Analysis of chronic kidney disease epidemiology in Kazakhstan using nationwide data for 2014-2020 and forecasting future trends of prevalence and mortality for 2030.

According to the Global Burden of Disease (GBD) study, chronic kidney disease (CKD) was prevalent in 697.5 million individuals worldwide in 2017. By 2040, it is anticipated that CKD will rank as the fifth most common cause of death. This study aims to examine the epidemiology of CKD in Kazakhstan and to project future trends in CKD prevalence and mortality by 2030. The retrospective analysis was performed on a database acquired from the Unified National Electronic Health System for 703,122 patients with CKD between 2014 and 2020. During the observation period, 444,404 women and 258,718 men were registered with CKD, 459,900 (66%) were Kazakhs and 47% were older than 50. The incidence rate notably decreased: 6365 people per million population (PMP) in 2014 and 4040 people PMP in 2020. The prevalence changed from 10,346 to 38,287 people PMP, and the mortality rate increased dramatically from 279 PMP to 916 PMP. Kazakhstan's central regions, Turkestan and Kyzylorda were identified as the most burdensome ones. The ARIMA model projected 1,504,694 expected prevalent cases in 2030. The predicted mortality climbed from 17,068 cases in 2020 to 37,305 deaths in 2030. By 2030, the prevalence and mortality of CKD will significantly increase, according to the predicted model. A thorough action plan with effective risk factor management, enhanced screening among risk populations, and prompt treatment are required to lessen the burden of disease in Kazakhstan.

Epidemiology of pediatric hematological malignancies in Kazakhstan: Data from Unified National Electronic Healthcare System 2014-2021.

We aimed to describe incidence and all-cause mortality of hematological pediatric malignancies (leukemia and lymphomas) in Kazakhstan based on nationwide large-scale healthcare data from the Unified National Electronic Healthcare System (UNEHS) for the 2014-2021 year period. The cohort included data of patients less than 18 years old with the diagnosis of hematological malignancies registered in the UNEHS (inpatient and outpatient registries) for the year period 2014-2021. Descriptive statistics were conducted to indicate socio-demographic characteristics of the cohort. Incidence and all-cause mortality were calculated per 100,000 population. Cox proportional hazard regression analysis was performed to investigate the association between determinants with the all-cause mortality. The total cohort consisted of 3357 children with leukemia and 1474 children with lymphomas. The mean age at diagnosis of leukemia and lymphomas was 7.3 ± 4.7 and 9.9 ± 4.9 years, respectively. The incidence rate of hematological malignancies was 6.8 per 100,000 in 2021. Patients with ALL had a higher incidence rate than patients with AML (3.4 and 1.2 per 100,000 in 2021, respectively). The incidence rate of HL and NHL was relatively similar which varied from 0.6 to 2.6 per 100,000 in 2014-2021. All-cause mortality of pediatric hematological malignancies varied from 1.1 to 1.5 per 100,000 in 2014-2021, with the peak in 2016 (1.7 per 100,000). Younger age is significantly associated with increased risk of all-cause mortality in children with AML. CONCUSION: Patients with ALL had a higher incidence rate than patients with AML. The incidence rate of HL and NHL was relatively similar. All-cause mortality rates for leukemia and lymphomas were quite stable during the study period. Younger age is significantly associated with increased all-cause mortality among AML patients. However, there is no significant association of age with all-cause mortality among ALL, HL and NHL. In order to obtain more reliable data and analysis on pediatric (hematological) malignancies, specific registries for childhood tumors (including detailed information on relapses, treatments, short and long-term side effects, and specific death causes) should be implemented. WHAT IS KNOWN: • Leukemias and lymphomas together account for around 45% of all pediatric malignancies. • Lymphoma accounts for 12% of all childhood malignancies; non-Hodgkin's lymphomas (NHL) are more frequent than Hodgkin's lymphomas (HL). WHAT IS NEW: • The incidence rate of ALL was higher than the incidence rate of AML throughout the whole study period, whereas all-cause mortality of ALL and AML was quite stable. • According to Cox PH analysis, younger age (0-5 years old) was associated with a higher risk of death among AML children compared to older children, and no significant association of age was observed with all-cause mortality among ALL and lymphomas.

Epidemiology of tuberculosis in Kazakhstan: data from the Unified National Electronic Healthcare System 2014-2019.

