risk factors. Vitamin D has the strongest clinical trial evidence of benefit for preventing fractures among older men at risk. Issues involved in incorporating these evidence-based fall prevention interventions into outpatient practice are discussed, as are the trade-offs inherent in managing older patients at risk of falling. While challenges and barriers exist, fall prevention strategies can be incorporated into clinical practice.
Background: randomised controlled trials (RCTs) of fall prevention conducted in community settings have recently been systematically reviewed.
Objective: to augment this review by analysing older ...people's participation in the trials and engagement with the interventions.
Design: review of the 99 single and multifactorial RCTs included in the Cochrane systematic review of falls prevention interventions.
Setting: community.
Participants: adults aged 60+/mean age minus one standard deviation of 60+.
Methods: calculated aggregate data on recruitment (proportion who accepted the invitation to participate), attrition at 12 month follow-up (loss of participants), adherence (to intervention protocol) and whether adherence moderated the effect of interventions on trial outcomes.
Results: the median recruitment rate was 70.7% (64.2-81.7%, n = 78). At 12 months the median attrition rate including mortality was 10.9% (9.1-16.0%, n = 44). Adherence rates (n = 69) were ≥80% for vitamin D/calcium supplementation; ≥70% for walking and class-based exercise; 52% for individually targeted exercise; approximately 60-70% for fluid/nutrition therapy and interventions to increase knowledge; 58-59% for home modifications; but there was no improvement for medication review/withdrawal of certain drugs. Adherence to multifactorial interventions was generally ≥75% but ranged 28-95% for individual components. The 13 studies that tested for whether adherence moderated treatment effectiveness produced mixed results.
Conclusions: using median rates for recruitment (70%), attrition (10%) and adherence (80%), we estimate that, at 12 months, on average half of community-dwelling older people are likely to be adhering to falls prevention interventions in clinical trials.
To develop and cross-culturally adapt a Brazilian-Portuguese version of the Falls Behavioral Scale (FaB-Brazil) and to verify its psychometric properties.
The translation and cross-cultural ...adaptation process of the scale followed standard guidelines. The FaB-Brazil scale was applied to 93 community-dwelling older people. Cronbach's alpha was calculated to evaluate internal consistency and the intraclass correlation coefficient (ICC) to evaluate interrater and test-retest reliability. The standard error of measurement (SEM), minimal detectable change (MDC), ceiling and floor effects, convergent and discriminative validity were evaluated. A significance level of .05 was set for statistical analyses.
Internal consistency was moderate (α = 0.73). An excellent inter-rater (ICC = 0.93; p < 0.001) and a good test-retest (ICC = 0.79; p < 0.001) reliability were found. The SEM was 0.27 and MDC was 0.53. Neither ceiling nor floor effects were found. Convergent validity was established by the positive correlations between the FaB-Brazil scale, age, and functional mobility, and by the negative correlations between the FaB-Brazil scale and balance confidence, community mobility and EuroQol-5D (p < 0.05). No significant differences were found between males and females and between non-fallers and fallers.
Our results offer evidence for the reliability and validity of the FaB-Brazil scale for community-dwelling older people.
Implications for Rehabilitation
Fall-related behaviors should be part of the fall risk assessment of community-dwelling older people.
The Brazilian-Portuguese version of the Falls Behavioral Scale (FaB-Brazil) is reliable and valid for assessing fall-related behaviors in community-dwelling older people.
The FaB-Brazil scale may be used to raise awareness about potential fall hazards and to guide fall prevention programs.
•Falls are the leading cause of injury-related deaths in older adults.•Free-living fall risk assessment (FRA) may address limitations of clinical tests.•A literature review on free-living FRA using ...wearable sensors is presented.•Methods to extract and classify free-living fall predictors (FLFPs) were examined.•Recommendations to address methodological heterogeneities were discussed.
Despite advances in laboratory-based supervised fall risk assessment methods (FRAs), falls still remain a major public health problem. This can be due to the alteration of behavior in laboratory due to the awareness of being observed (i.e., Hawthorne effect), the multifactorial complex etiology of falls, and our limited understanding of human behaviour in natural environments, or in the’ wild’. To address these imitations, a growing body of literature has focused on free-living wearable-sensor-based FRAs. The objective of this narrative literature review is to discuss papers investigating natural data collected by wearable sensors for a duration of at least 24 h to identify fall-prone older adults.
Databases (Scopus, PubMed and Google Scholar) were searched for studies based on a rigorous search strategy.
Twenty-four journal papers were selected, in which inertial sensors were the only wearable system employed for FRA in the wild. Gait was the most-investigated activity; but sitting, standing, lying, transitions and gait events, such as turns and missteps, were also explored. A multitude of free-living fall predictors (FLFPs), e.g., the quantity of daily steps, were extracted from activity bouts and events. FLFPs were further categorized into discrete domains (e.g., pace, complexity) defined by conceptual or data-driven models. Heterogeneity was found within the reviewed studies, which includes variance in: terminology (e.g., quantity vs macro), hyperparameters to define/estimate FLFPs, models and domains, and data processing approaches (e.g., the cut-off thresholds to define an ambulatory bout). These inconsistencies led to different results for similar FLFPs, limiting the ability to interpret and compare the evidence.
Free-living FRA is a promising avenue for fall prevention. Achieving a harmonized model is necessary to systematically address the inconsistencies in the field and identify FLFPs with the highest predictive values for falls to eventually address intervention programs and fall prevention.
Fatal injuries and hospitalizations caused by accidental falls are significant problems among the elderly. Detecting falls in real-time is challenging, as many falls occur in a short period. ...Developing an automated monitoring system that can predict falls before they happen, provide safeguards during the fall, and issue remote notifications after the fall is essential to improving the level of care for the elderly. This study proposed a concept for a wearable monitoring framework that aims to anticipate falls during their beginning and descent, activating a safety mechanism to minimize fall-related injuries and issuing a remote notification after the body impacts the ground. However, the demonstration of this concept in the study involved the offline analysis of an ensemble deep neural network architecture based on a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN) and existing data. It is important to note that this study did not involve the implementation of hardware or other elements beyond the developed algorithm. The proposed approach utilized CNN for robust feature extraction from accelerometer and gyroscope data and RNN to model the temporal dynamics of the falling process. A distinct class-based ensemble architecture was developed, where each ensemble model identified a specific class. The proposed approach was evaluated on the annotated SisFall dataset and achieved a mean accuracy of 95%, 96%, and 98% for Non-Fall, Pre-Fall, and Fall detection events, respectively, outperforming state-of-the-art fall detection methods. The overall evaluation demonstrated the effectiveness of the developed deep learning architecture. This wearable monitoring system will prevent injuries and improve the quality of life of elderly individuals.
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