The purpose of the study was to evaluate compliance with medical treatment in elderly patients with heart failure (HF), and to identify factors that associated with patients’ compliance levels. 475 patients (including 222 women), mean age 69.7±7.7, with HF, hospitalized at University Hospital between January and December 2018 were included in the study. The patients were selected by a physician specializing in cardiology. A cardiac nurse assessed the non-pharmacological level of compliance using the Revised Heart Failure Compliance Questionnaire (RHFCQ). The socio-clinical data were obtained from medical records. The majority of the study group were patients in NYHA II (62.4%) and NYHA III (28.3%), the mean duration of the disease was 6.2±4.9 years, and the mean ejection fraction of the left ventricle (EF) was 48.6±12.6. The average level of compliance in the study group measured on a scale from 0 to 4 points was: median = 2.7, IQR [2.32; 3.25]. Only 6.9% of the respondents adhere to recommendations totally (all dimensions of RHFCQ). In univariate analysis, predictors negatively affecting compliance were: female gender (rho = -0.325), age below 65 years (rho = -0.014)), loneliness (rho = -0.559), number of hospitalizations (rho = -0.242), higher stage of NYHA (rho = -1.612), co-morbidities (rho = -0.729), re-hospitalizations (rho = -0.729), beta-blockers treatment (rho = -1.612) and diuretics treatment (rho = -0.276). Factors positively affecting compliance were: EF≥45% (rho = 0.020) and treatment with ACEI/ARB (rho = 0.34), whereas compliance was negatively affected by–EF<45% (β = 0.009). Independent predictors influencing the level of compliance were: loneliness (β = -1.816), number of hospitalizations (β = -0.117), NYHA III and IV and number of co-morbidities (β = -0.676). Patients with HF do not adhere to therapeutic recommendations. The lowest compliance levels were found for exercise and daily weighing, and the highest for follow-up appointment-keeping and medication. Loneliness and age are the strongest predictors which influence the level of compliance.

The registration of physical signals has long been an important part of cardiological diagnostics. Current technology makes it possible to send large amounts of data to remote locations. Solutions that enable diagnosis and treatment without direct contact with patients are of enormous value, especially during the COVID-19 outbreak, as the elderly require special protection. The most important examples of telemonitoring in cardiology include the use of implanted devices such as pacemakers and defibrillators, as well as wearable sensors and data processing units. The arrythmia detection and monitoring patients with heart failure are the best studied in the clinical setting, although in many instances we still lack clear evidence of benefits of remote approaches vs. standard care. Monitoring for ischemia is less well studied. It is clear however that the economic and organizational gains of telemonitoring for healthcare systems are substantial. Both patients and healthcare professionals have expressed an enormous demand for the further development of such technologies. In addition to these subjects, in this paper we also describe the safety concerns associated with transmitting and storing potentially sensitive personal data.

In 2016 heart failure (HF) affected between 600,000 and 700,000 people in Poland being one of the most common causes of hospitalization and death. Health education is an elements of patient treatment aimed at improving the level of self-care and adherence to the treatment recommendations. To perform a systematic review and meta-analysis of the available literature in order to determine the role of health education in HF treatment and its impact on outcomes in patients with chronic HF. A search was performed in the MEDLINE, PubMed and Scopus databases from January 2010 to January 2019 for the impact of health education on treatment outcomes in HF patients. A total of 16 studies from 12 countries on 5 continents were analyzed. The meta-analysis focused on the impact of education on outcomes in 944 study group patients. We found that the overall impact of education on outcomes was positive (+1 standard deviation (SD); 95% confidence interval (CI) >0). After education was provided, the target patients improved in terms of self-care (mean change (MC) = 13.49; p = 0.003; I² = 99.47%). Self-care also improved in the controls, but the improvement was less marked (MC = 9.56; p = 0.001; I² = 98.33%). No impact of education on quality of life (QoL) was confirmed (95% CI = 0). The greatest benefit of education is seen in terms of adherence to pharmaceutical treatment and self-care, while QoL was not associated with education.

Graphene is a novel carbon-based material with unique crystal nanostructure and extraordinary physical and chemical properties. Several biomedical applications of graphene and graphene-derived materials have been proposed. Its antimicrobial properties might be useful in all areas of medicine where antiseptics are required. On the other hand, the safe limits of graphene concentration for human cells have not been clearly established yet. The possibility to attach various chemically active groups to the basic lattice structure allows researchers to build graphene-based sensors for detecting biochemical molecules (and ultimately - selected cells). Sensors for physical signals, such as cardiac electrical activity, have also been proposed. The unique nanostructure of the material and the resulting physical properties (mechanical strength, elasticity and large surface area) make it a very promising material for scaffolds used in tissue regeneration. Several studies have investigated the potential advantages of a graphene coating for endovascular implants, such as stents or valves. Most of them indicate an advantage of graphene coating over other currently available solutions in terms of better hemocompatibility and facilitating endothelialization. Many of the results published so far are from in vitro studies. Promising as they might be, more data, preferably from experiments on more sophisticated animal models, must be obtained before any valid conclusions as to potential uses of graphene in medicine can be drawn.

Introduction: Atrial fibrillation (AF) and frailty syndrome (FS) are a part of the aging process. Both are still of great importance in the assessment of quality of life (QoL). There is definitely a lack of research clarifying the association between FS and QoL in AF patients. Objective: The aim of this study was to evaluate the influence of FS on QoL in AF patients. Materials and Methods: The retrospective and observational study included 158 inpatients with mean age 69.8± 7.1 years, treated for AF in the cardiac department from 1 April 2019 to 31 June 2019. The following instruments were used: the Arrhythmia-Specific Questionnaire in Tachycardia and Arrhythmia (ASTA) and the Edmonton Frail Scale (EFS). Results: The mean level of frailty in the study group was 8.5± 5.0. In 25.9% of patients, the level of frailty was mild, in 10.1% moderate, and in 17.1% severe. Patients were divided into two groups based on their frailty status. In comparative analysis of the QoL, there were significant differences between the groups: the frail group had more intense symptoms of arrhythmia than the non-frail group (14.9± 4.1 vs 11.9± 4.9; p< 0.001). In the analysis of the total score impact of arrhythmia on QoL, the frail group had a significantly higher score than the non-frail group (23.5± 5.2 vs 14.5± 5.5), which confirmed the stronger negative impact of arrhythmia on QoL. In the regression coefficient analysis, the independent predictor of symptom severity and QoL was FS. However, we observed a negative impact of diabetes, which increased the impact of arrhythmia on QoL, and physical activity, which improved QoL and decreased the impact of symptoms on everyday life. Conclusion: Patients in the frail group have worse QoL and higher impact of arrhythmia on QoL in comparison to patients in the non-frail group. Frailty is an independent predictor of higher intensity of symptoms of arrhythmia and worse QoL. Diabetes and physical activity are predictors of QoL for patients with AF.