Heterogeneity of diabetes and disease progression with a tree-like representation: findings from the China Cardiometabolic Disease and Cancer Cohort (4C) study
Rattachement africain : cn, hk. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
AIMS/HYPOTHESIS: Diabetes heterogeneity has been modelled as a continuum in European populations, but its phenotypes and long-term comorbidity risks remain unclear in Chinese individuals. This study aimed to identify distinct phenotypes and evaluate their links to future cardiometabolic risks in a large Chinese cohort. METHODS: The discriminative dimensionality reduction with trees (DDRTree) algorithm was used to develop a tree structure based on nine clinical variables. Cox proportional hazard models or logistic regression models were used to analyse probabilities of diabetes-related outcomes. RESULTS: This study included 19,612 individuals with newly diagnosed diabetes (36.8% male, mean age 59.01 years [SD 8.63]) from the China Cardiometabolic Disease and Cancer Cohort (4C) study. All nine clinical variables used for establishing DDRTree models were gradient distributed across the tree. By overlaying risks of diabetes-related outcomes, we show how these risks differ by participant phenotype. Participants characterised by hyperglycaemia, obesity and dyslipidaemia showed elevated risks of insulin initiation, hypoglycaemia and chronic kidney diseases, while those with hypertension and high creatinine, total cholesterol and alanine aminotransferase levels were associated with a higher risk of CVD. Notably, social determinants and lifestyle factors further contributed to the observed heterogeneity. CONCLUSIONS/INTERPRETATION: These findings characterise the heterogeneity of diabetes phenotypes and complication risks in the Chinese population, suggesting potential implications for personalised diabetes care. Given the observed phenotypic differences, management strategies should consider population-specific characteristics.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Heterogeneity of diabetes and disease progression with a tree-like representation: findings from the China Cardiometabolic Disease and Cancer Cohort (4C) study
- Date Crossref
- 30/08/2025
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
-
Shanghai Jiao Tong University Department of Endocrine and Metabolic Diseases pays non établi dans la noticeUniversité ou école supérieure
-
Ruijin Hospital pays non établi dans la noticeÉtablissement de santé
-
Wenzhou Medical University Department of Endocrine and Metabolic Diseases pays non établi dans la noticeUniversité ou école supérieure
-
First Affiliated Hospital of Wenzhou Medical University pays non établi dans la noticeÉtablissement de santé
-
People's Liberation Army No. 150 Hospital pays non établi dans la noticeÉtablissement de santé
-
Chinese People's Liberation Army Department of Endocrine and Metabolic Diseases pays non établi dans la noticeOrganisme public
-
Union Hospital pays non établi dans la noticeÉtablissement de santé
-
Qilu Hospital of Shandong University Department of Endocrine and Metabolic Diseases pays non établi dans la noticeÉtablissement de santé
-
Huazhong University of Science and Technology pays non établi dans la noticeUniversité ou école supérieure
-
Nanyang Medical College pays non établi dans la noticeÉtablissement de santé
-
XinHua Hospital pays non établi dans la noticeÉtablissement de santé
-
Tongji Hospital pays non établi dans la noticeÉtablissement de santé
Department of Endocrine and Metabolic Diseases — Shanghai Jiao Tong University, Ruijin Hospital et Department of Endocrine and Metabolic Diseases — Wenzhou Medical University, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.