A Novel Composite Index for Cardiovascular Risk: The Cholesterol, high-density lipoprotein, Glucose (CHG) Index

Background: Cardiovascular diseases (CVDs) are a leading cause of death, with traditional risk factors like dyslipidemia, insulin resistance (IR), and obesity studied extensively. However, current indices do not fully integrate glucose and cholesterol metabolism. This study introduces the Cholesterol, HDL, and Glucose Index (CHG) as a more comprehensive biomarker for diagnosing CVDs and compares its predictive value to existing indices like TyG, AIP, and LAP. Materials and Methods: The Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study is a longitudinal prospective cohort study initiated in 2010, involving 7,641 participants. Over a 10-year follow-up, expert cardiologists diagnosed CVDs based on clinical evaluations and medical history. Receiver operating characteristic (ROC) curve analysis was employed to determine the cut-off values of CHG and other indices such as TyG, AIP, and LAP and compare their sensitivity and specificity. Results: Among the 7,433 participants, 837 were diagnosed with CVDs. CHG showed the highest discriminatory power in assessing CVDs risk, with an area under the curve (AUC) of 0.660 (95% CI: 0.649-0.671, p<0.001) and a cut-off value of 5.28. TyG, LAP, and AIP showed lower AUC values of 0.637 (95% CI: 0.626-0.648, p<0.001), 0.599 (95% CI: 0.588-0.611, p<0.001), and 0.592 (95% CI: 0.580-0.603, p<0.001), respectively, with corresponding cut-off values of 8.93, 40.42, and 0.38. Conclusion: CHG is an innovative composite index that combines glucose and lipid markers, enhancing its predictive capability for diagnosing cardiovascular diseases. This index delivers a more thorough evaluation of cardiometabolic health, taking into account the intricate relationship between glucose and lipid metabolism in the development of CVDs.