Fall prevention in the elderly population.
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ABSTRACT:
SUBMITTER: Weir E
PROVIDER: S-EPMC517852 | biostudies-literature | 2004 Sep
REPOSITORIES: biostudies-literature
Publications
Fall prevention in the elderly population.
CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne 20040901 7
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Project description: Not available
| S-EPMC8246567 | biostudies-literature
Project description:Medication use is an important risk factor for falls. Community pharmacists should therefore organise fall prevention care; however, little is known about patients' expectations of such services. This qualitative study aims to explore the expectations of community-dwelling older patients regarding fall prevention services provided by community pharmacies. Telephone intakes, followed by three focus groups, were conducted with 17 patients, who were aged ≥75 years, used at least one fall risk-increasing drug (FRID) and were registered at a community pharmacy in Amsterdam, the Netherlands. Some time of the focus groups was spent on playing a game involving knowledge questions and activities to stimulate discussion of topics related to falling. Data were collected between January 2020 and April 2020, and all focus groups were audiotaped and transcribed verbatim. The precaution adoption process model (PAPM) was applied during data analysis. Patients who had already experienced a fall more often mentioned that they took precautions to prevent falling. In general, patients were unaware that their medication use could increase their fall risk. Therefore, they did not expect pharmacists to play a role in fall prevention. However, many patients were interested in deprescribing. Patients also wanted to be informed about which medication could increase fall risk. In conclusion, although patients initially did not see a role for pharmacists in fall prevention, their perception changed when they were informed about the potential fall risk-increasing effects of some medications. Patients expected pharmacists to focus on drug-related interventions to reduce fall risk, such as deprescribing.
| S-EPMC9290894 | biostudies-literature
Project description:Fall is common in the elderly, and chronic kidney disease is considered a major risk factor. Serum creatinine (Cre) and cystatin C (Cys C) are commonly used biomarkers for renal function, while the ratio of Cre to Cys C, known as the sarcopenia index (SI), provides insights into muscle health. This study investigates the relationships between Cre, Cys C, estimated glomerular filtration rates (eGFR), SI, and self-reported falls using National Health and Nutrition Examination Survey (NHANES) data. We included 4,272 older adults with eGFR > 30mL/min/1.73m2 from NHANES (1999 to 2004) and divided them into the fall and non-fall groups based on the questionnaires. Correlations were assessed using restricted cubic spline, weighted generalized linear regression models. Multi-factor logistic regression analysis identified serum Cys C as significantly associated with falls (all participants: OR 1.16, 95% CI: 1.09 to 1.23, p < 0.001; participants with eGFR > 75 mL/min/1.73m2: OR 1.17, 95% CI: 1.05 to 1.30, p < 0.001,). In contrast, Cre and eGFR were not significant after adjustments; SI showed marginal significance (p = 0.045). Cys C is significantly associated with fall risk in older adults, demonstrating a positive linear relationship with self-reported falls.
| S-EPMC11522524 | biostudies-literature
Project description:Falls are a major threat to older adults worldwide. Although various effective interventions have been developed, their comparative effectiveness remains unreported. A systematic review and network meta-analysis was conducted to determine the most effective interventions to prevent falls in community-dwelling adults aged 60 and over. Combined odds ratio (OR) and 95% credible interval (95% CrI) were calculated. A total of 49 trials involving 27,740 participants and 9271 fallers were included. Compared to usual care, multifactorial interventions (MFI) demonstrated the greatest efficacy (OR: 0.64, 95% CrI: 0.53 to 0.77) followed by interventions combining education and exercise (EDU + EXC) (OR: 0.65, 95% CrI: 0.38 to 1.00) and interventions combining exercise and hazard assessment and modification (EXC + HAM) (OR: 0.66, 95% CrI: 0.40 to 1.04). The effect of medical care performed the worst (OR: 1.02, 95% CrI: 0.78 to 1.34). Model fit was good, inconsistency was low, and publication bias was considered absent. The overall quality of included trials was high. The pooled odds ratios and ranking probabilities remained relatively stable across all sensitivity analyses. MFI and exercise appear to be effective to reduce falls among older adults, and should be considered first as service delivery options. Further investigation is necessary to verify effectiveness and suitableness of the strategies to at-risk populations.
