Diabetology & Metabolic Syndrome· 2026Q1
Data-driven clinical phenotypes of diabetic kidney disease and their association with disease progression: a real-world cohort study
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- Q1SCImago
- 2026year
Short summary
Outcome-blind clustering identified three distinct diabetic kidney disease (DKD) phenotypes: metabolic–preserved kidney function (P1; n=3,797), older, leaner, lower-eGFR (P2; n=1,947), and albuminuric renal impairment (P3; n=923). P3 patients had an 8.12x higher risk of kidney outcomes and a faster eGFR decline (-9.14 mL/min/1.73 m²/year) compared to P1.
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Key points
- Three distinct DKD phenotypes (P1, P2, P3) were identified using outcome-blind partitioning around medoids on 11 baseline variables in 6,667 patients.
- Phenotype P3 (albuminuric renal impairment) showed the highest risk for composite kidney outcomes (adjusted HR 8.12 vs. P1) and the steepest annual eGFR decline (-9.14 mL/min/1.73 m²/year).
- Phenotype P2 (older, leaner, lower-eGFR) also had increased risk (adjusted HR 1.89 vs. P1) and faster eGFR decline (-4.94 mL/min/1.73 m²/year) compared to P1.
- These phenotypes exhibited prognostic heterogeneity even within established KDIGO categories.
AI-generated from the title and abstract; the full text is not read.
Abstract
Diabetic kidney disease (DKD) has a heterogeneous clinical course. A refined classification of DKD phenotypes could help identify patients at increased risk of kidney disease progression and guide individualized clinical management. This retrospective cohort included 6,667 adults with type 2 diabetes and DKD. Phenotypes were derived by outcome-blind partitioning around medoids using 11 routinely available baseline variables. Reproducibility was evaluated using repeated subsampling and consensus clustering across multiply imputed datasets. Cox models assessed kidney outcomes, and linear mixed-effects models characterized longitudinal estimated glomerular filtration rate (eGFR) trajectories. Phenotypic and prognostic heterogeneity within specific combinations of glomerular filtration rate and albuminuria categories defined by Kidney Disease: Improving Global Outcomes (KDIGO) was also examined. Three phenotypes were identified: metabolic–preserved kidney function (P1; n = 3,797), older, leaner, lower-eGFR (P2; n = 1,947), and albuminuric renal impairment (P3; n = 923). Among 2,651 patients included in the time-to-event analysis, 546 experienced the composite kidney outcome. Compared with P1, the adjusted hazard ratios were 1.89 (95% CI, 1.50–2.37) for P2 and 8.12 (95% CI, 6.54–10.07) for P3. Adjusted annual eGFR slopes were −4.94, −3.80, and −9.14 mL/min/1.73 m 2 per year for P1, P2, and P3, respectively. All 15 KDIGO category combinations contained more than one phenotype. After stratification by KDIGO category combination, the adjusted hazard ratios were 1.35 (95% CI, 1.03–1.79) for P2 and 2.35 (95% CI, 1.70–3.26) for P3. Outcome-blind clustering identified three DKD phenotypes with distinct kidney outcome risks and longitudinal eGFR trajectories. Multidimensional clinical phenotyping may complement KDIGO classification.
The authors' abstract, as published at the source. Diabetology & Metabolic Syndrome, 2026 · DOI ↗
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Field: Nephrology
NephrologyMedicine