By 2050, the proportion of people over 60 years of age worldwide is expected to be 22 %, and the number of people over 80 is expected to triple by that time, reaching 426 million. Population aging threatens the sustainable functioning of national health care systems, since the increase in the proportion of the elderly population is accompanied by increased costs for the health care system and a decrease in the availability of medical care for other age groups. Based on the analysis and synthesis of data from foreign publications on the impact of population aging on the sustainability of the functioning of national healthcare systems, proposed measures and models of medical care that take into account changes in the age structure of the population are systematized. Analysis of foreign publications made it possible to identify the following challenges for the healthcare system associated with the aging population: rising costs of providing medical care, the need to increase emphasis on preventive measures, increasing prevalence and severity of chronic non-communicable diseases and comorbidity, inequality in access to medical care, expressed in territorial (regional), age and gender aspects, as well as determined by the socio-economic status of a person. Experts suggest that the most obvious and realistic solution to the problem is active prevention of chronic diseases and more intensive monitoring of the health status of the population. Digital solutions that provide disease prevention and remote monitoring of the health status of the elderly population, based on the use of machine learning technologies, artificial intelligence and telemedicine technologies, are identified as promising areas for limiting healthcare costs.

This study aims to establish relationships between inflammatory status, ferrokinetics and lipid metabolism in patients with diabetes mellitus. Subclinical inflammation was assessed by levels of high-sensitive C-reactive protein, tumor necrosis factor-α and erythrocyte sedimentation rate. Iron metabolism parameters included complete blood count, serum iron, transferrin and ferritin. Metabolic status assessment included lipid profile, glycated hemoglobin and microalbuminuria measurement. As a result of the study it was possible to establish both general (universal) and diabetes mellitus (DM) type-dependent relationships between the parameters of lipid profile and metabolic control in DM. High-density lipoprotein cholesterol (HDL-C) levels negatively correlated with microalbuminuria (r = −0.293; p ˂ 0.05 for type 1 diabetes and r = −0.272; p ˂ 0.05 for type 2 diabetes). Ferritin concentration positively correlated with triglyceride level (r = 0.346; p ˂ 0.05 for type 1 diabetes and r = 0.244; p ˂ 0.05 for type 2 diabetes). In type 1 diabetes, a negative correlation was discovered between estimated glomerular filtration rate (eGFR) and LDL-C (r = −0.480; p ˂ 0.05), very low-density-lipoprotein cholesterol (VLDL-C) (r = −0.490; p ˂ 0.05) and triglycerides (r = −0.553; p ˂ 0.05), and a positive one between C-reactive protein concentration and triglyceride level (r = 0.567; p ˂ 0.05). Discovered relationships between lipid profile indices, inflammatory status and microalbuminuria confirmed mutual influence of hyperlipidemia, inflammation and nephropathy in diabetes patients. Obtained results justify the strategy of early hypolipidemic therapy in patients with diabetes mellitus to prevent the development and progression of microvascular complications.

Diabetes mellitus type 1 and 2 is associated with cognitive impairment. Previous studies have reported a relationship between changes in cerebral metabolite levels and the variability of glycemia. However, the specific risk factors that affect the metabolic changes associated with type 1 and type 2 diabetes in cognitive dysfunction remain uncertain. The aim of the study was to evaluate the specificity of hippocampal spectroscopy in type 1 and type 2 diabetes and cognitive dysfunction. Materials and methods: 65 patients with type 1 diabetes with cognitive deficits and 20 patients without, 75 patients with type 2 diabetes with cognitive deficits and 20 patients without have participated in the study. The general clinical analysis and evaluation of risk factors of cognitive impairment were carried out. Neuropsychological testing included the Montreal Scale of Cognitive Dysfunction Assessment (MoCA test). Magnetic resonance spectroscopy (MRS) was performed in the hippocampal area, with the assessment of N-acetylaspartate (NAA), choline (Cho), creatine (Cr), and phosphocreatine (PCr) levels. Statistical processing was performed using the commercially available IBM SPSS software. Results: Changes in the content of NAA, choline Cho, phosphocreatine Cr2 and their ratios were observed in type 1 diabetes. More pronounced changes in hippocampal metabolism were observed in type 2 diabetes for all of the studied metabolites. Primary risk factors of neurometabolic changes in patients with type 1 diabetes were episodes of severe hypoglycemia in the history of the disease, diabetic ketoacidosis (DKA), chronic hyperglycemia, and increased body mass index (BMI). In type 2 diabetes, arterial hypertension (AH), BMI, and patient’s age are of greater importance, while the level of glycated hemoglobin (HbA1c), duration of the disease, level of education and insulin therapy are of lesser importance. Conclusion: Patients with diabetes have altered hippocampal metabolism, which may serve as an early predictive marker. The main modifiable factors have been identified, correction of which may slow down the progression of cognitive dysfunction.

