View clinical trials related to Fall.
Filter by:The incidence of fall in older adults aged 65 and over is estimated at 30%, and 50% of the people aged 80 and over with at least one fall a year. Falls are associated with significant morbidity and mortality. The origin falls is often multifactorial, involving intrinsic and extrinsic factors. Few studies have investigated the association with all antidepressants. Potential adverse effects of antidepressants such as hyponatremia, sedation, orthostatic hypotension, extrapyramidal symptoms are known risk factors for falls. Due to multimorbidity, polypharmacy including interaction risks, and aging-related changes in pharmacokinetic and pharmacodynamic of drugs, antidepressants may further increase this risk in older patients. Based on the World Health Organization global database, the main objective of this study is to investigate the association between antidepressants classes and the occurrence of falls reported in the database. A disproportionality analysis will be performed. It will aim to assess whether some classes of antidepressants, and within these classes some molecules, are associated with a greater risk of falls. A mediation analysis will also be performed. It will aim to examine some of the mediators involved in the association between antidepressants classes and falls.
Falling is considered one of the major problems that may affect the elderly, which may lead to bad consequences. Safe walking needs the older adult to anticipate and respond quickly to external demands and sudden environmental changes.Many studies have shown that treadmill training is effective in improving the elderly person's ability to walk and avoid falls. The C-Mill treadmill is an innovative device that recently used for the training of impaired gait and balance.Therefore, this study will aim to evaluate the efficacy of gait training with a virtual reality treadmill on the risk of fall in the elderly.
Falls are a leading cause of injuries among older patients. Medication use is a major risk factor for falls. Because we lack tools to assess individualized risks, general practitioners (GPs) struggle with fall-related medication management for older patients. Furthermore, these older patients are often not properly equipped to engage in the joint management of their medication. A Clinical Decision Support System (CDSS) for GPs and a patient portal for older patients may stimulate shared decision making between GPs and older patients when discussing the medication-related fall risk. The CDSS provides the GP with advice on how to alter medication in such a way that the fall risk decreases, and the patient portal helps the older patient to prepare for a consultation and to engage in the joint management of their medication.
This study aimed to explore the effects of an exercise and cognitive training intervention on the physical fitness, fall, and cognitive functions of community-dwelling older adults with dementia. The exercise and cognitive training intervention of this study promoted physical fitness, reduced chance of falling, and improved the cognitive functions of community-dwelling older adults with dementia. In addition, the score of risk of falling reduced.
Researchers at the University of North Carolina at Greensboro conduct a single-arm intervention trial to investigate the efficacy of a music-based group exercise program for community-dwelling older adults. Up to forty participants will be recruited to participate in a music-based light-to-moderate intensity group exercise program for 20 weeks (30 - 40 min/day, up to 6 days/week), which is designed for older adults with or without functional limitations to exercise with chairs for the improvement of aerobic capacity, upper and lower body strength, and balance control at a gradually increasing pace. During the exercise sessions, participants will be trained to move in time with music playlists in synchronous tempos. Primary outcomes are cognitive performance, mobility, and health-related quality of life measured before and after the intervention. Secondary outcomes are adherence to the exercise program as a potential mediator of the treatment.
Falls in older adults represents a growing public health challenge. The use of certain medication is recognized as an important modifiable risk factor for falls. Research indicates fall-risk increasing drug (FRID) deprescribing is effective in reducing falls but difficult to initiate and to sustain over longer periods of follow-up. A clinical decision support system (CDSS) and patient portal for communicating medication-related fall risk to fall clinic patients may improve joint medication management between patients and physicians and consequently reduce the incidence of injurious falls.
Due to the clinical, functional, cognitive and social complexity of older adults after fragility hip fractures (defined as those produced by low-impact trauma), the investigators propose an intervention. This intervention involves a multidisciplinary and multicomponent program consisting of physical exercise with tele-rehabilitation, nutritional assessment and other variables related to comprehensive geriatric assessment. The investigators want to improve functional status, quality of life and prevent new fractures. In addition, the investigators try to optimize treatments and resources based on the functional status of patients and their life expectancies, improving care and healthcare cost
The Digital Fall Prevention Study is a single-group unblinded study to explore the feasibility and acceptability of a 3-month fall prevention exercise program delivered digitally via a tablet interface. Evidence-based exercise programs and motivational techniques will be used along with new wearable technology to predict fall risk.
Fall is one of the most common problems experienced by the elderly, is an important public health problem in many societies. Falls are one of the leading causes of fatal and non-fatal injuries in the elderly. An average of one-third of individuals aged 65 and over have a fall at least once each year. The research will be carried out on the web page that on fall prevention prepared within the scope of this project. The aim of this project is to assess the effect of Web-Based Fall Prevention Program on falling, fall risk and fear of fall.
Sarcopenia is quickly becoming a major global public health issue. Falls are the leading cause of mortality among the elderly, and they must be addressed. The investigators will use machine learning techniques such as empirical mode decomposition technology and decision tree algorithms to extract the characteristics and classification of sarcopenia in this retrospective study in order to offer clinically proven and effective interventional strategies to prevent, stabilize, and reverse sarcopenia.