ArticleBMJ open diabetes research & care2024
Clinical utility of novel diabetes subgroups in predicting vascular complications and mortality: up to 25 years of follow-up of the HUNT Study.
Article in BMJ open diabetes research & care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Type 2 diabetes subtypes for precision medicine: methodological challenges and alternative prediction-based approaches.Diabetologia · 2026Review
- Metabolic Risk Predictors Associated With the Onset of Vascular Complications Among Patients With Type 2 Diabetes in Zambia: A Retrospective Statistical Modeling Study.Health science reports · 2026Article
- Assessment of fatal cardiovascular disease risk using data-driven diabetes subgroups and SCORE2-Diabetes: a prospective, observational, population-based analysis of adults with diabetes in Mexico City.Lancet regional health. Americas · 2026Article
- Subtypes of newly diagnosed type 2 diabetes and risk of complications: analysis of electronic health records in the USA.Diabetologia · 2026Article
- Phenotypic clustering of newly diagnosed type 2 diabetes in a Mediterranean cohort.Cardiovascular diabetology · 2026Article
- Cluster-Defined Metabolic Heterogeneity and Longitudinal Effects of Allopurinol and SGLT2 Inhibitors in Hyperuricemic Type 2 Diabetes.Medical sciences (Basel, Switzerland) · 2026Article
- Assessment of fatal cardiovascular disease risk using data-driven diabetes subgroups and SCORE2-Diabetes in 24,943 adults in Mexico City.medRxiv : the preprint server for health sciences · 2025Article
- Metabolic and inflammatory axes of insulin resistance in normoglycemic adults with high HIV burden.PLOS global public health · 2025Article
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10 authors.
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Abstract
introductionCluster analysis has previously revealed five reproducible subgroups of diabetes, differing in risks of diabetic complications. We aimed to examine the clusters' predictive ability for vascular complications as compared with established risk factors in a general adult diabetes population. RESEARCH DESIGN AND
methodsParticipants from the second (HUNT2, 1995-1997) and third (HUNT3, 2006-2008) surveys of the Norwegian population-based Trøndelag Health Study (HUNT Study) with adult-onset diabetes were included (n=1899). To identify diabetes subgroups, we used the same variables (age at diagnosis, body mass index, HbA1c, homeostasis model assessment estimates of beta cell function and insulin resistance, and glutamic acid decarboxylase antibodies) and the same data-driven clustering technique as in previous studies. We used Cox proportional hazards models to investigate associations between clusters and risks of vascular complications and mortality. We estimated the C-index and R
resultsWe reproduced five subgroups with similar key characteristics as identified in previous studies. During median follow-up of 9-13 years (differing between outcomes), the clusters were associated with different risks of vascular complications and all-cause mortality. However, in prediction models, individual established risk factors were at least as good predictors as cluster assignment for all outcomes. For example, for retinopathy, the C-index for the model including clusters (0.65 (95% CI 0.63 to 0.68)) was similar to that of HbA1c (0.65 (95% CI 0.63 to 0.68)) or fasting C-peptide (0.66 (95% CI 0.63 to 0.68)) alone. For chronic kidney disease, the C-index for clusters (0.74 (95% CI 0.72 to 0.76)) was similar to that of triglyceride/high-density lipoprotein ratio (0.74 (95% CI 0.71 to 0.76)) or fasting C-peptide (0.74 (95% CI 0.72 to 0.76)), and baseline estimated glomerular filtration rate yielded a C-index of 0.76 (95% CI 0.74 to 0.78).
conclusionsCluster assignment did not provide better prediction of vascular complications or all-cause mortality compared with established risk factors.
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