Predictive value of the novel cardiometabolic index for reduced aerobic capacity in patients with coronary heart disease: a clinical comparative study of 378 cases

BACKGROUND: Coronary heart disease(CHD) is an important cause of cardiovascular diseases and, under adverse conditions such as arteriosclerosis, will raise the risk of death significantly. Due to the shortcomings of traditional adiposity indices when assessing aerobic capacity (AC), this paper intended to explore whether the novel cardiometabolic index (CMI) could predict lower AC in patients with coronary heart disease. METHODS: A retrospective analysis was performed on 378 hospitalized patients with coronary heart disease who underwent treatment and completed cardiopulmonary exercise testing. Patients were grouped according to AC levels and CMI levels, and the baseline characteristics of both groups were assessed.Three multivariable binary logistic regression models were constructed to evaluate the associations of the CMI, body mass index (BMI), and waist-to-height ratio (WHtR) with reduced AC. Receiver operating characteristic (ROC) curve analysis was performed to assess and compare the predictive performance of the three models, including the area under the curve (AUC). Model fit was further evaluated using the - 2 log-likelihood, Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC). Calibration of each model was assessed using the Hosmer-Lemeshow test, and DeLong's test was used to compare differences in AUC values between models. RESULTS: Three multivariable logistic regression models were constructed, each incorporating different core variables (BMI, WHtR, and CMI) along with other relevant covariates. Variance inflation factor (VIF) analysis confirmed the absence of significant multicollinearity among variables. Model performance evaluation demonstrated that Model 3, which included CMI, had the best fit, with the lowest - 2 log-likelihood, AIC, and BIC values, good calibration (Hosmer-Lemeshow test, P = 0.441), and the highest AUC (0.671, 95% CI: 0.605-0.736). However, DeLong's test revealed that the difference in AUC between Model 3 and Model 1, as well as between Model 3 and Model 2, did not reach statistical significance (P = 0.062 and P = 0.110, respectively). CONCLUSION: CMI demonstrates clinical potential in evaluating the decline of AC in patients with CHD.