| S-EPMC5877043 | biostudies-literature
Project description:PurposeFalls are a common adverse event experienced by elderly in hospitals. This study assessed the effects of a fall prevention program on the rate of fallers, the patient safety culture, and patient-perceived safety.Materials and methodsTwo orthopedic departments in different towns in Norway participated in the study. A comprehensive, multifactorial fall prevention program was implemented in one of the departments, the other one was used for control. The changes in the outcomes in the two departments from before to after the intervention were compared. All patients above 64 years of age admitted to the two departments in a 1-year period before and after the intervention were included. All employees at the two departments were invited to participate in surveys measuring the patient safety culture, and a selection of the patients reported patient-perceived safety. The primary outcome was the rate of fallers. Secondary outcomes were the employees' perceived patient safety culture (measured with the Safety Attitudes Questionnaire) and patient-perceived safety (measured with Norwegian Patient Experience Questionnaire).ResultsFalls were registered in 114 out of 3,143 patients (3.6%) with 17,006 days in the hospital. Ten patients had two falls, giving a fall rate of 7.3 falls/1,000 days in the hospital. The number of fallers before and after the intervention in the intervention department were 37/734 (5.04%) and 31/735 (4.22%), P=0.46, and in the control department, 25/811 (3.08%) and 21/863 (2.43%), P=0.46. The difference between the changes in the two departments was not statistically significant; 0.17% (95% CI: -2.49 to 2.84; P=0.90). There were also no significant differences in the changes in patient safety culture and patient-perceived safety.ConclusionThe fall prevention program revealed no significant effect on the rate of fallers, the patient safety culture, or patient-perceived safety.
| S-EPMC6339647 | biostudies-literature
Project description:Elderly falls are a major concerning threat resulting in over 1.5-2 million elderly people experiencing severe injuries and 1 million deaths yearly. Falls experienced by Elderly people may lead to a long-term negative impact on their physical and psychological health conditions. Major healthcare research had focused on this lately to detect and prevent the fall. In this work, an Artificial Intelligence (AI) edge computing based wearable device is designed and developed for detection and prevention of fall of elderly people. Further, the various deep learning algorithms such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) are utilized for activity recognition of elderly. Also, the CNN-LSTM, RNN-LSTM and GRU-LSTM with and without attention layer respectively are utilized and the performance metrics are analyzed to find the best deep learning model. Furthermore, the three different hardware boards such as Jetson Nano developer board, Raspberry PI 3 and 4 are utilized as an AI edge computing device and the best deep learning model is implemented and the computation time is evaluated. Results demonstrate that the CNN-LSTM with attention layer exhibits the accuracy, recall, precision and F1_Score of 97%, 98%, 98% and 0.98 respectively which is better when compared to other deep learning models. Also, the computation time of NVIDIA Jetson Nano is less when compared to other edge computing devices. This work appears to be of high societal relevance since the proposed wearable device can be used to monitor the activity of elderly and prevents the elderly falls which improve the quality of life of elderly people.
| S-EPMC11019185 | biostudies-literature
Project description:BackgroundDiet is considered an important factor for bone health, but is composed of a wide variety of foods containing complex combinations of nutrients. Therefore we investigated the relationship between dietary patterns and fall-related fractures in the elderly.MethodsWe designed a population-based prospective survey of 1178 elderly people in Japan in 2002. Dietary intake was assessed with a 75-item food frequency questionnaire (FFQ), from which dietary patterns were created by factor analysis from 27 food groups. The frequency of fall-related fracture was investigated based on insurance claim records from 2002 until 2006. The relationship between the incidence of fall-related fracture and modifiable factors, including dietary patterns, were examined. The Cox proportional hazards regression model was used to examine the relationships between dietary patterns and incidence of fall-related fracture with adjustment for age, gender, Body Mass Index (BMI) and energy intake.ResultsAmong 877 participants who agreed to a 4 year follow-up, 28 suffered from a fall-related fracture. Three dietary patterns were identified: mainly vegetable, mainly meat and mainly traditional Japanese. The moderately confirmed (see statistical methods) groups with a Meat pattern showed a reduced risk of fall-related fracture (Hazard ratio = 0.36, 95% CI = 0.13 - 0.94) after adjustment for age, gender, BMI and energy intake. The Vegetable pattern showed a significant risk increase (Hazard ratio = 2.67, 95% CI = 1.03 - 6.90) after adjustment for age, gender and BMI. The Traditional Japanese pattern had no relationship to the risk of fall-related fracture.ConclusionsThe results of this study have the potential to reduce fall-related fracture risk in elderly Japanese. The results should be interpreted in light of the overall low meat intake of the Japanese population.
