RESUMEN
BACKGROUND: Diagnosis of perioperative myocardial infarction (PMI) after coronary artery bypass grafting (CABG) is fraught with complexity since it is primarily based on a single cut-off value for cardiac troponin (cTn) that is exceeded in over 90% of CABG patients, including non-PMI patients. In this study we applied an unsupervised statistical modeling approach to uncover clinically relevant cTn release profiles post-CABG, including PMI, and used this to improve diagnostic accuracy of PMI. METHODS: In 624 patients that underwent CABG, cTnT concentration was serially measured up to 24 h post aortic cross clamping. 2857 cTnT measurements were available to fit latent class linear mixed models (LCMMs). RESULTS: Four classes were found, described by: normal, high, low and rising cTnT release profiles. With the clinical diagnosis of PMI as golden standard, the rising profile had a diagnostic accuracy of 97%, compared to 83% for an optimally chosen cut-off and 21% for the guideline recommended cut-off value. CONCLUSION: Clinically relevant subgroups, including patients with PMI, can be uncovered using serially measured cTnT and a LCMM. The LCMM showed superior diagnostic accuracy of PMI. A rising cTnT profile is potentially a better criterion than a single cut-off value in diagnosing PMI post-CABG.