Diabetes as an independent risk factor for severe inflammatory bowel disease: evidence from an inflammation–metabolism–liver coupling framework - Huang, Bin; An, Honglin; Chen, Liming; Qiu, Yiman; Su, Yaping; Shen, Shiju; Wu, Huaping; Li, Mengyuan; Lu, Lisha; Wang, Rong; Hua, Hangju; Chen, Wujin (Frontiers in Endocrinology, 2025)
BackgroundThe clinical course of inflammatory bowel disease (IBD) varies widely, and identifying factors associated with severe disease is essential for risk stratification. Diabetes has been proposed as a potential determinant of adverse outcomes, yet its independent role in disease progression remains unclear.MethodsWe retrospectively analyzed clinical data from patients with mild and severe IBD. Demographic, inflammatory, hepatic, and metabolic parameters were compared between groups. Logistic regression was used to identify independent predictors of severe IBD. Model performance was assessed using receiver operating characteristic curves, calibration analysis, and cross-validation. An inflammation–metabolism–liver coupling index (IMLCI) was constructed to integrate key predictors.ResultsPatients with severe IBD exhibited significantly higher levels of inflammatory markers (WBC, neutrophil percentage, CRP), impaired hepatic function indices (ALT, AST, bilirubin), and adverse metabolic profiles (elevated TG and LDL, reduced HDL and vitamin B12). Diabetes was strongly associated with severe IBD (odds ratio = 3.81, P < 0.001), confirming its independent effect beyond traditional risk factors. The inflammation–metabolism–liver coupling index (IMLCI) demonstrated excellent discrimination (AUC = 0.900 in the training cohort and 0.891 in the testing cohort), good calibration (Hosmer–Lemeshow P = 0.83), and robust internal validation, outperforming single laboratory or metabolic biomarkers.ConclusionDiabetes represents a strong independent risk factor for severe IBD. The proposed IMLCI framework, integrating inflammation, metabolism, and liver function, demonstrates high predictive accuracy and may provide a practical tool for early identification and risk management of patients with severe IBD.