Dataset Information

Frailty Versus Stopping Elderly Accidents, Deaths and Injuries Initiative Fall Risk Score: Ability to Predict Future Falls.

ABSTRACT: OBJECTIVES:To compare the ability of frailty status to predict fall risk with that of community fall risk screening tools. DESIGN:Analysis of cross-sectional and longitudinal data from NHATS. SETTING:National Health and Aging Trend Study (NHATS) 2011-2015. PARTICIPANTS:Individuals aged 65 and older (N = 7,392). MEASUREMENTS:Fall risk was defined according to the Stopping Elderly Accidents, Deaths and Injuries (STEADI) initiative. Frailty was defined as exhaustion, weight loss, low activity, slow gait speed, and weak grip strength. Robust was defined as meeting 0 criteria, prefrailty as 1 or 2 criteria, and frailty as 3 or more criteria. Falls were self-reported and ascertained using NHATS subsequent rounds (2012-2015). We compared the ability of frailty to predict future falls with that of STEADI score, adjusting for age, race, sex, education, comorbidities, hearing and vision impairment, and disability. RESULTS:Of the 7,392 participants (58.5% female), there 3,545 (48.0%) were classified as being at low risk of falling, 2,966 (40.1%) as being at moderate risk, and 881 (11.9%) as being at high risk. The adjusted risk of falling over the 4 subsequent years was 2.5 times as great for the moderate-risk group (hazard ratio (HR) = 2.50, 95% confidence interval (CI) = 2.16-2.89) and almost 4 times as great (HR = 3.79, 95% CI = 2.76-5.21) for the high-risk group as for the low-risk group. Risk of falling was greater for those who were prefrail (HR = 1.34, 95% CI 1.16-1.55) and frail (HR = 1.20, 95% CI = 0.94-1.54) than for those who were robust. CONCLUSION:STEADI score is a strong predictor of future falls. Addition of frailty status does not improve the ability of the STEADI measure to predict future falls.

SUBMITTER: Crow RS

PROVIDER: S-EPMC5933526 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Frailty Versus Stopping Elderly Accidents, Deaths and Injuries Initiative Fall Risk Score: Ability to Predict Future Falls.

Crow Rebecca S RS Lohman Matthew C MC Pidgeon Dawna D Bruce Martha L ML Bartels Stephen J SJ Batsis John A JA

Journal of the American Geriatrics Society 20180210 3

<h4>Objectives</h4>To compare the ability of frailty status to predict fall risk with that of community fall risk screening tools.<h4>Design</h4>Analysis of cross-sectional and longitudinal data from NHATS.<h4>Setting</h4>National Health and Aging Trend Study (NHATS) 2011-2015.<h4>Participants</h4>Individuals aged 65 and older (N = 7,392).<h4>Measurements</h4>Fall risk was defined according to the Stopping Elderly Accidents, Deaths and Injuries (STEADI) initiative. Frailty was defined as exhaust ...[more]

PMID: 29427525

Similar Datasets

Project description:BackgroundFalls are common in older adults and can lead to severe injuries. The Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) trial cluster-randomized 86 primary care practices across 10 health systems to a multifactorial intervention to prevent fall injuries, delivered by registered nurses trained as falls care managers, or enhanced usual care. STRIDE enrolled 5451 community-dwelling older adults age ≥70 at increased fall injury risk.MethodsWe assessed fall-related outcomes via telephone interviews of participants (or proxies) every 4 months. At baseline, 12 and 24 months, we assessed health-related quality of life (HRQOL) using the EQ-5D-5L and EQ-VAS. We used Poisson models to assess intervention effects on falls, fall-related fractures, fall injuries leading to hospital admission, and fall injuries leading to medical attention. We used hierarchical longitudinal linear models to assess HRQOL.ResultsFor recurrent event models, intervention versus control incidence rate ratios were 0.97 (95% confidence interval [CI], 0.93-1.00; p = 0.048) for falls, 0.93 (95% CI, 0.80-1.08; p = 0.337) for self-reported fractures, 0.89 (95% CI, 0.73-1.07; p = 0.205) for adjudicated fractures, 0.91 (95% CI, 0.77-1.07; p = 0.263) for falls leading to hospital admission, and 0.97 (95% CI, 0.89-1.06; p = 0.477) for falls leading to medical attention. Similar effect sizes (non-significant) were obtained for dichotomous outcomes (e.g., participants with ≥1 events). The difference in least square mean change over time in EQ-5D-5L (intervention minus control) was 0.009 (95% CI, -0.002 to 0.019; p = 0.106) at 12 months and 0.005 (95% CI, -0.006 to 0.015; p = 0.384) at 24 months.ConclusionsAcross a standard set of outcomes typically reported in fall prevention studies, we observed modest improvements, one of which was statistically significant. Future work should focus on patient-, practice-, and organization-level operational strategies to increase the real-world effectiveness of interventions, and improving the ability to detect small but potentially meaningful clinical effects.Clinicaltrialsgov identifier: NCT02475850.

