Background: Anemia is a serious and highly prevalent co-morbidity in chronic heart failure (HF) patients. Its influence on health-related quality of life (HR-QoL) has rarely been studied, and no data is available regarding the role it plays in hospitalized HF patients. Methods: Baseline data from the COACH study (Coordinating study evaluating Outcomes of Advising and Counselling in Heart Failure) were used. HR-QoL was assessed by means of generic and disease-specific questionnaires. Analyses were performed using ANOVA and ANCOVA, with covariates of age, gender, eGFR, diabetes, and NYHA class. Results: In total, 1013 hospitalized patients with a mean age of 71 (SD 11) years were included; 70% of these patients had no anemia (n = 712), 14% had mild anemia (n = 141), and 16% had moderate-to-severe anemia (n = 160). Independent associations were found between anemia and physical functioning (p = 0.019), anemia and role limitations due to physical functioning (p = 0.002), anemia and general health (p = 0.024), and anemia and global well-being (p = 0.003). Conclusion: In addition to the burden of HF itself, anemia is an important factor which influences HR-QoL in hospitalized HF patients, and one that is most pronounced in the domain related to physical functioning and general health. © 2012 Elsevier Ireland Ltd.
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.
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.
