Predictive value of creatine kinase MB for contrast-induced acute kidney injury among myocardial infarction patients

Background Predictive value of creatine kinase MB (CK-MB) for contrast-induced acute kidney injury (CI-AKI) among myocardial infarction (MI) patients has rarely been reported. We aim to evaluate the predictive value of CK-MB for CI-AKI among MI patients. Methods Totally, 1131 MI patients were included from the REduction of rIsk for Contrast-Induced Nephropathy (REICIN) study. The peak CK-MB before coronary angiography (CAG) was chosen. The study population was divided into two groups by log-transformed CK-MB cut-off point. The association between CK-MB and CI-AKI was tested by multivariable logistic regression. CK-MB was integrated with Age, creatinine and ejection fraction (ACEF) score and Mehran risk score (MRS) to evaluate the additive value of CK-MB. The integrated models were validated internally by the bootstrap method and externally by the PREdictive Value of COntrast voluMe to creatinine Clearance Ratio (PRECOMIN) study data set. Results Overall, 62(5.48%) patients developed CI-AKI, patients with CK-MB point > 4.7 displayed a higher incidence of CI-AKI than those without (11.9% vs. 4.0%, p < 0.001). CK-MB point > 4.7 was independently associated with CI-AKI (adjusted OR: 3.40, 95% CI: 1.93-5.98, p < 0.001). The additions of CK-MB to ACEF score, Mehran score A and Mehran score B resulted in increases in C-statistics, which ranged from 0.680 to 0.733 (p = 0.046), 0.694 to 0.727 (p = 0.091), 0.704 to 0.734 (p = 0.102), respectively. Internal validation also showed increases in C-statistics, and external validation performed well in discrimination and calibration. Conclusions Preprocedural peak CK-MB was a predictor of CI-AKI among MI patients.

Automated summary

This study evaluated the predictive value of CK-MB for CI-AKI among MI patients, finding that CK-MB was independently associated with CI-AKI. Additionally, integrating CK-MB with ACEF score, Mehran score A, and Mehran score B resulted in increased C-statistics. Internal validation showed consistent results, and external validation demonstrated good discrimination and calibration.