Cardiometabolic & kidneyCohort study
Data-driven cluster analysis identifies distinct types of cardiovascular-kidney-metabolic syndrome
- Cohort study with data-driven cluster analysis
- K-means clustering
- UK Biobank
- training and validation cohorts
Authors' conclusion
Our findings provide insights into the patients with CKM syndrome, aiding in the identification of high-risk patients who may benefit from targeted interventions.
Study context
- Population
- UK Biobank participants with cardiovascular-kidney-metabolic (CKM) syndrome stages 1–3 without organ-specific complications34,487 training
- Participants
- 44,200 participants
- Exposure
- Low-risk (LR) vs liver high-risk (LHR) vs cerebrovascular high-risk (CBHR) vs age-driven high-risk (ADHR) vs cardiorenal high-risk (CRHR)
Main finding
As reported in the abstract
Complication risk by cluster · median follow-up 15.88 years
Five clusters identified
Five
Observational data: associations, not effects.
Further findings
Plasma proteomic and genetic risk patterns
- Each cluster showed unique plasma proteomic characteristics and genetic risk patterns
Original publication
Data-driven cluster analysis identifies distinct types of cardiovascular-kidney-metabolic syndrome. Eur J Prev Cardiol. Published 6 November 2025. doi:10.1093/eurjpc/zwaf708
Summarised from the published abstract; every number is checked against it