Cardiac Troponin I and Q-wave perioperative myocardial infarction after coronary artery bypass surgery

Objective: To monitor cardiac troponin I (cTnI), a newly developed biochemical index for cardiac damage, in patients during and after coronary artery bypass surgery (CABS) to determine whether the measurement of the serum levels of this marker could be of value in formulating an early diagnosis of Q-wave perioperative myocardial infarction (PMI). Design: Prospective study with sequential measurements of biological markers in a selected surgical patient group. Setting: University research laboratory and general university hospital (Cardiac Surgery Unit and Anesthesiology and Reanimation Unit). Patients: Forty two patients undergoing elective CABS without concomitant valvular replacement. Interventions: There were no interventions required for this study. However, patients entered into the study had CABS, sequential arterial blood samples, ECG recordings, and echocardiograms performed. Measurements and Main Results: Pre, intra, and postoperative (up to 48 hrs) measurements of cardiac troponin I, MB CK, and total creatine kinase, as well as serial electrocardiograms and echocardiograms. Perioperative infarction was assessed as the development of new persistent regional wall motion abnormalities in echocardiography together with electrocardiographic alterations and MB CK increases. Eight patients had Q-wave PMI. All PMI patients had elevated peak cTnI values (all >9.2 ng/mL), whereas the 34 nonPMI patients had peak values <9.0 ng/mL; therefore, sensitivity and specificity (with a 9.0 ng/mL cut off value) are 100%. MB-CK measurement peak values did not demonstrate such a high specificity and sensitivity. Conclusions: Because of its high specificity and sensitivity, serial measurements of cTnI provide a rapid and accurate method for confirming or excluding the diagnosis of perioperative myocardial injury. cTnI evaluation can therefore be used both as an independent prognostic marker for patients undergoing cardiac surgery and as a powerful tool for detecting smaller PMIs often missed with standard PMI diagnostic criteria.