Background: Osteoporosis is a socio-economic problem of modern aging societies. Bone fractures and the related treatments generate the highest costs. The occurrence of osteoporotic fractures is a cause of chronic disability, many complications, reduced quality of life, and often premature death. Aim of the study: The aim of the study was to determine which of the patient’s potential risk factors pertaining to various diseases and lifestyle have an essential impact on the occurrence of low-energy fractures and the hierarchy of these factors. Methods: The study was retrospective. The documentation of 222 patients (206 women and 16 men) from an osteoporosis treatment clinic in Łódź, Poland was analyzed. Each patient was described by a vector consisting of 27 features, where each feature was a different risk factor. Using artificial neural networks, an attempt was made to create a model that, based on the available data, would be able to predict whether the patient would be exposed to low-energy fractures. We developed a neural network model that achieved the best result for the testing data. In addition, we used other methods to solve the classification problem, i.e., correctly dividing patients into two groups: those with fractures and those without fractures. These methods were logistic regression, k-nearest neighbors and SVM. Results: The obtained results gave us the opportunity to assess the effectiveness of various methods and the importance of the features describing patients. Using logistic regression and the recursive elimination of features, a ranking of risk factors was obtained in which the most important were age, chronic kidney disease, neck T-score, and serum phosphate level. Then, we repeated the learning procedure of the neural network considering only these four most important features. The average mean squared error on the test set was about $27\%$ for the best variant of the model. Conclusions: The comparison of the rankings with different numbers of patients shows that the applied method is very sensitive to changes in the considered data (adding new patients significantly changes the result). Further cohort studies with more patients and more advanced methods of machine learning may be needed to identify other significant risk factors and to develop a reliable fracture risk system. The obtained results may contribute to the improved identification patients at risk of low-energy fractures and early implementation of comprehensive treatment.

Background: The impact of cardiac rehabilitation on the number of alerts in patients with remote monitoring (RM) of cardiac implantable electronic devices (CIEDs) is unknown. We compared alerts in RM and outcomes in patients with CIEDs undergoing hybrid comprehensive telerehabilitation (HCTR) versus usual care (UC). Methods: Patients with heart failure (HF) after a hospitalization due to worsening HF within the last 6 months (New York Heart Association (NYHA) class I-III and left ventricular ejection fraction (LVEF) ≤40%) were enrolled in the TELEREH-HF study and randomised 1:1 to HCTR or UC. Patients with HCTR and CIEDs received RM (HCTR-RM). Patients with UC and CIEDs were offered RM optionally (UC-RM). Data from the initial 9 weeks of the study were analysed. Results: Of 850 enrolled patients, 208 were in the HCTR-RM group and 62 in the UC-RM group. The HCTR-RM group was less likely to have alerts of intrathoracic impedance (TI) decrease (p < 0.001), atrial fibrillation (AF) occurrence (p = 0.031) and lower mean number of alerts per patient associated with TI decrease (p < 0.0001) and AF (p = 0.019) than the UC-RM group. HCTR significantly decreased the occurrence of alerts in RM of CIEDs, 0.360 (95%CI, 0.189–0.686; p = 0.002), in multivariable regression analysis. There were two deaths in the HCTR-RM group (0.96%) and no deaths in the UC-RM group (p = 1.0). There were no differences in the number of hospitalised patients between the HCTR-RM and UC-RM group (p = 1.0). Conclusions: HCTR significantly reduced the number of patients with RM alerts of CIEDs related to TI decrease and AF occurrence. There were no differences in mortality or hospitalisation rates between HCTR-RM and UC-RM groups.

Methylation is a biochemical process involving the addition of a methyl group (-CH₃) to various chemical compounds. It plays a crucial role in maintaining the homeostasis of the endothelium, which lines the interior surface of blood vessels, and has been linked, among other conditions, to coronary artery disease (CAD). Despite significant progress in CAD diagnosis and treatment, intensive research continues into genotypic and phenotypic CAD biomarkers. This review explores the significance of the methylation pathway and folate metabolism in CAD pathogenesis, with a focus on endothelial dysfunction resulting from deficiency in the active form of folate (5-MTHF). We discuss emerging areas of research into CAD biomarkers and factors influencing the methylation process. By highlighting genetically determined methylation disorders, particularly the MTHFR polymorphism, we propose the potential use of the active form of folate (5-MTHF) as a novel CAD biomarker and personalized pharmaceutical for selected patient groups. Our aim is to improve the identification of individuals at high risk of CAD and enhance their prognosis.

Background: Patients with peripheral artery disease (PAD) often experience intermittent claudication. It is manifested by pain typically seen in the distal part of the legs during walking, which impairs the ability to walk, limits physical activity and results in lower health-related quality of life. It often leads to chronic ischemic pain, ulceration and even amputation. The aim of the study was to evaluate the effect of controlled physical training and whirlpool massage on changes in circuits, range of motion and distance of claudication in people with atherosclerotic ischemia of the lower limbs. Material and methods: The study included 100 patients, males and females aged 39 to 79 years, with peripheral circulation disorders of the lower limbs. The subjects were randomly divided into two groups. Group I (G) was treated with a series of 10 lower-limb whirling massages and took part in individually planned training, including breathing, relaxation and active free lower-limb exercises. Group II-control group (GC) took part only in individually planned training. Prior to the treatment procedures and after their completion, the ranges of movement of the ankle joint and the circumference of the lower limbs were measured and the corridor test (6MWT, six-minute walk test) was performed. Results: Statistically significant reduction in the circumference of the foot, ankle, calf and thigh in the G group was noticed. Both, in G and in GC group, a statistically significant increase in the range of dorsiflexion of the foot was found in comparison to the period before the procedures (p = 0.010; p = 0.006, respectively). There was also a statistically significant increase in the range of motion of the plantar flexion of the foot after the procedures in G (p = 0.007) and in GC (p = 0.048). Differences in the circumference of the lower limbs and the range of ankle joint movements between the study group and the control group before and after the therapy were not statistically significant. However, there was a statistically significant difference between these groups after the procedures in the 6-min walk test—significantly higher values of 6MWT were recorded in group G (p = 0.003). Conclusions: Individually planned training, supplemented with hydrotherapy as thermal therapy, has a beneficial effect on reducing swelling of the lower limbs, increasing the range of foot movements and extending the distance in the 6-min walk test.