Phenotypic clustering of newly diagnosed type 2 diabetes in a Mediterranean cohort
Authors' conclusion
The Ahlqvist clustering architecture could be approximated in this Mediterranean cohort at diagnosis, but internal stability of the five-cluster solution was limited. In this population, a four-cluster structure showed substantially better internal validity. These findings support the feasibility of phenotypic subclassification of T2D while underscoring the importance of evaluating population-specific cluster structures and their clinical relevance in longitudinal studies.
Study context
- Population
- Adults with newly diagnosed T2D, Catalonia (Northeast Spain), recruited March 2022–January 2026
- Participants
- 67 / 326 / 241 / 206 / 151 / 347 / 186 / 391
- Exposure
- Ahlqvist clustering vs data-driven clustering
- Severe autoimmune diabetes (SAID)n = 67
- Mild age-related diabetes (MARD)n = 326
- Severe insulin-resistant diabetes (SIRD)n = 241
- MODn = 206
- Severe insulin-deficient diabetes (SIDD)n = 151
- C1n = 347
- C2n = 186
- C3n = 391
- Outcome
- Cluster structure and stability
- Follow-up
- Diagnosis (baseline)
Methodological detailssex-stratified k-means clustering (k = 4), principal component analysis and silhouette analyses
- Sex-stratified k-means clustering (k = 4)
- Principal component analysis and silhouette analyses
Main finding
As reported in the abstract
SAID
6.8%
67
- Ahlqvist clusters: separation modest, bootstrap stability limited (Jaccard)
- 0.555-0.718
- Unconstrained analysis: three clusters most internally optimal; stability substantially higher (Jaccard)
- 0.799-0.863
- Concordance between Ahlqvist and data-driven models moderate (ARI)
- 0.473
Observational data: associations, not effects.
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Original publication
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