Clinical Significance of the C-Reactive Protein-Triglyceride-Glucose Index in Cardiovascular Disease, Stroke, Cardiovascular-Kidney-Metabolic Syndrome, Cancer, Diabetes, and Osteoporosis: A Narrative Review

Objective: This narrative review aimed to summarize and critically appraise current evidence on the clinical significance of CTI in cardiovascular disease, stroke, cardiovascular-kidney-metabolic syndrome, cancer, diabetes, and osteoporosis. Methods: PubMed and Web of Science databases were searched from January 2022, when CTI was first proposed, to January 2026. Search terms combined “C-reactive protein-triglyceride glucose index”, “CTI”, “CRP-TyG”, “insulin resistance”, “inflammation”, and disease-specific terms including cardiovascular disease, coronary heart disease, heart failure, stroke, cardiovascular-kidney-metabolic syndrome, cancer, diabetes, osteoporosis. Eligible studies reported CTI-specific clinical associations, prognostic performance, or relevant mechanistic evidence. Because this was a narrative review, no meta-analysis was performed. Results: Current evidence is dominated by observational studies. Elevated CTI is consistently associated with higher cardiometabolic risk and poorer outcomes in cardiovascular disease, coronary heart disease, heart failure, stroke, cardiovascular-kidney-metabolic syndrome, cancer, and diabetes. Emerging data also suggest a potential relationship between higher CTI and reduced bone mineral density or osteoporosis, particularly among patients with type 2 diabetes mellitus. However, reported associations differ by glycometabolic status, disease stage, sex, age, and study design, and standardized CTI thresholds remain unavailable. Conclusion: CTI is a simple, accessible index that may help characterize the inflammatory-metabolic burden underlying several chronic diseases. Its clinical value is most plausible as a complementary risk-stratification tool rather than a stand-alone diagnostic marker. Future studies should validate disease-specific thresholds, test whether CTI improves established prediction models, and determine whether interventions that reduce CTI translate into better clinical outcomes.