Troponin is superior to electrocardiogram and creatinine kinase MB for predicting clinically significant myocardial injury after coronary artery bypass grafting

Abstract

Aims: Cardiac biomarkers are routinely elevated after uncomplicated cardiac surgery to levels considered diagnostic of myocardial infarction in ambulatory populations. We investigated the diagnostic power of electrocardiogram (ECG) and cardiac biomarker criteria to predict clinically relevant myocardial injury using benchmarks of mortality and increased hospital length of stay (HLOS) in patients undergoing coronary artery bypass graft (CABG) surgery.

Methods and results: Perioperative ECGs, creatinine kinase MB fraction, and cardiac troponin I (cTnI) were assessed in 545 primary CABG patients. None of the ECG criteria for myocardial injury predicted mortality or HLOS. However, post-operative day (POD) 1 cTnI levels independently predicted 5-year mortality (hazard ratio = 1.42; 95% CI 1.14-1.76 for each 10 microg/L increase; P = 0.009), while adjusting for baseline demographic characteristics and perioperative risk factors. Moreover, cTnI was the only biomarker that significantly improved the prediction of 5-year mortality estimated by the logistic Euroscore (P = 0.02). Furthermore, the predictive value of cTnI for 5-year mortality was replicated in a separately collected cohort of 1031 CABG patients using cardiac troponin T.

Conclusion: Electrocardiogram diagnosis of post-operative myocardial injury after CABG does not independently predict an increased risk of 5-year mortality or HLOS. Conversely, cTnI is independently associated with an increased risk of mortality and prolonged HLOS.

Figure 1

CONSORT diagram. ECG indicates electrocardiogram; MI, myocardial infarction; OPCAB, off-pump coronary artery bypass grafting; PFO, patent foramen ovale; cTnT, cardiac troponin T.

Figure 2

Distribution of troponin levels across all seven perioperative time points. Whisker plot showing box with median cTnI levels with edge of boxes at 25–75% and whiskers extending to the 10–90th percentile. cTnI indicates cardiac troponin I; Pre, pre-operative; Post, immediately post-protamine.

Figure 3

Forest plot demonstrating predictive value of biomarkers and ECG for all-cause mortality and hospital length of stay. Cox multivariable proportional hazards model, adjusted for demographic and clinical covariates, is shown for each individual variable. HRs and 95% CIs are shown. All biomarkers were entered as continuous variables. Significances for mortality: POD1 cTnI (HR 1.42 for each 10 µg/L increase; 95% CI 1.14–1.76; P = 0.009), POD1 CKMB (HR 1.23 for each 25 µg/L increase; 95% CI 1.02–1.48; P = 0.034) Significances for HLOS: POD1 cTnI (HR 1.13 for each 10 µg/L increase, 95% CI 1.02–1.26; P = 0.011), POD1 CKMB (HR 1.06 for each 25 µg/L increase, 95% CI 1.01–1.12; P = 0.01) HR indicates hazard ratio; CI, confidence interval; CKMB creatinine kinase MB fraction; cTnI, cardiac troponin I; POD, post-operative day; ECG, electrocardiogram.

Figure 4

Kaplan–Meier survival for troponin dichotomized at optimal ROC. Shown are unadjusted all-cause survival curves for troponin at respective cut-offs. The optimal dichotomization point was determined in a Cox proportional hazard model for mortality by examining the troponin level which resulted in maximal improvement in model performance shown by the negative two log-likelihood ratio. Additionally, area under the curve (AUC) was examined in receiver operating characteristic (ROC) curves in a multivariable model for mortality to confirm the optimal cut-point selection. cTnT and cTnI indicate cardiac troponin T and I.