Abstract Frailty syndrome (FS) is an independent predictor of mortality in cardiovascular disease and is found in 15-74% of patients with heart failure (HF). The syndrome has a complex, multidimensional aetiology and contributes to adverse outcomes. Proper FS diagnosis and treatment determine prognosis and support the evaluation of treatment outcomes. Routine FS assessment for HF patients should be included in daily clinical practice as an important prognostic factor within a holistic process of diagnosis and treatment. Multidisciplinary team members, particularly nurses, play an important role in FS assessment in hospital and primary care settings, and in the home care environment. Raising awareness of concurrent FS in patients with HF patients and promoting targeted interventions may contribute to a decreased risk of adverse events, and a better prognosis and quality of life.
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Objective: The aim of this study was to assess the relationship between frailty syndrome and the nutritional status of older patients. Material and methods: This cross-sectional study was conducted in a sample of 120 patients hospitalized at the Geriatric Clinic between January 2017 and May 2017. The research tools were the Frailty Instrument of the Survey of Health, Ageing and Retirement in Europe (SHARE-FI), including relevant anthropometric measurements and muscle strength measurement, and the Mini Nutritional Assessment (MNA). All the calculations were performed using the Statistica 10.0 program. The p-values lower than 0.05 were considered as statistically significant. Results: The mean age of the participants was 71 years (SD=9.03). Most participants were from urban areas. More than half of the participants (53.3%) were women. Based on the SHARE-FI, the frailty syndrome was found in 33.3% of the participants. The mean value in the MNA scale was 24.4 points (SD=3.4). The frailty syndrome was significantly correlated to gender (p<0.025), financial status (p=0.036) and MNA (p<0.01) score. A statistically significant difference was observed between gender (p=0.026), financial status (p=0.016), place of living (p=0.046) and MNA score. Conclusion: This study confirmed significant correlations between the frailty syndrome and the nutritional status of older adults. In terms of prevention and clinical application, it seems important to control the nutritional status of older people and the frailty syndrome. The above-mentioned scales should be used to evaluate patients, analyze the risk and plan the intervention for that group of patients.
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Abstract: Hypertension is both a health problem and a financial one globally. It affects nearly 30 % of the general population. Elderly people, aged ≥65 years, are a special group of hypertensive patients. In this group, the overall prevalence of the disease reaches 60 %, rising to 70 % in those aged ≥80 years. In the elderly population, isolated systolic hypertension is quite common. High systolic blood pressure is associated with an increased risk of cardiovascular disease, cerebrovascular disease, peripheral artery disease, cognitive impairment and kidney disease. Considering the physiological changes resulting from ageing alongside multiple comorbidities, treatment of hypertension in elderly patients poses a significant challenge to treatment teams. Progressive disability with regard to the activities of daily life, more frequent hospitalisations and low quality of life are often seen in elderly patients. There is discussion in the literature regarding frailty syndrome associated with old age. Frailty is understood to involve decreased resistance to stressors, depleted adaptive and physiological reserves of a number of organs, endocrine dysregulation and immune dysfunction. The primary dilemma concerning frailty is whether it should only be defined on the basis of physical factors, or whether psychological and social factors should also be included. Proper nutrition and motor rehabilitation should be prioritised in care for frail patients. The risk of orthostatic hypotension is a significant issue in elderly patients. It results from an autonomic nervous system dysfunction and involves maladjustment of the cardiovascular system to sudden changes in the position of the body. Other significant issues in elderly patients include polypharmacy, increased risk of falls and cognitive impairment. Chronic diseases, including hypertension, deteriorate baroreceptor function and result in irreversible changes in cerebral and coronary circulation. Concurrent frailty or other components of geriatric syndrome in elderly patients are associated with a worse perception of health, an increased number of comorbidities and social isolation of the patient. It may also interfere with treatment adherence. Identifying causes of non-adherence to pharmaceutical treatment is a key factor in planning therapeutic interventions aimed at increasing control, preventing complications, and improving long-term outcomes and any adverse effects of treatment. Diagnosis of frailty and awareness of the associated difficulties in adhering to treatment may allow targeting of those elderly patients who have a poorer prognosis or may be at risk of complications from untreated or undertreated hypertension, and for the planning of interventions to improve hypertension control.
