ArticleFrontiers in endocrinology2025
Evaluating the triglyceride glucose index as a predictive biomarker for osteoporosis in patients with type 2 diabetes.
Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Altered cortical thickness in type 2 diabetes mellitus patients revealed by coordinate-based meta-analysis.BMC endocrine disorders · 2026Pooled it
- Development and validation of a multimodal interpretable machine learning model for the identification of osteoporosis in patients with type 2 diabetes mellitus: a multicenter retrospective study.Frontiers in endocrinology · 2026Article
- Linear Inverse Association Between Triglyceride Glucose-Body Mass Index and Osteoporosis in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Article
- Clinical Manifestations and Risk Factors of Osteoporosis in Patients with Type 2 Diabetes Mellitus.Journal of inflammation research · 2026Article
- Development and validation of an interpretable machine learning model for osteoporosis prediction using routine blood tests: a retrospective cohort study.BMC medical informatics and decision making · 2025Article
- The joint effect of triglyceride-glucose index and C-reactive protein levels on the risk of chronic obstructive pulmonary disease: a prospective cohort study.Lipids in health and disease · 2025Article
- Development and validation of an explainable machine learning model for predicting osteoporosis in patients with type 2 diabetes mellitus.Frontiers in endocrinology · 2025Article
- Association of triglyceride glucose body mass index with osteoporosis risks in a large Chinese adult cohort.Frontiers in endocrinology · 2025Article
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8 authors.
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Abstract
Objective: Osteoporosis is a common condition among individuals with type 2 diabetes; however, the relationship between insulin resistance, as measured by the Triglyceride Glucose Index (TyG), and osteoporosis has not been sufficiently explored. This study seeks to address this research gap by investigating the diagnostic value of TyG in identifying osteoporosis in patients with type 2 diabetes. Methods: A retrospective analysis was performed on clinical data from 207 diabetic subjects (83 in the osteoporosis group, 124 in the non-osteoporosis group), using SPSS version 27.0 and MedCalc 23 for statistical analysis. Results: Significant statistical differences were noted between the two groups in terms of gender, age, hemoglobin levels, red blood cell count, total cholesterol levels, and the TyG. Binary logistic regression analysis revealed that gender, age, and TyG are independent predictors of osteoporosis in patients with type 2 diabetes. Receiver operating characteristic (ROC) analysis showed that the area under the curve for TyG, gender, age, and their combination in predicting osteoporosis among patients with T2DM was 0.653, 0.698, 0.760, and 0.857, respectively. Additionally, the diagnostic performance of the TyG value was effectively evaluated, determining 8.78 as the optimal cutoff value, with a corresponding sensitivity of 89.1% and specificity of 52.4%. Meanwhile, the predictive model constructed using gender, age, and the TyG index achieved an area under the curve (AUC) of 0.857 (95% confidence interval: 0.801~0.901), with a maximum Youden index of 0.629. The corresponding diagnostic sensitivity was 83.1% and the specificity was 79.8%. Conclusion: The TyG holds potential to serve as a prominent biomarker for the diagnosis of osteoporosis among type 2 diabetic patients in various clinical settings.
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