Journal of Clinical Medicine of Kazakhstan

Background: Vaccine-preventable diseases such as pertussis, measles, and influenza remain among the most significant medical and socioeconomic issues in Kazakhstan, despite significant vaccination achievements. Thus, here we aimed to analyze the long-term dynamics and provide information on the current epidemiology of pertussis, measles, and influenza in Kazakhstan. Methods: A retrospective analysis of the long-term dynamics of infectious diseases was carried out using the data from the statistical collections for 2010-2020 and the Unified Payment System from 2014 to 2020. Results: During the 2010-2020 years, the long-term dynamics show an unequal distribution of pertussis, measles, and influenza-related morbidity. In comparison with earlier years, registration of infectious disease was the highest in 2019 and 2020. The incidence cases among registered infectious diseases in 2019 were: pertussis-147, measles-13,326, and in 2020: influenza-2,678. High incidence rates have been documented in Pavlodar, North Kazakhstan, Mangystau regions, and the cities of Shymkent and Nur-Sultan. The incidence varies depending on the seasonality: pertussis (summer-autumn), measles (winter-spring), and influenza (mostly in winter). Conclusion: The findings highlight the importance of focusing more on the characteristics of the epidemic process of vaccine-preventable diseases in order to assess the effectiveness of implemented measures and verify new routes in strengthening the epidemiological surveillance system.

Background: COVID-19 pandemic has presented extreme challenges to developing countries across the world. The aim of this paper was to provide estimates for current development COVID-19 pandemic in the Post-Soviet states and forecast potential best and worst scenarios for spread of this deadly infection. Methods: The data on COVID-19 cases extracted from official governmental sources until April 18, 2020. A modified SEIR (Susceptible-Exposed-Infected-Recovered) modelling was used to plot the pandemic outbreak in 10 Post-Soviet states and forecasting over the period of 10, 30 and 60 days. The optimal measures (best-scenario) and suboptimal measures (worst-scenarios) of potential spread of COVID-19 in these countries were estimated. Results: It was estimated that Armenia and Azerbaijan have reached their peaks, Kazakhstan, Kyrgyzstan, Moldova, and Uzbekistan are expected to reach their peaks in the early May-2020), with comparatively low cases of COVID-19 in the best-case scenario. In contrast, Belarus, Russia, and Ukraine would likely see the outbreaks with the largest number of COVID-19 cases amongst the studied Post-Soviet States in the worst-scenario during the next 30 and 60 days. Conclusion: Governmental response was shown to be as an important determining factor responsible for the development of COVID-19 epidemic in Post-Soviet states. The current protection rates should be maintained to reduce active cases during upcoming 30 and 60 days. The estimated possible scenarios based on the proposed model can potentially be used by healthcare professionals from each studied Post-Soviet States as well as others to improve plans to contain the current and future epidemic.

BACKGROUND: We hypothesize that oxygen consumption (V̇ o ₂ ) estimation in patients with respiratory symptoms is inaccurate and can be improved by considering arterial blood gases or spirometric variables. METHODS: For this retrospective study, we included consecutive subjects who underwent cardiopulmonary exercise testing. Resting V̇ o ₂ was determined using breath-by-breath testing methodology. Using a training cohort ( n = 336), we developed 3 models to predict V̇ o ₂ . In a validation group ( n = 114), we compared our models with 7 available formulae. RESULTS: Our first model (V̇ o ₂ = −184.99 + 189.64 × body surface area [BSA, m ² ] + 1.49 × heart rate [beats/min] + 51.51 × F IO ₂ [21% = 0; 30% = 1] + 30.62 × gender [male = 1; female = 0]) showed an R ² of 0.5. Our second model (V̇ o ₂ = −208.06 + 188.67 × BSA + 1.38 × heart rate + 35.6 × gender + 2.06 × breathing frequency [breaths/min]) showed an R ² of 0.49. The best R ² (0.68) was obtained with our last model, which included minute ventilation (V̇ o ₂ = −142.92 + 0.52 × heart rate + 126.84 × BSA + 14.68 × minute ventilation [L]). In the validation cohort, these 3 models performed better than other available equations, but had wide limits of agreement, particularly in older individuals with shorter stature, higher heart rate, and lower maximum voluntary ventilation. CONCLUSIONS: We developed more accurate formulae to predict resting V̇ o ₂ in subjects with respiratory symptoms; however, equations had wide limits of agreement, particularly in certain groups of subjects. Arterial blood gases and spirometric variables did not significantly improve the predictive equations.

