Back
For best output, select "Paper Size" as "A4" and "Margin" as "0" or "None".
To save or print to PDF, please select Print Destination > Save as PDF, enable Background Graphics under "More Settings", then click "Save".
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.
Comorbidity contributes to increased risks for mortality in chronic kidney disease (CKD) patients, but the patterns of comorbidity in CKD and their impacts on accelerating death across different disease categories remained unclear.
To identify comorbidity patterns, we analyzed 16,955 CKD patients at baseline from the UK Biobank. The K-modes algorithm was applied to cluster patients based on the presence or absence of medical conditions, which were defined using the first three digits of ICD-10 codes and recorded from 10 years before to 180 days after CKD diagnosis. The optimal number of clusters was determined by combining the “elbow” method with the maximum average silhouette width. We characterized the derived clusters by identifying overrepresented disease categories, defined as those with a prevalence ratio (prevalence in cluster/prevalence in total population) of 2.5 or higher. To evaluate the association between comorbidity patterns and cause-specific mortality across 13 disease categories, we employed log-logistic accelerated failure time models. In these models, a time ratio (TR) of less than 1 indicates an accelerator factor, meaning it is associated with a shorter time to the event (death). For all associations, a P-value below the Bonferroni-corrected threshold of 0.004 (0.05/13) was considered statistically significant.
Among the 16,955 participants, the median age was 65.00 years (interquartile range was from 61.04 to 67.81), and 52.15% were female. Four cluster were idented, Cluster 1 was characterized as “multi-system” comorbidity pattern, featuring a high prevalence of respiratory, digestive, metabolic and infectious system diseases, cluster 2 as “mild” pattern, cluster 3 as “musculoskeletal” pattern, cluster 4 as “metabolic-neoplasms” pattern (in Figure panel A and B). Notably, as compared to CKD patients with “mild” comorbidity pattern, those with “multi-system” pattern had significantly higher risks across multiple cause-specific mortalities, including circulatory (TR 0.46, 95% CI: 0.43–0.49), digestive (TR 0.45, 95% CI: 0.39–0.51), metabolic (TR 0.40, 95% CI: 0.36–0.44), infectious (TR 0.44, 95% CI: 0.36–0.53), and respiratory diseases (TR 0.44, 95% CI: 0.36–0.53). Patients with “musculoskeletal” or “metabolic-neoplasms” patterns had more pronounced risks of mortality from musculoskeletal (TR 0.45, 95% CI: 0.34–0.58) and neoplastic diseases (TR 0.52, 95% CI: 0.47–0.58), respectively.
Our findings identified 4 distinct comorbidity patterns in CKD patients and demonstrated that these patterns are associated with accelerated mortality in certain disease systems. This study provides valuable evidence to support interventions aimed at preventing progression to death in CKD patients and offers insights to assist policymakers in improving CKD management.
