Background: Diagnosing post-COVID syndrome (PCS) in older adults with hypertension is difficult due to heterogeneity and multimorbidity. We aimed to identify factors associated with PCS. Methods: An observational study was conducted from June 2024 to April 2025. Patients aged 60–89 years with arterial hypertension were enrolled; PCS was verified according to the national protocol. Between-group comparisons used standard tests. Multivariable logistic regression with pre-specified clinical predictors estimated independent associations. Results: A total of 291 patients with arterial hypertension were included in the study. Patients were grouped by PCS status (PCS = 101; controls = 190). In multivariable analysis, female sex (OR 3.64; 95% CI 1.22–10.82), younger age (OR 0.93; 95% CI 0.89–0.98), lower systolic blood pressure (SBP) (OR 0.98; 95% CI 0.96–1.00), and rhythm disturbances (OR 2.63; 95% CI 1.07–6.49) were associated with PCS; other predictors were not significant. Model discrimination was moderate (AUC 0.728; 95% CI 0.668–0.787; Brier score 0.193) with positive net benefit across thresholds ~0.10–0.65. Conclusions: In older hypertensive adults, female sex, younger age, lower SBP, and rhythm disturbances indicate higher PCS likelihood, supporting risk-stratified monitoring and management.

The COVID-19 pandemic substantially altered the levels and structure of all-cause mortality: in addition to directlosses, indirect deaths arose due to health-system overload, delays in elective care, and changes in health-care seeking; seasonal profiles were disrupted, and the contribution of causes shifted—from infectious-respiratory to conditions whose outcomes depend on timely diagnosis and treatment. The aim of this study is to assess the impact of the COVID-19 pandemic on all-cause mortality in the Republic of Kazakhstan. We analyzed data on population counts and deaths by sex and 5-year age groups (1-4, …, ≥85) for 2015-2024; based on WHO data, periods were defined as pre-COVID (2015-2019), pandemic (2020-2023), and post-COVID (2024). Age-standardized mortality rates were calculated by the direct method using the 2013 European Standard Population (ESP 2013). Changes in levels and trends were assessed with a negative binomial model. Effects are presented as IRR (95% CI). The cause-of-deathstructure was compared using a year*cause contingency table (Pearson’s χ², Cramer’s V; standardized residuals;practical significance|r|>3). After a peak increase in standardized levels in 2020-2021, the indicators returned to the pre-COVID downward trajectory and fell below it: relative to 2019, age-standardized mortality increased by +19% in 2020 (2.113.6 vs 1.773.5 per 100.000) and by +33% in 2021 (2.358.0 per 100.000). In 2023-2024, age-standardized mortality declined to 1,504.5-1,493.7 per 100.000 (approximately 16% below 2019). Negative binomial regression showed no difference in the mean level for 2020-2023 versus pre-COVID (IRR=1.017; p=0.690) alongside an additional downward slope in the pandemic years (period*year interaction: IRR=0.960; 95% CI 0.931-0.991; p=0.012); in 2024 the level was substantially lower than pre-COVID (IRR=0.755; 95% CI 0.692-0.823). The cause-of-death structure exhibited a marked shift during the pandemic with partial normalization in 2022-2024. The pandemic had a short-term but pronounced effect on all-cause mortality, disrupting seasonal patterns and altering the cause-of-death structure while preserving age- and sex-related heterogeneity. Regular monitoring of all-cause and excess mortality should be maintained, causeof-death coding improved, and preventive and rehabilitation measures targeted to high-risk groups, taking into account possible delayed effects.

Background: Depressive symptoms are frequent sequelae of COVID-19 and may remain unrecognized in older outpatients, particularly those with post-COVID syndrome. The objective of the current study was to assess the under-detection of depressive symptoms in older ambulatory patients and to examine its relationship with post-COVID syndrome status. Methods: We conducted an observational outpatient cohort study of adults aged 60–89 years with prior SARS-CoV-2 infection (N = 85), recruited at two city polyclinics. Depressive symptoms were assessed through three detection channels: spontaneous complaint during the visit, a standardized direct question about current depressive symptoms, and the 15-item Geriatric Depression Scale (GDS-15). Agreement between complaint and direct question was evaluated using Cohen’s κ and McNemar’s test. Screening performance of complaint and direct question was assessed against GDS-15 thresholds (≥5; sensitivity analysis ≥ 6). Associations between post-COVID syndrome status and binary depressive-symptom indicators were expressed as risk ratios (RRs). Results: Spontaneous complaints missed a substantial proportion of cases: among complaint-negative patients, 18.3% (15/82) reported depressive symptoms on the direct question (κ = 0.149; McNemar p = 0.00052). Against GDS-15 ≥ 5, complaint sensitivity was 10.3% with specificity 100.0% (F1 = 0.19), whereas the direct question showed higher sensitivity (34.5%) with specificity 87.5% (F1 = 0.43). Using the alternative threshold GDS-15 ≥ 6, complaint sensitivity was 15.0% with specificity 100.0% (F1 = 0.26), and direct question sensitivity was 45.0% with specificity 87.7% (F1 = 0.49). A positive response to the direct question was more frequent in patients with post-COVID syndrome than in controls (RR = 2.70 (1.04–7.00)); stratified estimates suggested higher RRs in patients ≤ 75 years (RR = 4.55 (1.08–19.10)) and in women (RR = 2.67 (1.04–6.83)), with limited precision due to sparse events. Conclusions: In older post-COVID outpatients, reliance on spontaneous complaints leads to marked under-detection of GDS-15 screen-positive depressive symptoms. A standardized direct question improves initial case-finding but does not replace a validated screening scale; a stepped approach (brief direct question followed by a scale when indicated) may be warranted.

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide. According to the World Health Organization, approximately 19.8 million deaths were attributed to CVDs in 2022, accounting for 32% of all global deaths. Objective. To comprehensively assess the role of medical and socioeconomic factors in the development of cardiovascular diseases, determine their contribution to the prevalence of risk factors, and identify the most significant determinants influencing cardiovascular risk formation. Materials and Methods. A narrative literature review was conducted using a structured search strategy in PubMed, Scopus, and Web of Science databases covering the period 2005–2025. The review focused on the impact of social determinants of health on cardiovascular risk. Following screening and full-text assessment, 79 publications were included in the final analysis. Results. Cardiovascular diseases remain the leading cause of mortality and disability-adjusted life years (DALYs) globally, with substantial variation depending on countries’ levels of socio-demographic development. Global evidence demonstrates a consistent social gradient: low income, limited education, unsafe urban environments, and restricted access to healthcare are associated with higher CVD risk and poorer clinical outcomes. Economic and psychosocial factors (poverty, unstable employment, financial stress, depression, and social isolation), as well as environmental exposures (air pollution, noise, and limited access to green spaces), increase cardiovascular risk through behavioral and biological mechanisms, including chronic stress and systemic inflammation. In Kazakhstan, pronounced regional and urban–rural disparities highlight the need for prevention strategies that address social determinants and barriers to healthcare access. Conclusions. The most significant medical and socioeconomic determinants of CVDs were identified, and their mechanisms of influence on risk factor prevalence were established. The findings confirm the necessity of a comprehensive, multilevel approach integrating social interventions, preventive strategies, and early biomedical risk stratification.