Clinical characteristics and complication risks in data‐driven clusters among Chinese community diabetes populations

Abstract

Abstract Background Novel 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. Methods We 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. Results Overall, 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. Conclusion The 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.

Keywords

• Chinese community population
• cluster analysis
• diabetes
• diabetic complication
• K‐means