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The prevention and diagnosis of frailty syndrome (FS) in cardiac patients requires innovative systems to support medical personnel, patient adherence, and self-care behavior. To do so, modern medicine uses a supervised machine learning approach (ML) to study the psychosocial domains of frailty in cardiac patients with heart failure (HF). This study aimed to determine the absolute and relative diagnostic importance of the individual components of the Tilburg Frailty Indicator (TFI) questionnaire in patients with HF. An exploratory analysis was performed using machine learning algorithms and the permutation method to determine the absolute importance of frailty components in HF. Based on the TFI data, which contain physical and psychosocial components, machine learning models were built based on three algorithms: a decision tree, a random decision forest, and the AdaBoost Models classifier. The absolute weights were used to make pairwise comparisons between the variables and obtain relative diagnostic importance. The analysis of HF patients’ responses showed that the psychological variable TFI20 diagnosing low mood was more diagnostically important than the variables from the physical domain: lack of strength in the hands and physical fatigue. The psychological variable TFI21 linked with agitation and irritability was diagnostically more important than all three physical variables considered: walking difficulties, lack of hand strength, and physical fatigue. In the case of the two remaining variables from the psychological domain (TFI19, TFI22), and for all variables from the social domain, the results do not allow for the rejection of the null hypothesis. From a long-term perspective, the ML based frailty approach can support healthcare professionals, including psychologists and social workers, in drawing their attention to the nonphysical origins of HF.
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Abstract Introduction: More and more researchers are convinced that frailty should refer not only to physical limitations but also to psychological and social limitations that older people may have. Such a broad, or multidimensional, definition of frailty fits better with nursing, in which a holistic view of human beings, and thus their total functioning, is the starting point. Purpose: In this article, which should be considered a Practice Update, we aim at emphasizing the importance of the inclusion of other domains of human functioning in the definition and measurement of frailty. In addition, we provide a description of how district nurses view frailty in older people. Finally, we present interventions that nurses can perform to prevent or delay frailty or its adverse outcomes. We present, in particular, results from studies in which the Tilburg Frailty Indicator, a multidimensional frailty instrument, was used. Conclusion: The importance of a multidimensional assessment of frailty was demonstrated by usually satisfactory results concerning adverse outcomes of mortality, disability, an increase in healthcare utilization, and lower quality of life. Not many studies have been performed on nurses’ opinions about frailty. Starting from a multidimensional definition of frailty, encompassing physical, psychological, and social domains, nurses are able to assess and diagnose frailty and conduct a variety of interventions to prevent or reduce frailty and its adverse effects. Because nurses come into frequent contact with frail older people, we recommend future studies on opinions of nurses about frailty (e.g., screening, prevention, and addressing).
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Objective: The Tilburg Frailty Instrument (TFI) is an instrument for assessing frailty in community-dwelling older people. Since its development, many studies have been carried out examining the psychometric properties. The aim of this study was to provide a review of the main findings with regard to the reliability and validity of the TFI. Methods: We conducted a literature search in the PubMed and CINAHL databases on May 30, 2020. An inclusion criterion was the use of the entire TFI, part B, referring to the 15 components. No restrictions were placed on language or year of publication. Results: In total, 27 studies reported about the psychometric properties of the TFI. By far, most of the studies (n = 25) were focused on community-dwelling older people. Many studies showed that the internal consistency and test–retest reliability are good, which also applies for the criterion and construct validity. In many studies, adverse outcomes of interest were disability, increased health-care utilization, lower quality of life, and mortality. Regarding disability, studies predominantly show results that are excellent, with an area under the curve (AUC) >0.80. In addition, the TFI showed good associations with lower quality of life and the findings concerning mortality were at least acceptable. However, the association of the TFI with some indicators of health-care utilization can be indicated as poor (eg, visits to a general practitioner, hospitalization). Conclusion: Since population aging is occurring all over the world, it is important that the TFI is available and well known that it is a user-friendly instrument for assessing frailty and its psychometric properties being qualified as good. The findings of this assessment can support health-care professionals in selecting interventions to reduce frailty and delay its adverse outcomes, such as disability and lower quality of life.
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Abstract Background: Multidimensional frailty, including physical, psychological, and social components, is associated to disability, lower quality of life, increased healthcare utilization, and mortality. In order to prevent or delay frailty, more knowledge of its determinants is necessary; one of these determinants is lifestyle. The aim of this study is to determine the association between lifestyle factors smoking, alcohol use, nutrition, physical activity, and multidimensional frailty. Methods: This cross-sectional study was conducted in two samples comprising in total 45,336 Dutch communitydwelling individuals aged 65 years or older. These samples completed a questionnaire including questions about smoking, alcohol use, physical activity, sociodemographic factors (both samples), and nutrition (one sample). Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Results: Higher alcohol consumption, physical activity, healthy nutrition, and less smoking were associated with less total, physical, psychological and social frailty after controlling for effects of other lifestyle factors and sociodemographic characteristics of the participants (age, gender, marital status, education, income). Effects of physical activity on total and physical frailty were up to considerable, whereas the effects of other lifestyle factors on frailty were small. Conclusions: The four lifestyle factors were not only associated with physical frailty but also with psychological and social frailty. The different associations of frailty domains with lifestyle factors emphasize the importance of assessing frailty broadly and thus to pay attention to the multidimensional nature of this concept. The findings offer healthcare professionals starting points for interventions with the purpose to prevent or delay the onset of frailty, so communitydwelling older people have the possibility to aging in place accompanied by a good quality of life.