| S-EPMC2895588 | biostudies-literature
Project description:Maintaining and controlling postural balance is important for activities of daily living, with poor postural balance being predictive of future falls. This study investigated eyes open and eyes closed standing posturography with elderly adults to identify differences and determine appropriate outcome measure cut-off scores for prospective faller, single-faller, multi-faller, and non-faller classifications. 100 older adults (75.5 ± 6.7 years) stood quietly with eyes open and then eyes closed while Wii Balance Board data were collected. Range in anterior-posterior (AP) and medial-lateral (ML) center of pressure (CoP) motion; AP and ML CoP root mean square distance from mean (RMS); and AP, ML, and vector sum magnitude (VSM) CoP velocity were calculated. Romberg Quotients (RQ) were calculated for all parameters. Participants reported six-month fall history and six-month post-assessment fall occurrence. Groups were retrospective fallers (24), prospective all fallers (42), prospective fallers (22 single, 6 multiple), and prospective non-fallers (47). Non-faller RQ AP range and RQ AP RMS differed from prospective all fallers, fallers, and single fallers. Non-faller eyes closed AP velocity, eyes closed VSM velocity, RQ AP velocity, and RQ VSM velocity differed from multi-fallers. RQ calculations were particularly relevant for elderly fall risk assessments. Cut-off scores from Clinical Cut-off Score, ROC curves, and discriminant functions were clinically viable for multi-faller classification and provided better accuracy than single-faller classification. RQ AP range with cut-off score 1.64 could be used to screen for older people who may fall once. Prospective multi-faller classification with a discriminant function (-1.481 + 0.146 x Eyes Closed AP Velocity-0.114 x Eyes Closed Vector Sum Magnitude Velocity-2.027 x RQ AP Velocity + 2.877 x RQ Vector Sum Magnitude Velocity) and cut-off score 0.541 achieved an accuracy of 84.9% and is viable as a screening tool for older people at risk of multiple falls.
| S-EPMC5319679 | biostudies-literature
Project description:ObjectiveThis study aimed to optimize Fall Risk Appraisal (FRA) graphing for use in intervention programs tailored toward reducing the fall risk of older adults by using computing graphic functions in the R language.Materials and methodsWe utilized RStudio, a free development environment for the R language, as well as the functions within the "ggplot2" and "grid" packages, to develop a code that would recreate the FRA matrix for use in data visualization and analysis, as well as feedback for older adults.ResultsThe developed code successfully recreates the FRA matrix in R and allows researchers and clinicians to graph participant data onto the matrix itself.DiscussionThe use of an R code allows for a streamlined approach to manipulating the FRA matrix for use in data visualization and feedback for older adults, which improves upon the traditional paper-pencil method that has been previously used.ConclusionsThe code presented in this study recreates the FRA matrix instrument in the R language and gives researchers the ability to instantaneously add, remove, or change different aspects of the instrument to improve its readability for researchers and older adults.
| S-EPMC11410192 | biostudies-literature
Project description:PurposeModel-based economic evaluations require conceptualization of the model structure. Our objectives were to identify important health states, events, and patient attributes to be included in a model-based cost-effectiveness analysis of fall prevention interventions, to develop a model structure to examine cost-effectiveness of fall prevention interventions, and to assess the face validity of the model structure.MethodsAn expert panel comprising clinicians, health service researchers, health economists, a patient partner, and policy makers completed two rounds of online surveys to gain consensus on health states, events, and patient attributes important for fall prevention interventions. The surveys were informed by a literature search on fall prevention interventions for older adults (≥65 years) including economic evaluations and clinical practice guidelines. The results of the Delphi surveys and subsequent discussions can support the face validity of a state-transition model for an economic evaluation of fall prevention interventions.ResultsIn total, 11 experts rated 24 health states/events and 41 patient attributes. Consensus was achieved on 14 health states/events and 26 patient characteristics. The proposed model structure incorporated 12 of the 14 selected health states/events. Panelists confirmed the face validity of the model structure during teleconferences.ConclusionsThere is a dearth of studies presenting the model conceptualization process; consequently, this study involving multiple end user partners with opportunities for input at several stages adds to the literature as another case study. This process is an example of how a fall prevention economic model was developed using a modified Delphi process and assessed for face validity.
| S-EPMC9882648 | biostudies-literature