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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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 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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BACKGROUND: Patients' self-care behaviour is still suboptimal in many heart failure (HF) patients and underlying mechanisms on how to improve self-care need to be studied.AIMS: (1) To describe the trajectory of patients' self-care behaviour over 1 year, (2) to clarify the relationship between the trajectory of self-care and clinical outcomes, and (3) to identify factors related to changes in self-care behaviour.METHODS: In this secondary analysis of the COACH-2 study, 167 HF patients (mean age 73 years) were included. Self-care behaviour was assessed at baseline and after 12 months using the European Heart Failure Self-care Behaviour scale. The threshold score of ⩾70 was used to define good self-care behaviour.RESULTS: Of all patients, 21% had persistent poor self-care behaviour, and 27% decreased from good to poor. Self-care improved from poor to good in 10%; 41% had a good self-care during both measurements. Patients who improved self-care had significantly higher perceived control than those with persistently good self-care at baseline. Patients who decreased their self-care had more all-cause hospitalisations (35%) and cardiovascular hospitalisations (26%) than patients with persistently good self-care (2.9%, p < 0.05). The prevalence of depression increased at 12 months in both patients having persistent poor self-care (0% to 21%) and decreasing self-care (4.4% to 22%, both p < 0.05).CONCLUSION: Perceived control is a positive factor to improve self-care, and a decrease in self-care is related to worse outcomes. Interventions to reduce psychological distress combined with self-care support could have a beneficial impact on patients decreasing or persistently poor self-care behaviour.
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BACKGROUND:: Physical activity is the only nonpharmacological therapy that is proven to be effective in heart failure (HF) patients in reducing morbidity. To date, little is known about the levels of daily physical activity in HF patients and about related factors. OBJECTIVE:: The objectives of this study were to (a) describe performance-based daily physical activity in HF patients, (b) compare it with physical activity guidelines, and (c) identify related factors of daily physical activity. METHODS:: The daily physical activity of 68 HF patients was measured using an accelerometer (SenseWear) for 48 hours. Psychological characteristics (self-efficacy, motivation, and depression) were measured using questionnaires. To have an indication how to interpret daily physical activity levels of the study sample, time spent on moderate- to vigorous-intensity physical activities was compared with the 30-minute activity guideline. Steps per day was compared with the criteria for healthy adults, in the absence of HF-specific criteria. Linear regression analyses were used to identify related factors of daily physical activity. RESULTS:: Forty-four percent were active for less than 30 min/d, whereas 56% were active for more than 30 min/d. Fifty percent took fewer than 5000 steps per day, 35% took 5000 to 10 000 steps per day, and 15% took more than 10 000 steps per day. Linear regression models showed that New York Heart Association classification and self-efficacy were the most important factors explaining variance in daily physical activity. CONCLUSIONS:: The variance in daily physical activity in HF patients is considerable. Approximately half of the patients had a sedentary lifestyle. Higher New York Heart Association classification and lower self-efficacy are associated with less daily physical activity. These findings contribute to the understanding of daily physical activity behavior of HF patients and can help healthcare providers to promote daily physical activity in sedentary HF patients.PMID:23416939DOI: 10.1097/JCN.0b013e318283ba14
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Abstract People over 65 years of age constitute over 80% of patients with heart failure (HF) and the incidence of HF is 10 per 1,000 in people aged above 65 years. Approximately 25% of older patients with HF exhibit evidence of frailty. Frail patients with cardiovascular disease (CVD) have a worse prognosis than non-frail patients, and frailty is an independent risk factor for incident HF among older people. Planning the treatment of individuals with HF and concomitant frailty, one should consider not only the limitations imposed by frailty syndrome (FS) but also those associated with the underlying heart disease. It needs to be emphasized that all patients with HF and concomitant FS require individualized treatment.
