Study on the construction of a risk assessment model for type 2 diabetes complications based on GlycA and HDL1-TC

作者：Jinxin Kou, Jingjing Tie, Minjie Li, Qing Tang, Hui Sun, Zhen Wei, Yang Zhao, Ying Liu, Xianfei Zeng · 发表于：Frontiers in Endocrinology · 年份：2026 · DOI：10.3389/fendo.2026.1814397 · 研究领域：Diabetes, Cardiovascular Risks, and Lipoproteins、Metabolomics and Mass Spectrometry Studies、Hyperglycemia and glycemic control in critically ill and hospitalized patients

Background: This study evaluated NMR-derived GlycA and lipoprotein subfractions for stratifying type 2 diabetes (T2DM) complication risk. Methods: A retrospective cross-sectional study included 228 adults with T2DM from two hospitals between January and December 2023. Clinical variables, the NMR-derived inflammatory markers GlycA and GlycB, and lipoprotein subfractions were analyzed. A stepwise logistic model was assessed by ROC analysis, Hosmer-Lemeshow test, bootstrap calibration, and decision-curve analysis. Results: Age, diabetes duration, fasting plasma glucose, GlycA, and HDL1-TC were retained. The model showed good fit (χ² = 7.141, P = 0.521), discrimination (AUC = 0.82, 95% CI: 0.756-0.873), calibration (MAE = 0.021), and higher net benefit than HbA1c/hs-CRP. Conclusions: A model integrating GlycA, HDL1-TC, and clinical factors showed good performance for T2DM complication risk stratification, but causal inference and temporal prediction cannot be established because of the cross-sectional design.