Background and Objectives: In-hospital mortality associated with myocardial infarction complicated by cardiogenic shock (MI-CS) remains critically high. A particularly challenging form, mixed shock (MS), combines features of cardiogenic shock (CS) with distributive elements such as vasodilation and reduced vascular resistance. MS is associated with elevated mortality rates and presents unique diagnostic and therapeutic challenges. This study aimed to analyze the clinical, historical, instrumental, and laboratory characteristics of the primary phenotypes of MI-CS, stratified according to the Society for Cardiovascular Angiography and Interventions (SCAI) shock severity scale. Materials and Methods: In this single-center, retrospective observational study, we reviewed the medical records of 1289 patients admitted to the emergency cardiology department from 1 January to 12 December 2020. Among them, 117 patients were identified as having MI-CS and were divided into two groups: MS (n = 48) and isolated CS (n = 69). The data were analyzed using the SCAI shock classification. Logistic regression analysis was employed to identify predictors of mortality and improved survival outcomes. Results: Patients with MS were older (80 years [71.0; 83.0] vs. 73 years [64.0; 81.0], p = 0.035). The overall mortality rate was significantly higher in the MS group (68% vs. 53%, RR = 1.438, 95% CI: 1.041–1.986, p = 0.03). Logistic regression identified mechanical ventilation (OR = 8.33, 95% CI: 2.54–22.80, p = 0.012), elevated lactate levels (OR = 1.20, 95% CI: 1.02–1.41, p = 0.026), and cardiopulmonary resuscitation (CPR) (OR = 7.97, 95% CI: 2.51–24.40, p < 0.0001) as independent predictors of mortality. Conversely, the use of an intra-aortic balloon pump (IABP) (OR = 0.22, 95% CI: 0.06–0.80, p = 0.021) and a higher body mass index (BMI) (OR = 0.91, 95% CI: 0.84–0.99, p = 0.038) were associated with reduced mortality risk. Conclusions: MS in the context of MI-CS represents a distinct clinical phenotype with specific hemodynamic features and significantly worsened outcomes. The identification of mortality predictors, such as mechanical ventilation, elevated lactate levels, and CPR, alongside protective factors like IABP use and a higher BMI, underscores the importance of early and tailored therapeutic interventions. These findings highlight the need for further studies to refine treatment protocols and improve outcomes in this high-risk population.

The dynamics of the force–interval relationship of the human myocardium in coronary artery disease (CAD) and CAD with concomitant diabetes mellitus was studied, and its dependence on the level of sarcoplasmic reticulum (SR) Ca²⁺-ATPase expression was evaluated. The study was performed on myocardial biopsy material obtained during coronary bypass operation using cardiopulmonary techniques. Patients with chronic CAD and patients with CAD associated with type II diabetes mellitus were enrolled in the study. It was found that CAD patients with and without diabetes mellitus with similar clinical parameters had either negative or positive dynamics of the force–interval relationship. The positive force–interval relationship was associated with a “high level” of Ca²⁺-ATPase, while the negative force–interval relationship was associated with a “low level” of this protein. In CAD associated with diabetes mellitus of short duration, the positive dynamics of the force–interval relationship is more pronounced and corresponds to a higher level of SR Ca²⁺-ATPase expression than in CAD alone.