In step II, PMI was diagnosed according to the statements of Joint Task Force of ESC/ACCF/AHA/WHF, the PMI diagnostic ability of miRs was tested and we performed a multivariate analysis. Continuous variables were expressed as the mean 6 standard deviation or median as appropriate. Categorical variables were described by counts and percentages. Plasma miRNA levels were presented as the foldchange relative to the controls. Linear regression models were used to clarify the relationships between miRs and the diagnostic components of the baseline or cTnI levels. The mean miRNA levels of CABG patients were compared at seven time points with the baseline using repeated measures ANOVA. Bonferroni correction was performed for multiple testing when continuous variables were compared between groups. Receiver operating characteristic curves were established for diagnosing patients with PMI, and a multivariate logistic regression analysis was performed. An alpha of 0.05 was set as the level of statistical significance. The present study provides the first insights into circulating miRs in cardiac surgery. We demonstrated the time course of circulating miRs in cardiac injury and clarified their correlation to the traditional marker cTnI. We demonstrated that circulating miRs, consistent with the Icotinib Hydrochloride results of a previous study of acute myocardial inarction patients, appeared earlier than the protein marker cTnI in the blood, peaked and quickly declined following on-pump CABG surgery. As both on-pump and off-pump techniques were equally used for CABG, we further detected the time course of miRs in Octacosanol offpump CABG group and compared them between the two groups. We found that on-pump group can cause a high level of miR release, far higher than observed in the beating heart group. Our results indicate that the level of miR-499 at 6 hours after surgery can clearly predict the occurrence of PMI, with a very high sensitivity and specificity. These results reveal, for the first time, that miR-499 is potentially a stronger biomarker than troponin in predicting PMI in the early postoperative period.