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

Author:

Li Binqi12ORCID,Yang Zizhong1,Liu Yang23ORCID,Zhou Xin456,Wang Weiqing7,Gao Zhengnan8,Yan Li9,Qin Guijun10,Tang Xulei11,Wan Qin12,Chen Lulu13,Luo Zuojie14ORCID,Ning Guang7ORCID,Gu Weijun2ORCID,Mu Yiming123ORCID

Affiliation:

1. School of Medicine Nankai University Tianjin China

2. Department of Endocrinology the First medical center of PLA General Hospital Beijing China

3. Department of Endocrinology the eighth medical center of PLA General Hospital Beijing China

4. Graduate School Chinese PLA General Hospital Beijing China

5. Department of Medical Oncology the Fifth Medical Center of Chinese PLA General Hospital Beijing China

6. Department of Geriatrics The Second Medical Center of Chinese PLA General Hospital Beijing China

7. Department of Endocrinology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China

8. Department of Endocrinology Dalian Central Hospital Dalian China

9. Department of Endocrinology Zhongshan University Sun Yat‐sen Memorial Hospital Guangzhou China

10. Department of Endocrinology First Affiliated Hospital of Zhengzhou University Zhengzhou China

11. Department of Endocrinology First Hospital of Lanzhou University Lanzhou China

12. Department of Endocrinology Southwest Medical University Affiliated Hospital Luzhou China

13. Department of Endocrinology Wuhan Union Hospital, Huazhong University of Science and Technology Wuhan China

14. Department of Endocrinology First Affiliated Hospital of Guangxi Medical University Nanning China

Abstract

AbstractBackgroundNovel 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.image

Publisher

Wiley

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