Advances in geriatric medicine and research最新文献

Background: 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).

Methods: 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.

Results: 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).

Conclusions: 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.

Background: Falls are a primary cause of injuries and hospitalization in older adults. It has been reported that cognitive impairments and dementia can increase fall risk in the older population; however, it remains unknown if fall risk differs among subgroups of dementia. This meta-analysis summarized previous studies reporting the annual fall risk of people with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and compared the fall risk between these two groups of people with dementia.

Methods: Thirty-five studies enrolling 7844 older adults with AD or MCI were included. The annual fall prevalence and average number of falls of the included studies were meta-analyzed and compared by random-effects models with inverse variance weights.

Results: The annual fall prevalence in people with AD (43.55%) was significantly higher than MCI (35.26%, p < 0.001). A χ² test indicated that the pooled fall prevalence is significantly higher in people with AD than MCI χ² = 158.403, p < 0.001). Additionally, the yearly average number of falls in AD was higher than in MCI (1.30 vs 0.77 falls/person).

Conclusions: The results showed that older people with AD experience a higher annual fall prevalence with a larger number of falls than older adults with MCI. The results suggested that the fall risk measurements should be reported separately between people with AD and MCI. The findings could provide preliminary guidance for the identification of individuals with dementia who experience a high fall risk.

Falls are the leading cause of injury, disability, and injury-related mortality in the older adult population. Older adults with Alzheimer disease (AD) are over twice as likely to experience a fall compared to cognitively normal older adults. Intrinsic and extrinsic fall risk factors may influence falls during symptomatic AD; intrinsic factors include changes in cognition and impaired functional mobility, and extrinsic factors include polypharmacy and environmental fall hazards. Despite many known fall risk factors, the high prevalence of falls, and the presence of effective fall prevention interventions for older adults without cognitive impairment, effective fall prevention interventions for older adults with AD to date are limited and inconclusive. Falls may precede AD-related cognitive impairment during the preclinical phase of AD, though a narrow understanding of fall risk factors and fall prevention interventions for older adults with preclinical AD limits clinical treatment of falls among cognitively normal older adults with preclinical AD. This mini review explores fall risk factors in symptomatic AD, evidence for effective fall prevention interventions in symptomatic AD, and preclinical AD as an avenue for future falls research, including recommendations for future research directions to improve our understanding of falls and fall risk during preclinical AD. Early detection and tailored interventions to address these functional changes are needed to reduce the risk of falls for those at risk for developing AD. Concerted efforts should be dedicated to understanding falls to inform precision fall prevention strategies for this population.

Sarcopenia, defined as a loss of muscle mass and function, is a physiologic factor that has been implicated as a predictor of adverse postoperative outcomes in many older adult populations. However, data related to sarcopenia in older adults with inflammatory bowel disease (IBD) remain limited. Older adults with IBD are particularly vulnerable to adverse postoperative outcomes, in part, due to muscle depletion from systemic inflammation, malnutrition, and reduced physical activity. However, few patients undergo routine muscle evaluation as a part of preoperative assessment. Moreover, cut-off values for measures of sarcopenia in the literature are modeled after non-IBD populations. The lack of standardized measures and values for sarcopenia in the IBD patient population has led to heterogenous findings and a paucity of preoperative risk stratification tools. Therefore, we aim to explore the scope of sarcopenia as a preoperative risk stratification tool among older adults with IBD.

Estrogen receptor alpha (ERα) plays a crucial role in reproductive function in both sexes. It also mediates cellular responses to estrogens in multiple nonreproductive organ systems, many of which regulate systemic metabolic homeostasis and inflammatory processes in mammals. The loss of estrogens and/or ERα agonism during aging is associated with the emergence of several comorbid conditions, particularly in females undergoing the menopausal transition. Emerging data also suggests that male mammals likely benefit from ERα agonism if done in a way that circumvents feminizing characteristics. This has led us, and others, to speculate that tissue-specific ERα agonism may hold therapeutic potential for curtailing aging and chronic disease burden in males and females that are at high-risk of cancer and/or cardiovascular events with traditional estrogen replacement therapies. In this mini-review, we emphasize the role of ERα in the brain and liver, summarizing recent evidence that indicates these two organs systems mediate the beneficial effects of estrogens on metabolism and inflammation during aging. We also discuss how 17α-estradiol administration elicits health benefits in an ERα-dependent manner, which provides proof-of-concept that ERα may be a druggable target for attenuating aging and age-related disease burden.

Urinary incontinence is common in older women and doubles the risk of falls in this population. The association between urinary incontinence, especially urgency urinary incontinence, and falls is multifactorial and likely the result of a complex interaction between physical, mental, social, and environmental factors. As a result of this multifactorial etiology and based on existing evidence, the integration of different fall prevention strategies including strength and resistance exercises, bladder training, and home hazard reduction have the potential to decrease the risk of falls in older women with urinary incontinence. Given the prevalence of urinary incontinence and the significant morbidity associated with falls, effective interventions to reduce fall risk in older women with urinary incontinence is of high public health significance.

Mobility limitation is common among older populations and is a major burden to public health. While lower extremity dysfunction is a known contributor, the influence of shoulder dysfunction on mobility is less well understood. Shoulder pain and rotator cuff tear are common causes of shoulder dysfunction, and both ailments are highly prevalent in older adults. This article discusses shoulder pain and rotator cuff tear as contributors to shoulder dysfunction and describes the association of shoulder dysfunction with mobility limitation in older adults.

It is predicted that the growth in the U.S. elderly population alongside continued growth in chronic disease prevalence will further strain an already overburdened healthcare system and could compromise the delivery of equitable care. Current trends in technology are demonstrating successful application of artificial intelligence (AI) and machine learning (ML) to biomarkers of cardiovascular disease (CVD) using longitudinal data collected passively from internet-of-things (IoT) platforms deployed among the elderly population. These systems are growing in sophistication and deployed across evermore use-cases, presenting new opportunities and challenges for innovators and caregivers alike. IoT sensor development that incorporates greater levels of passivity will increase the likelihood of continued growth in device adoption among the geriatric population for longitudinal health data collection which will benefit a variety of CVD applications. This growth in IoT sensor development and longitudinal data acquisition is paralleled by the growth in ML approaches that continue to provide promising avenues for better geriatric care through higher personalization, more real-time feedback, and prognostic insights that may help prevent downstream complications and relieve strain on the healthcare system overall. However, findings that identify differences in longitudinal biomarker interpretations between elderly populations and relatively younger populations highlights the necessity that ML approaches that use data from newly developed passive IoT systems should collect more data on this target population and more clinical trials will help elucidate the extent of benefits and risks from these data driven approaches to remote care.

Over the past few decades, interest has begun to surge in understanding the role of emotion in decision making, and more recently in studies across the adult life span. Relevant to age-related changes in decision making, theoretical perspectives in judgment and decision making draw critical distinctions between deliberative versus intuitive/affective processes, as well as integral versus incidental affect. Empirical findings demonstrate the central role of affect in various decision-related domains such as framing and risk taking. To situate this review within an adult life-span context, we focus on theoretical perspectives in adult development regarding emotion and motivation. As a result of age differences in deliberative and emotional processes, taking a life-span perspective is critical to advance a comprehensive and grounded understanding of the role of affect in decision making. Age-related shifts in information processing from negative toward positive material also have consequential implications. By taking a life-span perspective, not only will decision theorists and researchers benefit, but so too will practitioners who encounter individuals of various ages as they make consequential decisions.