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AimsKnowledge of patient preferences is vital for delivering optimal healthcare. This study uses utility measurement to assess the preferences of heart failure (HF) patients regarding quality of life or longevity. The utility approach represents the perspective of a patient; facilitates the combination of mortality, morbidity, and treatment regimen into a single score; and makes it possible to compare the effects of different interventions in healthcare.Methods and resultsPatient preferences of 100 patients with HF were assessed in interviews using the time trade-off (TTO) approach. Health-related quality of life (HR-QoL) was assessed with the EQ-5D and the Minnesota Living with Heart Failure Questionnaire (MLHFQ). Patients' own estimation of life expectancy was assessed with a visual analogue scale (VAS). Of the 100 patients (mean age 70 ± 9 years; 71% male), 61% attach more weight to quality of life over longevity; while 9% and 14% were willing to trade 6 and 12 months, respectively, for perfect health and attach more weight to quality of life. Patients willing to trade time had a significantly higher level of NT-proBNP and reported significantly more dyspnoea during exertion. Predictors of willingness to trade time were higher NT-proBNP and lower EQ VAS.ConclusionThe majority of HF patients attach more weight to quality of life over longevity. There was no difference between both groups with respect to life expectancy described by the patients. These insights enable open and personalized discussions of patients' preferences in treatment and care decisions, and could guide the future development of more patient-centred care. © 2013 Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2013. For permissions please email: journals.permissions@oup.com.
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The author reflects on the need for a comprehensive assessment of the structure and quality of the family or social network given that relationships are affected after the diagnosis of a cardiovascular disease. He points out that families may experience changing needs for support during the disease trajectory and emotional support may be necessary to cope with changing roles. He advocates for a family-oriented approach for patients with heart failure and their families.
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Rationale To improve the quality of exercise-based cardiac rehabilitation (CR) in patients with chronic heart failure (CHF) a practice guideline from the Dutch Royal Society for Physiotherapy (KNGF) has been developed. Guideline development A systematic literature search was performed to formulate conclusions on the efficacy of exercise-based intervention during all CR phases in patients with CHF. Evidence was graded (1–4) according the Dutch evidence-based guideline development criteria. Clinical and research recommendations Recommendations for exercise-based CR were formulated covering the following topics: mobilisation and treatment of pulmonary symptoms (if necessary) during the clinical phase, aerobic exercise, strength training (inspiratory muscle training and peripheral muscle training) and relaxation therapy during the outpatient CR phase, and adoption and monitoring training after outpatient CR. Applicability and implementation issues This guideline provides the physiotherapist with an evidence-based instrument to assist in clinical decision-making regarding patients with CHF. The implementation of the guideline in clinical practice needs further evaluation. Conclusion This guideline outlines best practice standards for physiotherapists concerning exercise-based CR in CHF patients. Research is needed on strategies to improve monitoring and follow-up of the maintenance of a physical active lifestyle after supervised CR.
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BACKGROUND: Since the number of heart failure (HF) patients is still growing and long-term treatment of HF patients is necessary, it is important to initiate effective ways for structural involvement of primary care services in HF management programs. However, evidence on whether and when patients can be referred back to be managed in primary care is lacking.AIM: To determine whether long-term patient management in primary care, after initial optimisation of pharmacological and non-pharmacological treatment in a specialised HF clinic, is equally effective as long-term management in a specialised HF clinic in terms of guideline adherence and patient compliance.METHOD: The study is designed as a randomised, controlled, non-inferiority trial. Two-hundred patients will be randomly assigned to be managed and followed in primary care or in a HFclinic. Patients are eligible to participate if they are (1) clinically stable, (2) optimally up-titrated on medication (according to ESC guidelines) and, (3) have received optimal education and counselling on pre-specified issues regarding HF and its treatment. Furthermore, close cooperation between secondary and primary care in terms of back referral to or consultation of the HF clinic will be provided.The primary outcome will be prescriber adherence and patient compliance with medication after 12 months. Secondary outcomes measures will be readmission rate, mortality, quality of life and patient compliance with other lifestyle changes.EXPECTED RESULTS: The results of the study will add to the understanding of the role of primary care and HF clinics in the long-term follow-up of HF patients.
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