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The following is a summary of “Modeling creatine-kinase MB concentrations following coronary artery bypass grafting,” published in the August 2024 issue of Surgery by Romeo et al.

Accurate detection of periprocedural myocardial infarction (PMI) following coronary artery bypass grafting (CABG) hinges on identifying elevated cardiac biomarkers, particularly serum creatine kinase-MB (CK-MB). This study focused on developing a model to understand the kinetics of CK-MB in the early postoperative phase, aiming to enhance risk detection and identify factors influencing CK-MB levels.

The study included patients who underwent elective CABG with CK-MB measurements taken within the first 72 hours post-surgery. The primary objective was to model the post-hoc kinetics of CK-MB in patients who showed no potential signs of PMI. The criteria for excluding potential PMI included the absence of ischemic electrocardiographic changes, imaging abnormalities, in-hospital cardiac arrest, mortality, or the need for unplanned postoperative catheterization. A web-based application was developed using mixed-effect modeling techniques to provide an interactive and individualized analysis of CK-MB kinetics.

The study involved 635 patients undergoing elective isolated CABG, with 1,589 CK-MB measurements. Of these, 609 patients (96%) did not exhibit potential PMI, while 26 (4%) did. The analysis revealed that CK-MB concentrations were significantly influenced by factors such as male sex, aortic cross-clamp time, and the type of cardioplegia used during surgery. The model demonstrated a diagnostic accuracy with an area under the receiver operating characteristic (ROC) curve of 82.8% (CI: 72.6-90.2%). A CK-MB threshold of 7 μg/L yielded a sensitivity of 94% and a specificity of 80% for excluding potential PMI, with a positive predictive value of 17% and a negative predictive value of 99% within the study population.

In conclusion, the release of CK-MB following CABG is contingent on several factors, including measurement timing, patient sex, aortic cross-clamp duration, and cardioplegia type. The model developed in this study offers a robust tool for early PMI risk detection, with the potential for validation, refinement, and application to other cardiac biomarkers, thereby contributing to more precise postoperative monitoring and patient care.

Source: sciencedirect.com/science/article/pii/S0022522324007037