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Abstract: Background: Little is known about frailty among patients hospitalized with heart failure (HF). To date, the limited information on frailty in HF is based on a unidimensional view of frailty, in which only physical aspects are considered when determining frailty. The aims of this study were to study different dimensions of frailty (physical, psychological and social) in patients with HF and the effect of different dimensions of frailty on the incidence of heart failure. Methods: The study used a cross-sectional design and included 965 patients hospitalized for heart failure and 164 healthy controls. HF was defined according to the ESC guidelines. The Tilburg Frailty Indicator (TFI) was used to assess frailty. Probit regression analyses and chi-square statistics were used to examine associations between the occurrence of heart failure and TFI domains of frailty. Results: Patients diagnosed with frailty were 15.3% more likely to develop HF compared to those not diagnosed with frailty (p < 0.001). An increase in physical, psychological and social frailty corresponded to an increased risk of HF of 2.9% (p < 0.001), 4.4% (p < 0.001) and 6.6% (p < 0.001), respectively. Conclusions: We found evidence of the association between different dimensions of frailty and incidence of HF.
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BACKGROUND: Preventing metabolic syndrome (MetS) and frailty in older adults is crucial for healthy aging. The association between MetS and physical frailty is well-documented, with low-grade inflammation as potential explanation. However, the association between MetS and frailty as a multidimensional concept, and the association of low-grade inflammation with presence of MetS and frailty, is yet unclear. Therefore, we examined these associations low-grade inflammation in a large cohort of community-dwelling older adults.METHODS: This cross-sectional study was performed among adults aged ≥ 65 years enrolled in the Dutch Lifelines population cohort. MetS was defined according to the Joint Interim Statement of 2009. Frailty was measured by the Groningen Frailty Indicator (GFI), which consists of 15 self-reported items on both physical and psychosocial functioning, with a score ≥ 4 indicating presence of frailty. The association between MetS and its five components and frailty was assessed using logistic regression models. Low-grade inflammation was represented by high-sensitivity C-reactive protein (hsCRP) level. The association of hsCRP level with presence of MetS and frailty was assessed using multinomial logistic regression in a sub-cohort with available hsCRP measurements.RESULTS: Of 11,552 adults (52.1% women) included, the prevalences of MetS and frailty were 28% and 15%, respectively. MetS was positively associated with frailty after adjusting for relevant covariates (OR: 1.37; 95% CI: 1.22-1.53). MetS components elevated blood pressure was most strongly associated with frailty. In the sub-cohort of 3896 participants, high hsCRP was associated with presence of MetS and frailty (OR: 1.31; 95% CI: 1.15-1.51), and MetS alone (OR: 1.44; 95% CI: 1.33-1.56), but not to frailty alone. A higher hsCRP level was associated with a higher score on the physical domain of frailty (b: 0.06; 95% CI: 0.03-0.08).CONCLUSIONS: Presence of MetS is associated with presence of frailty indicated by a multidimensional index in a large group of Dutch older adults. Low-grade inflammation, indicated by plasma hsCRP level, was found to be associated with both presence of MetS and frailty and presence of MetS alone. Increased hsCRP levels were associated with the physical component of frailty, but not with frailty as a multidimensional concept.
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Abstract: Existing frailty models have enhanced research and practice; however, none of the models accounts for the perspective of older adults upon defining and operationalizing frailty. We aim to propose a mixed conceptual model that builds on the integral model while accounting for older adults’ perceptions and lived experiences of frailty. We conducted a traditional literature review to address frailty attributes, risk factors, consequences, perceptions, and lived experiences of older adults with frailty. Frailty attributes are vulnerability/susceptibility, aging, dynamic, complex, physical, psychological, and social. Frailty perceptions and lived experience themes/subthemes are refusing frailty labeling, being labeled “by others” as compared to “self-labeling”, from the perception of being frail towards acting as being frail, positive self-image, skepticism about frailty screening, communicating the term “frail”, and negative and positive impacts and experiences of frailty. Frailty risk factors are classified into socio-demographic, biological, physical, psychological/cognitive, behavioral, and situational/environmental factors. The consequences of frailty affect the individual, the caregiver/family, the healthcare sector, and society. The mixed conceptual model of frailty consists of interacting risk factors, interacting attributes surrounded by the older adult’s perception and lived experience, and interacting consequences at multiple levels. The mixed conceptual model provides a lens to qualify frailty in addition to quantifying it.
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