Background: COVID-19 pandemic has presented extreme challenges to developing countries across the world. Post-Soviet states are facing unique challenges due to their developing healthcare systems and unstable economy. The aim of this paper was to provide estimates for current development COVID-19 pandemic in the Post-Soviet states and forecast potential best and worst scenarios for spread of this deadly infection. Methods: The data on confirmed cases and deaths were extracted from official governmental sources for a period from beginning of outbreak dates for each country until April 18, 2020. A modified SEIR (Susceptible-Exposed-Infected-Recovered) modelling was used to plot the parameters of epidemic in 10 post-Soviet states and forecast the number of cases over a period of 10, 30 and 60 days. We also estimated the numbers of cases based on the optimal measures (best scenario) and suboptimal measures (worst scenarios) of potential spread of COVID-19 in these countries. Results: It was estimated that Armenia and Azerbaijan have reached their peaks, Kazakhstan, Kyrgyzstan, Moldova and Uzbekistan are expected to reach their peaks in the coming week (April 29 – May 7, 2020), with comparatively low cases of COVID-19 and loss of lives in the best-case scenario. In contrast, Belarus, Russia, and Ukraine would likely see the outbreaks with the largest number of COVID-19 cases amongst the studied Post-Soviet States in the worst scenario during the next 30 and 60 days. Geographical remoteness and small number of international travelers from the countries heavily affected by the pandemic could also have contributed to delay in the spread of COVID-19. Conclusion: Governmental response was shown to be as an important determining factor responsible for the development of COVID-19 epidemic in Post-Soviet states. The current protection rates should be maintained to reduce active cases during upcoming 30 and 60 days. The estimated possible scenarios based on the proposed model can potentially be used by healthcare professionals from each studied Post-Soviet States as well as others to improve plans to contain the current and future epidemic.

Introduction: Cardiovascular diseases (CVDs) remain the leading cause of mortality and disability in Central Asia. This study analyzes trends in CVD burden across nine countries from 1990 to 2021, identifies major subtypes, explores sex and country-level disparities, and forecasts trends through 2050. Methods: We used data from the Global Burden of Disease (GBD) 2021 study to assess age-standardized death rates (ASDRs) and age-standardized disability-adjusted life years (ASYRs) for CVDs and their subtypes in Armenia, Azerbaijan, Georgia, Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan, Turkmenistan, and Uzbekistan. Forecasts were generated using GBD reference and alternative risk-reduction scenarios. Results: In 2021, the average ASDR for CVDs in the region was 436.1 per 100,000 population, nearly twice that for respiratory infections and tuberculosis. Ischemic heart disease (IHD) and stroke accounted for 89% of total CVD deaths. Turkmenistan reported the highest ASDR (552.2 per 100,000), while Armenia reported the lowest (314.8 per 100,000). Kazakhstan had the highest stroke-related ASDR at 163.0 per 100,000. Men experienced 1.5 times higher ASDR (538.2 vs. 365.7 per 100,000) and ASYR (10966.6 vs. 6807.5 per 100,000) than women. While most countries reduced ASDRs from 1990 to 2021, Uzbekistan showed a 0.7% increase. Forecasts project a regional decline in ASDR by 2050 in both improved-risk-factor and reference scenarios. Conclusion: CVDs remain the dominant health burden in Central Asia. Evidence-based prevention, improved hypertension control, and health system strengthening are essential to achieving future gains and reducing premature cardiovascular mortality.