ArticleJournal of diabetes2024
Clinical characteristics and complication risks in data-driven clusters among Chinese community diabetes populations.
Article in Journal of diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- The obesity-related chronic disease index (ORCDi), a novel composite metric to quantify ORCD burden: an ecological study across U.S. census tracts.Lancet regional health. Americas · 2026Article
- Association between triglyceride glucose-body roundness index and incidence diabetes mellitus: a cohort study.Metabolism open · 2026Article
- Diabetes mellitus as a multisystem disease: understanding subtypes, complications, and the link with steatotic liver diseases in humans.Hormones (Athens, Greece) · 2026Review
- Heterogeneity of diabetes and disease progression with a tree-like representation: findings from the China Cardiometabolic Disease and Cancer Cohort (4C) study.Diabetologia · 2026Article
- Young-onset type 2 diabetes-Epidemiology, pathophysiology, and management.Journal of diabetes investigation · 2025Review
- Cluster Analysis in Diabetes Research: A Systematic Review Enhanced by a Cross-Sectional Study.Journal of clinical medicine · 2025Review
- Application of the C-reactive protein-triglyceride glucose index in predicting the risk of new-onset diabetes in the general population aged 45 years and older: a national prospective cohort study.BMC endocrine disorders · 2025Article
- Recent updates to understand the heterogeneity of type 2 diabetes mellitus.Journal of diabetes investigation · 2025Article
- New approach to optimize therapy in type 2 diabetes mellitus: the importance of subclassification.Frontiers in endocrinology · 2025Review
- Clinical characteristics and complication risks in data-driven clusters among Chinese community diabetes populations.Journal of diabetes · 2024Article
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15 authors.
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Abstract
backgroundNovel diabetes phenotypes were proposed by the Europeans through cluster analysis, but Chinese community diabetes populations might exhibit different characteristics. This study aims to explore the clinical characteristics of novel diabetes subgroups under data-driven analysis in Chinese community diabetes populations.
methodsWe used K-means cluster analysis in 6369 newly diagnosed diabetic patients from eight centers of the REACTION (Risk Evaluation of cAncers in Chinese diabeTic Individuals) study. The cluster analysis was performed based on age, body mass index, glycosylated hemoglobin, homeostatic modeled insulin resistance index, and homeostatic modeled pancreatic β-cell functionality index. The clinical features were evaluated with the analysis of variance (ANOVA) and chi-square test. Logistic regression analysis was done to compare chronic kidney disease and cardiovascular disease risks between subgroups.
resultsOverall, 2063 (32.39%), 658 (10.33%), 1769 (27.78%), and 1879 (29.50%) populations were assigned to severe obesity-related and insulin-resistant diabetes (SOIRD), severe insulin-deficient diabetes (SIDD), mild age-associated diabetes mellitus (MARD), and mild insulin-deficient diabetes (MIDD) subgroups, respectively. Individuals in the MIDD subgroup had a low risk burden equivalent to prediabetes, but with reduced insulin secretion. Individuals in the SOIRD subgroup were obese, had insulin resistance, and a high prevalence of fatty liver, tumors, family history of diabetes, and tumors. Individuals in the SIDD subgroup had severe insulin deficiency, the poorest glycemic control, and the highest prevalence of dyslipidemia and diabetic nephropathy. Individuals in MARD subgroup were the oldest, had moderate metabolic dysregulation and the highest risk of cardiovascular disease.
conclusionThe data-driven approach to differentiating the status of new-onset diabetes in the Chinese community was feasible. Patients in different clusters presented different characteristics and risks of complications.
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