Abstract
BACKGROUND: Current preoperative models use clinical risk factors alone in estimating risk of in-hospital mortality following cardiac surgery. However, novel biomarkers now exist to potentially improve preoperative prediction models. An assessment of Galectin-3, N-terminal pro b-type natriuretic peptide (NT-ProBNP), and soluble ST2 to improve the predictive ability of an existing prediction model of in-hospital mortality may improve our capacity to risk-stratify patients before surgery. METHODS AND RESULTS: We measured preoperative biomarkers in the NNECDSG (Northern New England Cardiovascular Disease Study Group), a prospective cohort of 1554 patients undergoing coronary artery bypass graft surgery. Exposures of interest were preoperative levels of galectin-3, NT-ProBNP, and ST2. In-hospital mortality and adverse events occurring after coronary artery bypass graft were the outcomes. After adjustment, NT-ProBNP and ST2 showed a statistically significant association with both their median and third tercile categories with NT-ProBNP odds ratios of 2.89 (95% confidence interval [CI]: 1.04-8.05) and 5.43 (95% CI: 1.21-24.44) and ST2 odds ratios of 3.96 (95% CI: 1.60-9.82) and 3.21 (95% CI: 1.17-8.80), respectively. The model receiver operating characteristic score of the base prediction model (0.80 [95% CI: 0.72-0.89]) varied significantly from the new multi-marker model (0.85 [95% CI: 0.79-0.91]). Compared with the Northern New England (NNE) model alone, the full prediction model with biomarkers NT-proBNP and ST2 shows significant improvement in model classification of in-hospital mortality. CONCLUSIONS: This study demonstrates a significant improvement of preoperative prediction of in-hospital mortality in patients undergoing coronary artery bypass graft and suggests that biomarkers can be used to identify patients at higher risk.