Modified cardiometabolic index and stroke risk: Evidence from the CHARLS cohort
TL;DR
Although MCMI demonstrated slightly better predictive performance than CMI, the improvement was limited, and additional large-scale prospective studies and validation analyses are required before its routine use in clinical risk stratification can be considered.
Abstract
The association between the modified cardiometabolic index (MCMI) and stroke risk remains unclear. This study aimed to investigate the relationship between MCMI and incident stroke. A total of 8167 participants from the China Health and Retirement Longitudinal Study (baseline 2011) were included. MCMI was calculated as ln[triglycerides × fasting blood glucose/ high-density lipoprotein cholesterol] × waist circumference/ height. Incident stroke was defined as self-reported physician-diagnosed stroke during follow-up through 2020. Cox proportional hazards regression, restricted cubic spline (RCS) modeling, and subgroup analyses were performed to examine the association. Time-dependent receiver operating characteristic (ROC) analysis was used to compare the predictive performance of MCMI with that of the cardiometabolic index (CMI). Over 9 years of follow-up, higher MCMI levels were associated with increased stroke risk (hazard ratio [HR] = 1.32, 95% confidence interval [CI]: 1.20–1.46). Quartile analyses confirmed this trend, with the highest quartile showing the greatest risk compared with the lowest (HR = 2.30, 95% CI: 1.80–2.94). RCS analysis revealed a nonlinear relationship (P for nonlinearity = 0.002). Subgroup analyses suggested potential heterogeneity across marital status and residential location. ROC analysis showed that the MCMI consistently yielded higher AUC values than the CMI at 3 years (0.72 vs 0.70), 5 years (0.75 vs 0.73), 7 years (0.77 vs 0.75), and 8 years (0.72 vs 0.70), with all DeLong’s test P-values < 0.05. Higher MCMI levels were positively associated with stroke risk. Although MCMI demonstrated slightly better predictive performance than CMI, the improvement was limited. These findings support an association rather than direct clinical applicability. Additional large-scale prospective studies and validation analyses are required before its routine use in clinical risk stratification can be considered.