OBJECTIVES: This study aims to estimate tuberculosis (TB) incidence, mortality rates and survival HRs in Kazakhstan, using large-scale administrative health data records during 2014-2019. DESIGN: A retrospective cohort study. SETTINGS: Data for patients with TB in Kazakhstan during 2014-2019, reported in the Unified National Electronic Healthcare System. PARTICIPANTS: Patients with TB in Kazakhstan (ICD-10 (The International Classification of Diseases, 10th revision) codes: A15-A19). OUTCOME MEASURES: Demographic factors, diagnoses and comorbidities were analysed using descriptive, bivariate and multivariable statistical analyses. TB incidence and mortality rates were calculated, and Cox regression and Kaplan-Meier survival analysis were performed to assess risk factors for survival rates. RESULTS: Of the 149 122 patients with TB, 91 437 (61%) were males, and 139 931 (94%) had respiratory TB. From 2014 to 2019, TB incidence declined from 227 to 15.2 per 100 000 individuals, while all-cause mortality increased from 8.4 to 15.2 per 100 000. Age-specific TB incidence was lowest for 0-10 years of age and highest for 20 years of age. Being older, man, urban residence versus rural, retired versus employed, having HIV and having diabetes versus no comorbidities were associated with lower survival rates. CONCLUSION: To date, this is the largest TB published study for Kazakhstan, characterising TB incidence and mortality trends by demographic factors, and risk factors for survival rates. The findings highlight the need for targeted interventions to address the growing burden of TB, particularly among older adults, men, urban residents and those with HIV and diabetes. The study underscores the importance of using administrative health data to inform policy and health system responses to TB in Kazakhstan.

Dynamics of hospital admissions and all-cause mortality of HIV infected patients in Kazakhstan: data from unified nationwide electronic healthcare system 2014-2019.

Background and objectives: Although global HIV pandemic has stabilized, it continues to rise in Eastern Europe and Central Asia due to exponential growth of newly acquired cases. Based on UNAIDS, there are currently 35,000 people living with HIV (PLWH) in Kazakhstan. This alarming HIV epidemiologic situation mandates urgent investigation of causes, routes of transmission and other characteristics in order to halt the epidemic. We aimed to analyze the data of all hospitalized patients for the period of 2014-2019 who tested positive for HIV from the Unified National Electronic Health System (UNEHS) of Kazakhstan. Methods: This cohort study extracted data for all HIV positive patients during 2014-2019 from UNEHS of Kazakhstan to apply descriptive, Kaplan-Meier estimation, and Cox proportional hazards regression model. Crosscheck of the target population data was conducted with tuberculosis, viral hepatitis, alcohol abuse and intravenous drug user (IDU) cohorts in order to create a comprehensive database. All survival functions and factors associated with mortality were tested for significance. Results: The cohort population (n = 2,213) mean age was 33.3 ± 13.3 years with 1,375 males (62.1%) and 838 females (37.9%). Incidence rate decreased from 2.05 in 2014 to 1.88 in 2019, however, prevalence and mortality continues to escalate every year, the mortality raised significantly from 0.39 in 2014 to 0.97 in 2019. People aged >50 years, males, retired people, patients from tuberculosis hospital profile had much lower survival probabilities than the corresponding groups. Adjusted Cox regression model death hazard showed strong association of HIV patients with tuberculosis coinfection (HR 1.4, 95% CI 1.1; 1.7, p < 0.001). Conclusion: The results of this study demonstrate high rates of HIV mortality, strong association of HIV with TB coinfection, regional, age specific, gender, hospital profile and social status differences that significantly affect HIV prevalence. Since the prevalence of HIV is continuing to increase, more information is necessary for evaluation and implementation of prevention procedures.

Prevalence of HIV in Kazakhstan 2010-2020 and Its Forecasting for the Next 10 Years.

Background: HIV is a growing public health burden that threatens thousands of people in Kazakhstan. Countries around the world, including Kazakhstan, are facing significant problems in predicting HIV infection prevalence. It is crucial to understand the epidemiological trends of infectious diseases and to monitor the prevalence of HIV in a long-term perspective. Thus, in this study, we aimed to forecast the prevalence of HIV in Kazakhstan for 10 years from 2020 to 2030 by using mathematical modeling and time series analysis. Methods: We use statistical Autoregressive Integrated Moving Average (ARIMA) models and a nonlinear epidemic Susceptible-Infected (SI) model to forecast the HIV infection prevalence rate in Kazakhstan. We estimated the parameters of the models using open data on the prevalence of HIV infection among women and men (aged 15-49 years) in Kazakhstan provided by the Kazakhstan Bureau of National Statistics. We also predict the effect of pre-exposure prophylaxis (PrEP) control measures on the prevalence rate. Results: The ARIMA (1,2,0) model suggests that the prevalence of HIV infection in Kazakhstan will increase from 0.29 in 2021 to 0.47 by 2030. On the other hand, the SI model suggests that this parameter will increase to 0.60 by 2030 based on the same data. Both models were statistically significant by Akaike Information Criterion corrected (AICc) score and by the goodness of fit. HIV prevention under the PrEP strategy on the SI model showed a significant effect on the reduction of the HIV prevalence rate. Conclusion: This study revealed that ARIMA (1,2,0) predicts a linear increasing trend, while SI forecasts a nonlinear increase with a higher prevalence of HIV. Therefore, it is recommended for healthcare providers and policymakers use this model to calculate the cost required for the regional allocation of healthcare resources. Moreover, this model can be used for planning effective healthcare treatments.

Prevalence, incidence, and mortality rates of breast cancer in Kazakhstan: data from the Unified National Electronic Health System, 2014-2019.

Background: Although there are numerous sources of epidemiologic information on breast cancer in Kazakhstan, none of them have specifically examined the burden of this disease. Therefore, this article aims to provide an overview of the breast cancer prevalence, incidence, mortality, and distribution and changes over time in Kazakhstan based on nationwide large-scale healthcare data from the National Registry in order to encourage more research on the impact of various diseases at the regional and national levels. Methods: The study cohort included all adult women older than 25 years who were diagnosed with breast cancer in any clinical setting of the Republic of Kazakhstan during the period of 2014-2019. The data were extracted from the Unified Nationwide Electronic Health System (UNEHS) to get an overview of descriptive statistics, incidence, prevalence, and mortality rate calculations and the Cox proportional hazards regression model. All survival functions and factors associated with mortality were tested for significance. Results: The cohort population (n = 55,465) comprised subjects with the age at the diagnosis of breast cancer from 25 to 97 years, with a mean of 55.7 ± 12.0 years. The majority of the study population belonged to the age group 45-59 years, which is 44.8% of the cohort. The all-cause mortality rate of the cohort is 16%. The prevalence rate increased from 30.4 per 10,000 population in 2014 to 50.6 in 2019. The incidence rate varied from 4.5 per 10,000 population in 2015 to 7.3 in 2016. Mortality rates were stable and high in the senile age patients (75-89 years old). Breast cancer mortality was positively associated with women who had been diagnosed with diabetes, HR 1.2 (95% CI, 1.1-2.3), whereas it was negatively associated with arterial hypertension, HR 0.4 (95% CI, 0.4-0.5). Conclusion: Overall, Kazakhstan is experiencing an increase in the incidence of breast cancer cases, but the mortality rate has started to decline. The switch to population mammography screening could reduce the breast cancer mortality rate. These findings should be utilized to help Kazakhstan determine what cancer control priorities should be utilized, including the need to implement efficient and affordable screening and prevention programs.

Review of the research databases on population-based Registries of Unified electronic Healthcare system of Kazakhstan (UNEHS): Possibilities and limitations for epidemiological research and Real-World Evidence.

INTRODUCTION: A 'learning healthcare system', based on electronic health records and other routinely collected healthcare data, would allow Real World Data (RWD) to be continuously fed into the system, ensuring that with every new patient treated, we know more overall about the practice of medicine. A judicious use of RWD would complement the traditional evidence from clinical research, for the benefit of all stakeholders involved in healthcare. Lack of data on disease epidemiology in Kazakhstan resonates with lower life expectancy and poorer health indicators compared to countries with analogous income per capita. Usage of primary data collection methods to fill these gaps require additional financial and human resources. Usage of big data, which is routinely collected though healthcare information systems, is considered as a competitive alternative in described circumstances. OBJECTIVE: Development of the Unified National Electronic Healthcare System (UNEHS) in Kazakhstan allowed the creation of research databases to investigate epidemiology of numerous diseases. UNEHS research databases endorse extensive research activities due to a prospective follow-up, coverage of the whole Kazakhstani population and relatively lower expenses to conduct epidemiological studies. This review paper aims to introduce the content and descriptive data on research databases on population-based registries of UNEHS and to discuss opportunities and limitations of its usage. RESULTS AND DISCUSSION: UNEHS databases include medical data on 36.4% of an adult population of Kazakhstan. Research databases presented in this paper contain critical variables that can be utilized for investigation of disease epidemiology, effectiveness of provided medical procedures and infectious disease epidemiology. A few examples accompany a detailed elaboration on the possibilities of research database utilization in epidemiological research. CONCLUSION: Considering numerous advantages, the UNEHS research databases are expected to greatly contribute to healthcare in Kazakhstan by providing critical data on disease epidemiology. To warrant long-term usage and high research output several concerns and limitations should be addressed as well.

Urinary Protein Profiling for Potential Biomarkers of Chronic Kidney Disease: A Pilot Study.

Proteinuria is a risk factor for chronic kidney disease (CKD) progression and associated complications. However, there is insufficient information on individual protein components in urine and the severity of CKD. We aimed to investigate urinary proteomics and its association with proteinuria and kidney function in early-stage CKD and in healthy individuals. A 24 h urine sample of 42 individuals (21-CKD and 21-healthy individuals) was used for mass spectrometry-based proteomics analysis. An exponentially modified protein abundance index (emPAI) was calculated for each protein. Data were analyzed by Mascot software using the SwissProt database and bioinformatics tools. Overall, 298 unique proteins were identified in the cohort; of them, 250 proteins belong to the control group with median (IQR) emPAI 39.1 (19−53) and 142 proteins belong to the CKD group with median (IQR) emPAI 67.8 (49−117). The level of 24 h proteinuria positively correlated with emPAI (r = 0.390, p = 0.011). The emPAI of some urinary proteomics had close positive (ALBU, ZA2G, IGKC) and negative (OSTP, CD59, UROM, KNG1, RNAS1, CD44, AMBP) correlations (r < 0.419, p < 0.001) with 24 h proteinuria levels. Additionally, a few proteins (VTDB, AACT, A1AG2, VTNC, and CD44) significantly correlated with kidney function. In this proteomics study, several urinary proteins correlated with proteinuria and kidney function. Pathway analysis identified subpathways potentially related to early proteinuric CKD, allowing the design of prospective studies that explore their response to therapy and their relationship to long-term outcomes.

Epidemiological characteristics and climatic variability of viral meningitis in Kazakhstan, 2014-2019.

Background: The comprehensive epidemiology and impact of climate on viral meningitis (VM) in Kazakhstan are unknown. We aimed to study the incidence, in-hospital mortality and influence of climatic indicators on VM from 2014 to 2019. Methods: Nationwide electronic healthcare records were used to explore this study. ICD-10 codes of VM, demographics, and hospital outcomes were evaluated using descriptive statistics and survival analysis. Results: During the 2014-2019 period, 10,251 patients with VM were admitted to the hospital. 51.35% of them were children, 57.85% were males, and 85.9% were from the urban population. Enteroviral meningitis was the main cause of VM in children. The incidence rate was 13 and 18 cases per 100,000 population in 2014 and 2019, respectively. Case fatality rate was higher in 2015 (2.3%) and 2017 (2.0%). The regression model showed 1°C increment in the daily average temperature might be associated with a 1.05-fold (95% CI 1.047-1.051) increase in the daily rate of VM cases, 1hPa increment in the average air pressure and 1% increment in the daily average humidity might contribute to a decrease in the daily rate of VM cases with IRRs of 0.997 (95% CI 0.995-0.998) and 0.982 (95% CI 0.981-0.983), respectively. In-hospital mortality was 35% higher in males compared to females. Patients residing in rural locations had a 2-fold higher risk of in-hospital death, compared to city residents. Elderly patients had a 14-fold higher risk of in-hospital mortality, compared to younger patients. Conclusion: This is the first study in Kazakhstan investigating the epidemiology and impact of climate on VM using nationwide healthcare data. There was a tendency to decrease the incidence with outbreaks every 5 years, and mortality rates were higher for Russians and other ethnicities compared to Kazakhs, for males compared to females, for elder patients compared to younger patients, and for patients living in rural areas compared to city residents. The climatic parameters and the days of delay indicated a moderate interaction with the VM cases.

Nicotinic Acetylcholine Receptors of PC12 Cells.

Nicotinic acetylcholine receptors (nAChRs) have gained much attention in the scientific community since they play a significant role in multiple physiological and pathophysiological processes. Multiple approaches to study the receptors exist, with characterization of the receptors' functionality at a single cellular level using cell culturing being one of them. Derived from an adrenal medulla tumor, PC12 cells express nicotinic receptor subunits and form functional nicotinic receptors. Thus, the cells offer a convenient environment to address questions related to the functionality of the receptors. The review summarizes the findings on nicotinic receptors' expression and functions which were conducted using PC12 cells. Specific focus is given to α3-containing receptors as well as α7 receptor. Critical evaluation of findings is provided alongside insights into what can still be learned about nAChRs, using PC12 cells.