Subphenotypes of adult‐onset diabetes: Data‐driven clustering in the population‐based KORA cohort
Authors' conclusion
T2D subphenotyping based on its sample's own clinical characteristics leads to stable categorization and adequately reflects T2D heterogeneity.
Study context
- Population
- Individuals with T2D from the KORA FF4 study (Southern Germany)
- Participants
- 301 individuals
- Exposure
- Cluster 1 vs Cluster 2 vs Cluster 3
- Cluster 1n = 96
- Cluster 2n = 172
- Cluster 3n = 33
- Outcome
- Replication of original clusters and de novo T2D subphenotypes
Methodological detailsdata-driven cluster analysis, population-based, k-means clustering
- Data-driven cluster analysis
- Population-based
- K-means clustering
Main finding
As reported in the abstract
De novo clustering with k = 3 including hs-CRP showed high stability: all Jaccard indices
>0.75
Observational data: associations, not effects.
Original publication
Subphenotypes of adult‐onset diabetes: Data‐driven clustering in the population‐based KORA cohort. Diabetes Obes Metab. Published 28 October 2024. doi:10.
Composed by AI from the published abstract and checked against it. How Briefs are made →