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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Cardiovascular-Kidney-Metabolic (CKM) syndrome, characterized by critical pathophysiological interactions among metabolic risk factors, chronic kidney disease, and cardiovascular dysfunction, poses a significant global health challenge with substantial morbidity and mortality. This study aims to identify distinct temporal patterns in the disease burden of the five major CKM components, including ischemic heart disease, stroke, type 2 diabetes mellitus, chronic kidney disease, and atrial fibrillation, at the national level and to elucidate the key national-level drivers that may contribute to shape these patterns.
Disability-adjusted life year (DALY) rates for these diseases in 168 nations were obtained from the Global Burden of Disease Study 2021 for 2001 to 2019. Human Development Index (HDI), life expectancy, and health expenditure were obtained from the World Bank Open Data. Health system and programmatic indicators were retrieved from the World Health Organization Global Health Observatory. Taking into account the relative contribution of each component to the overall CKM burden, we constructed a weighted CKM index and applied log-transformation to represent each nation's total CKM burden as a single time-series variable. The k-shape clustering was used to identify distinct patterns of CKM burden trajectories. An XGBoost multi-class classification model was developed to identify associated factors for cluster membership.
We identified seven distinct clusters based on CKM burden trajectories (Figure 1). Three clusters, starting with a high CKM burden in 2001, exhibited patterns of gradual decline followed by a slow rise (Cluster 1), concave decline (Cluster 2), and convex decline (Cluster 3) by 2019. Two clusters, starting with a medium burden, showed patterns of slight decline followed by a sharp rise (Cluster 4) and decline followed by a rise and subsequent decline (Cluster 5). The remaining two clusters, starting with a relatively low burden, displayed fluctuating (Cluster 6) and consistently rising (Cluster 7) trends. Nations in Cluster 5 had the lowest mean HDI (0.61) and life expectancy (63.35 years), whereas Clusters 3 and 6 exhibited higher mean HDI of 0.74. The health expenditure as a share of GDP was lowest in Cluster 6 (5.37%), and highest in Cluster 2 and 3 which showed declining trends of disease burden (6.93% and 6.64%, respectively). Key factors associated with cluster membership included HDI, environmental risks (household air pollution from solid fuels and lead exposure), and dietary patterns (diets low in vegetables and legumes).
Temporal trends in the CKM disease burden vary significantly across nations, potentially influenced by socioeconomic development, environmental exposures, and dietary factors. These findings provide insights for developing targeted public health strategies tailored to the distinct risk profiles at the national level.
