The pressure-volume (PV) loop illustrates the changing interaction between left ventricular (LV) pressure and volume throughout a cardiac cycle, and can be reconstructed noninvasively using either cardiac magnetic resonance (CMR) or transthoracic echocardiography (TTE). While reference values have been described, a direct comparison of PV loop parameters derived from CMR and TTE data within the same group of individuals has not been reported yet. In this study, we aimed to evaluate PV loop indices obtained by both techniques in a cohort of healthy volunteers. Twenty participants underwent cine-CMR and 2D-TTE examinations during the same seven-day period at the Heart Center UMC in Astana, Kazakhstan. Image datasets were post-processed with a dedicated software to derive conventional volumetric indices together with PV loop parameters: ventricular elastance (Ees), arterial elastance (Ea), ventriculo-arterial coupling (VAC), stroke work (SW), PV area (PVA), and work efficiency (WE). Statistical comparisons were performed with a significance threshold defined as p < 0.05; Bland-Altman plots assessed agreement. Ees, Ea, and VAC were significantly higher, while SW, PVA, and WE were significantly lower when derived from TTE compared to CMR. These findings were confirmed at the Bland-Altman analysis. Our findings suggest that values of PV loop parameters are different according to the imaging method, which may affect their translational potential. CMR and TTE are not interchangeable for PV loop evaluation, especially in the context of follow-up examinations.

Background/Objectives: Type 2 diabetes mellitus (T2DM) significantly elevates the risk of coronary artery disease (CAD), particularly in Asian populations where both conditions are epidemic. While shared genetic factors contribute to this comorbidity, evidence from Asian cohorts remains fragmented, with limited focus on population-specific variants. This meta-analysis synthesizes evidence on genetic variants associated with CAD risk in Asian patients with T2DM. Methods: We systematically searched several databases according to the PRISMA statement and checklist. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated using random-effects models, with heterogeneity assessed via I2 and Cochran’s Q, and publication bias via funnel plots and Egger’s test. Results: In total, data on 11,268 subjects were reviewed, including 4668 cases and 6600 controls. Among 950 identified studies, 18 met eligibility criteria, and 14 studies provided sufficient data for the meta-analysis. The random-effects pooled estimate across all studied variants was not statistically significant (OR = 1.16 [95% CI: 0.68–2.00]; z = 0.56, p = 0.58). However, analysis of individual loci revealed gene-specific associations with CAD among this population: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%). ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with an elevated risk of CAD: PCSK1 gene (OR = 2.12 [95% CI: 1.26–3.52]; p < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27–3.97]; p < 0.01; weight = 8.62%) and ADIPOQ gene (OR = 8.00 [95% CI: 2.34–27.14]; p < 0.01; weight = 6.35%). Several genes were associated with possible protective effects: ACE gene (OR = 0.41 [95% CI: 0.23–0.73]; p < 0.01; weight = 8.57%), Q192R gene (OR = 0.20 [95% CI: 0.08–0.52]; p < 0.001; weight = 7.41%). Heterogeneity was substantial (τ2 = 0.78; I2 = 81.95%; Q (13) = 64.67, p < 0.001). Conclusions: This first meta-analysis of genetic variants associated with CAD in Asian populations with T2DM identified specific locus-level associations implicating lipid metabolism, incretin signaling, and oxidative stress pathways. The lack of a significant pooled effect, alongside high heterogeneity, underscores the complexity and population-specific nature of this genetic architecture. These findings suggest that effective precision risk stratification may depend more on specific variants than on a broad polygenic signal, highlighting the need for further research in a larger, distinct sample size.

Recently, intraventricular pressure gradients, or hemodynamic forces (HDF), which are their global measure integrated over the left ventricular volume, have been proposed as a new concept capable of detecting subtle changes in left ventricular function. Thanks to a mathematical model, the analysis of routinely acquired cine cardiac magnetic resonance (CMR) images is now feasible without the need for contrast administration or 4D flow imaging, making it an attractive tool for the early detection and follow-up of left ventricular dysfunction. HDF derived from cine CMR images have been applied in normal subjects and in several pathological conditions, and the results of these studies confirm the feasibility and support the usefulness of this method in clinical practice. This review focuses on the technical aspects of cine CMR-derived HDF, emphasizing the need for precise image acquisition. Furthermore, we review the clinical relevance of HDF in various clinical conditions, illustrating their potential in the detection of cardiac diseases at an early stage, evaluation of medical/interventional treatment, and prediction of future cardiac events. Additionally, we report the results of HDF in athletes, where the HDF analysis is able to discriminate physiological adaptations from pathological cardiac remodeling and to document the effect of intense physical training. Future developments should include consistency of HDF parameters, and at this aim we have suggested a standardized approach for HDF analysis for clear interpretation and clinical use.

BACKGROUND:The pressure-volume (PV) relationship remains a key tool for assessing cardiac function. PV loop derived parameters, including end-systolic elastance (Ees), effective arterial elastance (Ea), ventriculo-arterial coupling (VAC), stroke work (SW), pressure-volume area (PVA), and work efficiency (WE), are valuable tools, but reproducibility data are scarce. OBJECTIVE:To evaluate the inter- and intra-observer variability of PV loop parameters derived from transthoracic echocardiography images in patients undergoing hemodialysis. METHODS:Twenty-five adult patients with end-stage renal disease undergoing maintenance hemodialysis were randomly selected. PV loops were reconstructed using Q-Strain software (version 1.3.0.79, Medis, Leiden, the Netherlands), and parameters including Ees, Ea, VAC, SW, PVA, and WE were calculated. Two experienced readers performed measurements for inter-observer analysis; one reader repeated measurements one week apart for intra-observer analysis. Reliability was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plots. RESULTS:Inter-observer agreement was excellent for SW 0.96 (0.91-0.98) and PVA 0.95 (0.87-0.98), good for Ees 0.90 (0.77-0.96) and Ea 0.79 (0.49-0.91), and moderate for VAC 0.68 (0.23-0.85) and WE 0.72 (0.28-0.79). Intra-observer agreement was excellent for Ees 0.96 (0.90-0.98), Ea 0.98 (0.94-0.99), SW 0.98 (0.96-0.99) and PVA 0.98 (0.96-0.99), and good for VAC 0.78 (0.51-0.91) and WE 0.85 (0.65-0.94). Bland-Altman analysis showed minimal bias for Ees, SW and PVA, whereas Ea, VAC and WE exhibited proportional bias. CONCLUSIONS:PV loop-derived parameters obtained via transthoracic echocardiography demonstrate good-to-excellent reproducibility, particularly for Ees, Ea, SW and PVA. VAC and WE show moderate variability, suggesting careful interpretation of these parameters in clinical and research settings.

Cardiovascular diseases (CVDs) are the leading cause of death worldwide. While the impact of COVID-19 on trends is recognized, it is uncertain whether these patterns continued into the third pandemic year. This study sought to investigate the mortality patterns of CVDs during 2014–2022. We utilized data from Kazakhstan’s Unified National Electronic Health System and performed a descriptive data analysis. The authors employed Bayesian Structured Time Series and Joinpoint regression analyses to evaluate CVD-related mortality patterns over time. The study cohort included 240,036 patients with CVD-related deaths from 2014 to 2022. The leading causes of death were cerebrovascular disease (37.89

Analysis of intraventricular pressure gradients has gained interest due to the recent development of a new method of image analysis based on cardiac magnetic resonance feature tracking or echocardiographic speckle tracking. Currently, images acquired from routinely performed cardiac magnetic resonance or echocardiography can be analyzed, and the left ventricular hemodynamic forces (HDF) curves generated and displayed for measurements. This modality has been applied in clinical scenarios and normal reference values are available. However, different parameters have been derived in the available studies on HDF, and there is no standardization on which parameters should be reported. In this short review, we describe how to assess HDF and discuss the different parameters that can be derived from the HDF curves.

Many studies report that cardiac function is affected by hemodialysis due to alterations in left ventricular morphology and function, particularly left ventricular hypertrophy. Left ventricular hypertrophy is primarily driven by pressure and volume overload, aggravated by factors such as arteriovenous fistulas, anemia, and fluid retention. In addition to left ventricular mass, hemodialysis can impair both left ventricular systolic and diastolic functions, leading to transient reductions in left ventricular ejection fraction, and global longitudinal strain, which are strongly linked to increased mortality. Moreover, chronic dialysis leads to changes in arterial structure and function, including increased intima-media thickness and reduced arterial distensibility, which result in increased afterload. Fluctuating blood pressure during dialysis further affects cardiac function, emphasizing the need for comprehensive assessment of both ventricular and arterial functions, a relationship defined as ventriculo-arterial coupling. In patients with kidney failure, ventriculo-arterial coupling serves as a valuable load-independent prognostic marker, enhancing risk prediction and stratification. Non-invasive tools like echocardiography and speckle-tracking techniques are currently available for evaluating these parameters, enabling early detection and intervention to mitigate cardiovascular risks in patients with kidney failure undergoing hemodialysis. These insights highlight the complex interplay between fluid management, left ventricular function, and arterial stiffness, emphasizing the importance of improved strategies to optimize cardiovascular outcomes in this high-risk population.

Background The acute effect of hemodialysis (HD) on left ventricular mechanics has been evaluated in several studies; however, their results are not consistent. Eventually, the heart and the arterial system behave as an interconnected system and not as isolated structures; thus, the evaluation of the interaction of cardiac contractility with the arterial system would provide a more comprehensive understanding of cardiovascular function and cardiac energetics. However, there have not been any studies demonstrating changes in terms of volumes, contractility, intraventricular pressure gradient distribution, and vascular properties in response to changes in loading conditions and their impact on the outcome in patients undergoing HD. Recently, a noninvasive method for assessing left ventricular pressure-volume loop and ventriculo-arterial coupling (VAC) from feature-tracking cardiac magnetic resonance or echocardiography has been proposed. We believe that this method allows a comprehensive evaluation of the hemodynamic status of the patients undergoing HD, including the relationships between cardiac function and arterial elastance, and might provide prognostic information. Objective The primary objective of this study is to evaluate changes in VAC before and after a HD session. The secondary objective is to assess the prognostic value of VAC parameters in predicting adverse outcomes. Methods A 2D transthoracic echocardiogram will be performed before and after a HD session in patients with end-stage renal disease. We target to enroll 323 patients. Images will be analyzed with advanced software based on speckle-tracking, able to reconstruct the pressure-volume loop. From the pressure-volume loop, arterial (Ea) and ventricular (Ees) elastance will be derived. VAC will be calculated as the Ea/Ees ratio. Patients will be followed up for 18 months. Primary endpoints will be a composite of all causes of death, nonfatal myocardial infarction, and hospitalization due to worsening heart failure. Results The study received funding in August 2024, with patients’ enrollment scheduled to take place from January 1 to June 30, 2025. Data analysis will start in April 2025 and is expected to continue until June 2026. The findings of the study are tentatively planned for publication in the winter of 2027. Conclusions This study will provide data on the changes in VAC induced by HD and their potential prognostic value. This assessment could be useful for tailoring volume depletion during HD and to improve patients’ outcomes. Trial Registration ClinicalTrials.gov NCT06622928; https://clinicaltrials.gov/study/NCT06622928 International Registered Report Identifier (IRRID) PRR1-10.2196/71948

Hemodynamic forces (HDF), which reflect the forces exchanged between blood and cardiac tissues, can be derived from cardiac magnetic resonance (CMR) or transthoracic echocardiography (TTE). Although normal values are reported for each imaging technique, no study has compared HDF values within the same cohort so far. We aimed to compare left ventricular (LV) HDF parameters obtained from CMR and TTE in healthy subjects. Twenty volunteers underwent both cine-CMR and 2D-TTE (within 7 days) at the Heart Center University Medical Center in Astana, Kazakhstan. Images were analyzed offline using dedicated software to extract standard volumetric, functional, strain, and HDF parameters: longitudinal (A-B) and transverse (L-S) HDF, L-S/A-B HDF ratio, and HDF vector angle. Statistical comparisons were performed with significance set at p < 0.05; Bland-Altman plots assessed agreement. TTE significantly underestimated LV volumes, ejection fraction, and global longitudinal strain compared to CMR. Similarly, HDF values were lower with TTE for both longitudinal and transverse forces (A-B HDF: 12.4 ± 3.4 vs. 26.1 ± 6.6; L-S HDF: 2.6 ± 1.2 vs. 5.2 ± 1.4; both p < 0.001). Bland-Altman analysis confirmed systematic underestimation of HDF by TTE. These findings suggest that TTE and CMR cannot be used interchangeably for HDF assessment, particularly in serial studies.

PURPOSE:We sought to evaluate the effect of intensive physical training on left ventricular (LV) hemodynamic forces (HDF) in athletes. METHODS:Forty professional endurance athletes were evaluated at the beginning of their training cycle (off-season) and after a period of aerobic isotonic dynamic exercise (peak training period) using cine cardiac magnetic resonance (CMR). Images were analyzed off-line using dedicated software. LV HDF for the whole cardiac cycle and the different cardiac phases were measured. Standard statistics were used to compare off-season and peak training period values. RESULTS:The average sport experience was 11 ± 7 yr. There were no differences in LV volumes, stroke volume, LV ejection fraction, and LV mass between off-season and peak training CMR. Similarly, there were no changes induced by physical training in the strain parameters. Physical training induced a significant increase of the longitudinal HDF (18.7 vs 21.2, P = 0.023) and an increase of the transverse HDF (3.4 vs 4.0, P = 0.048) throughout the entire heartbeat. After physical training, the peak values and the hemodynamic work (expressed as area under the curve) of the first part of the systole were significantly higher compared with off-season values (63.9 vs 53.9 ( P = 0.034); 4.67 vs 3.79 ( P = 0.015), respectively). The difference in the elastic rebound between off-season and peak training (-0.22 vs -0.37) did not reach statistical significance ( P = 0.056). CONCLUSIONS:Intense physical training induces an increase in LV HDF throughout the entire heartbeat, independent from geometric cardiac remodeling. The first part of the systole is the phase of the cardiac cycle that is mostly improved by intense physical training.

Heart failure (HF) is a complex clinical syndrome with significant mortality risks, causing an increasing healthcare burden. Globally, 64.3 million prevalent cases were estimated in 2017. This research examines HF epidemiology in the adult population in Kazakhstan, the largest country in Central Asia. The retrospective analysis was performed on data from the Unified National Electronic Health System, involving 526 766 individuals registered with HF between 2014 and 2019. In the cohort, women accounted for 54% and men for 46%, and the majority (87%) were aged 50 or above. The most prevalent comorbid conditions were hypertension (46%), cerebrovascular diseases (32%), and atherosclerotic heart disease (23%). While the incidence rate declined over the observation period, the all-cause mortality rate almost tripled from 356 to 975 people per million population during the observation period. Of the cohort, 14% of the patients (71 591) were recorded as deceased. In 2019, HF in Kazakhstan resulted in the loss of 2364789.8 disability-adjusted life years. Premature death accounted for a major portion, with 1337578.9 years of life lost. Males have a higher risk of death compared to females [hazard ratio (HR) = 1.24, 95% confidence interval (CI): 1.23-1.26]. History of acute myocardial infarction increases the risk of death by 69% (HR = 1.69, 95% CI: 1.67-1.73) and diabetes by 14% (HR = 1.14, 95% CI: 1.12-1.16) after adjustment for other variables. This research evaluated the burden and disability-adjusted life years of HF in Kazakhstan. The results show that more effective disease management systems and preventive measures for the elderly are needed.

A comorbid hypertension was previously associated with survival advantages in patients with stroke. We aimed to explore how strong priors for the hypertension covariate affect the reverse association, as a way to test the sensitivity of reverse epidemiology findings to bias assumptions. The authors used stroke data from 2014 to 2019 (N = 177,947) and subsequently performed random sampling from a population of various sizes. The data were analyzed using Bayesian multiple logistic mixed-effects regression, which was further modelled in three scenarios: with informative (strong) priors, non-informative priors, and accounting for the interaction mechanism (age*hypertension). In addition, we perform a series of sensitivity analyses to check the robustness of the estimates to different prior choices. Both informative and non-informative priors demonstrated elevated posterior odds ratios (ORs) for hypertension in low sample fractions (n = 100-500). As the sample size increased, the ORs declined (below 1) for each subsequently larger samples. The ORs plateaued as the sample exceeded 5000 and became similar for both the modeling scenarios. Conversely, the interaction term revealed inverse patterns, increasing in effect as the sample size grew large. Thus, the reverse effect of hypertension diminishes with age. Although further modifications of prior precision revealed somewhat higher ORs for hypertension covariate, the estimates mostly overlapped. Bayesian analysis may improve the interpretation of reverse associations when data are limited; however, in large datasets, their influence diminishes. This pattern suggests that reverse associations reflect collider or selection bias rather than prior choice and that Bayesian priors alone cannot address design bias.

Peripheral artery disease (PAD) is a global health concern associated with arterial narrowing or blockage, leading to significant morbidity and mortality. The aim of this study is to assess the disease burden and trends in mortality utilizing nationwide administrative health data. This retrospective study utilized data from the Unified National Electronic Healthcare System (UNEHS) from 2014 to 2021. Patients meeting PAD criteria were included, with demographic and clinical data analyzed. Cox regression and Competing Risk Analysis assessed mortality risks. Between 2014 and 2021, 19,507 individuals were hospitalized due to PAD, with 8,332 (43

The concept of ventricular-arterial coupling (VAC) was first introduced in the early 1980s to quantify the relationship between left ventricular contractility and arterial load. The mathematical formulation of VAC, expressed as the ratio of arterial elastance to ventricular elastance, has since then been refined with adjustments to allow for non-invasive assessment. By the early 2000s, advancements in echocardiography, cardiac magnetic resonance and arterial tonometry provided non-invasive alternatives to the traditional invasive method of cardiac catheterization, broadening the clinical application of VAC. Emerging technologies, such as machine learning and computational models, have further enhanced the precision and personalization of VAC, with potential applications in heart failure, hypertension and other clinical scenarios. This review describes the physiological basis and the historical development of VAC, highlights the non-invasive assessment techniques, and discusses the potential for personalized treatment based on VAC insights. Machine learning models trained on large datasets from non-invasive imaging modalities may open new avenues in predicting individual patient responses to therapies. However, lack of standardized protocols across imaging modalities represents a challenge, making the call for standardization critical for consistent clinical application. This review underscores the need for harmonized methodologies to better utilize VAC in personalized medicine, aiming to improve cardiovascular outcomes through tailored therapies.

We sought to assess cardiac magnetic resonance derived left ventricular hemodynamic forces (HDF) in athletes compared to patients with hypertension. Sixty athletes and 48 hypertensive patients were studied. HDF were measured during the entire cardiac cycle, the systolic phase, suction, early LV filling, and atrial thrust. Statistical comparisons were made between athletes and hypertensive patients, and between endurance and strength athletes. The slope of the systolic ejection was higher in athletes compared to hypertensive patients (541.5 vs. 435 1/sec; p = 0.033). Athletes showed higher HDF during the first phase of systole (4.53 vs. 3.86; p = 0.047) and the systolic impulse (11.26 vs. 8.76; p = 0.045). Compared to hypertensive patients, the AUC of the elastic rebound in athletes was lower (-0.31 vs. -0.44; p = 0.011). Moreover, hypertensive patients had an abnormal suction as revealed by a divergent direction (apex-to-base) of the HDF. The atrial thrust was higher in hypertensive patients than in athletes (-0.31 vs. -0.05; p < 0.001). Compared to endurance athletes, strength athletes had a shorter duration of the systolic impulse (250 vs. 280 ms; p = 0.019) and higher AUC during the early LV filling (1.65 vs. 0.97; p = 0.016). We conclude that HDF allows distinction between the hemodynamic patterns of athletes and patients with hypertension.

By assessing left ventricular hemodynamic forces (HDF) during different phases of the cardiac cycle, we aimed to provide insights into the cardiac adaptations in athletes as compared to patients with hypertension. Sixty athletes and 48 hypertensive patients were studied using cardiac magnetic resonance. HDF were measured during the entire cardiac cycle, the systolic phase (including systolic impulse and elastic rebound), suction, early LV filling, and atrial thrust. Statistical comparisons of HDF parameters were made between athletes and hypertensive patients, and between endurance and strength athletes. The slope of the systolic ejection was significantly higher in athletes compared to hypertensive patients (541.5 vs 435 1/sec; p = 0.033). Athletes showed higher HDF during the first phase of systole (4.53 vs 3.86; p = 0.047) and the systolic impulse (11.2 vs 8.7; p = 0.045), and a higher peak value (62.9 vs 46.8; p = 0.001). Compared to hypertensive patients, the elastic rebound in athletes was shorter (51.6 vs 70.1 ms; p < 0.001) and the hemodynamic work during this phase was lower (-0.31 vs -0.44; p = 0.011). Moreover, hypertensive patients had an abnormal suction phase as revealed by a divergent direction (apex-to-base) of the HDF (0.09). The atrial thrust component was significantly higher in hypertensive patients than in athletes (-0.31 vs -0.05; p < 0.001). Compared to endurance athletes, strength athletes had a shorter duration of the systolic impulse (250 vs 280 ms; p = 0.019) and higher hemodynamic work during the early left ventricular filling (1.65 vs 0.97; p = 0.016). The assessment of HDF allows distinction between the hemodynamic patterns of athletes and patients with hypertension. Athletes were able to generate higher pressure gradients in a shorter period of time, and had a shorter and softer elastic rebound. In hypertensive patients, the suction mechanism is lost. Higher atrial thrust indicates the importance of the active LV filling during diastole in hypertensive patients. This study was funded by a grant of the Ministry of Education and Science of the Republic of Kazakhstan, № AP14869730.

Athletes require careful evaluation by specialized physicians to obtain eligibility for sport. In this context, electrocardiogram can be helpful to recognize patterns associated with heart disease that put the athletes at high risk of sudden cardiac death and may interdict participation in sports. On the other hand, adaptation to exercise may induce structural remodeling of the cardiac structures that results into electrocardiographic changes that are not associated with an increased risk of adverse events during exercise. Clearly, a correct interpretation of a resting 12-lead electrocardiogram is essential to differentiate athletes at risk of sudden cardiac death who must be prohibited from agonistic sports from those with physiologic changes who should be reassured and declared eligible for sport activities. Interpretation of the athlete’s ECG has evolved over the past 15 years, and in this chapter, we provide a brief review of current evidence regarding the electrocardiographic findings considered normal and abnormal in athletes based on the latest international recommendations.

BackgroundHemodynamic forces (HDF) analysis has been proposed as a method to quantify intraventricular pressure gradients, however data on its reliability are still scanty. Thus, the aim of this study is to assess the reliability of HDF parameters derived from cardiac magnetic resonance (CMR).MethodsCMR studies of 25 athletes were analysed by two independent observers and then re-analysed by the same observer one week apart. Intraclass Correlation Coefficient (ICC [95% CI]) and Bland-Altman plots were used to assess association, agreement, and bias of the longitudinal (A-B) HDF, transverse (L-S) HDF, and Impulse Angle. The sample size required to detect a relative change in the HDF parameters was also calculated.ResultsIn terms of inter-observer variability, there was a good correlation for the A-B and L-S (ICC 0.85 [0.67-0.93] and 0.86 [0.69-0.94]; p<0.001 for both, respectively) and a moderate correlation for the Impulse Angle (ICC 0.73 [0.39-0.87]; p = 0.001). For intra-observer variability, A-B and L-S showed excellent correlation (ICC 0.91 [0.78-0.93] and 0.93 [0.83-0.97]; p<0.001 for both, respectively). Impulse Angle presented good correlation (ICC 0.80 [0.56-0.90]; p<0.001). Frame selection and aortic valve area measurements were the most vulnerable step in terms of reliability of the method. Sample size calculation to detect relative changes ranged from n = 1 to detect a 15% relative change in Impulse Angle to n = 171 for the detection of 10% relative change in A-B HDF.ConclusionsThe results of this study showed a low inter- and intra-observer variability of HDF parameters derived from feature-tracking CMR. This provides the fundamental basis for their use both in research and clinical practice, which could eventually lead to the detection of significant changes at follow-up studies.

BackgroundCardiovascular diseases contribute to premature mortality globally, resulting in substantial social and economic burdens. The Global Burden of Disease (GBD) Study reported that in 2019 alone, heart attack and strokes accounted for the deaths of 18.6 million individuals. Ischemic heart diseases, including acute myocardial infarction (AMI), accounted for 182 million disability-adjusted life years (DALYs) and it is leading cause of death worldwide.AimThe aim of this study is to present the burden of AMI in Kazakhstan and describe the outcome of hospitalized patients.MethodsThe data of 79,172 people admitted to hospital with ICD-10 diagnosis I21 between 2014 and 2019 was derived from the Unified National Electronic Health System and retrospectively analyzed.ResultsThe majority of the cohort (53,285, 67%) were men, with an average age of 63 (±12) years, predominantly of Kazakh (38,057, 48%) and Russian (24,583, 31%) ethnicities. Hypertension was the most common comorbidity (61,972, 78%). In males, a sharp increase in incidence is present after 40 years, while for females, the morbidity increases gradually after 55. Throughout the observation period, all-cause mortality rose from 101 to 210 people per million population (PMP). In 2019, AMI account for 169,862 DALYs in Kazakhstan, with a significant proportion (79%) attributed to years of life lost due to premature death (YLDs). Approximately half of disease burden due to AMI (80,794 DALYs) was in age group 55–69 years. Although incidence is higher for men, they have better survival rates than women. In terms of revascularization procedures, coronary artery bypass grafting yielded higher survival rates compared to percutaneous coronary intervention (86.3% and 80.9% respectively) during the 5-year follow-up.ConclusionThis research evaluated the burden and disability-adjusted life years of AMI in Kazakhstan, the largest Central Asian country. The results show that more effective disease management systems and preventive measures at earlier ages are needed.