Project description:BackgroundAlthough there has been a range of studies that focused on physical frailty and associated fall outcomes within developed countries, similar studies from developing countries have been limited. This study aimed to examine the relationship between physical frailty and the prevalence of falls, multiple falls and fall-related injuries among the ageing population within the Indian context.MethodsIndividual-level data from the first wave of the Longitudinal Aging Study in India (LASI) with 28,285 older adults aged 60 years and above (male 48.9%) was used for this study. Physical frailty was assessed through the physical frailty phenotype adapted from Fried's criteria. Multivariable logistic regression was employed to examine the association of frailty status with falls, multiple falls, and fall-related injuries among Indian older adults.ResultsThe prevalence of frailty was found to be 29.94% within the sample and frail older adults had a higher prevalence of falls (15.43% vs 11.85%), multiple falls (7.73% vs 5.25%), and fall related injuries (6.68% vs 5.29%). The odds of falling among frail older adults were significantly higher in reference to the odds of falling among non-frail older adults [aOR: 1.24; CI: 1.09-1.41]. Similarly, the odds of multiple falls among frail older adults were significantly higher in reference to the odds of multiple falls among non-frail older adults [aOR: 1.24; CI: 1.05-1.48]. Moreover, the odds of fall-related injury among frail older adults were significantly higher in reference to the odds of fall-related injury among non-frail older adults [aOR: 1.21; CI: 1.01-1.45]. Falls, multiple falls and fall-related injuries were found to be significantly associated with employment and poor self-rated health, whereas, females and lone living older adults had a significantly higher likelihood of suffering from falls and multiple falls.ConclusionOlder individuals with physical frailty were found to be at increased risk of falls, multiple falls and fall-related injuries in India. The findings of our study also have important clinical implications in the measures undertaken to reduce falls and enable future healthcare practitioners and policymakers to factor in the key determinant of physical frailty.

Project description:Highlights • Shorter time since injury and higher mobility levels as well as poor physical health are associated with higher risk of falls and fall-related injuries, respectively in wheelchair users with spinal cord injury.• The findings indicate good discriminant ability and clinical utility of the factors presented to identify wheelchair users who are at risk of falls and fall-related injuries. Objective To identify risk factors for falls and fall-related injuries for wheelchair users with spinal cord injury (SCI). Design Cross-sectional study. Setting Community setting. Participants Fifty-nine community dwelling wheelchair users (N=59), 47.5% male, median age of 52.5 years (IQR, 21 years) with chronic SCI, median time since injury of 16.6 years (IQR, 27.3 years). Interventions No intervention. Main Outcome Measures Outcomes were incidence of falls and fall-related injuries. Participants reported on falls and fall-related injuries experienced in the previous 6 months. Independent variables were self-reported and performance-based measures. Self-reported measures included demographics, characteristics of SCI, fear of falling, psychological measures, functional independence, wheelchair skills, environmental barriers, quality of life, and community participation. Performance-based measures included transfer quality and sitting balance assessments. Logistic regression analyses were conducted to identify factors influencing falls and fall-related injuries. Results In total, 152 falls and 30 fall-related injuries were reported from a total of 37 fallers. After logistic regression analysis, the model with the greatest levels of clinical utility and discriminative ability for falls (sensitivity 81%; specificity 55%; area under the receiving operating characteristic curve [AUC] statistics=0.73; 95% CI, 0.60-0.86) included the variables of shorter time since SCI, high mobility level, and having received education on fall prevention. The model for fall-related injuries (sensitivity 79%; specificity 75%; AUC statistics=0.77; 95% CI, 0.59-0.96) included the variables of older male individual, lower physical health score, and having received education on fall prevention. Conclusions The regression models presented may be used to identify wheelchair users with SCI at greater risk of falls and fall-related injuries. The findings may help to refer those in need to tailored fall and fall-related injury prevention programs. The findings presented in this study were based on a relatively small sample convenience; therefore, further prospective studies with a larger sample size are warranted.

Dataset Information

Frailty Versus Stopping Elderly Accidents, Deaths and Injuries Initiative Fall Risk Score: Ability to Predict Future Falls.

Publications

Frailty Versus Stopping Elderly Accidents, Deaths and Injuries Initiative Fall Risk Score: Ability to Predict Future Falls.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets