BackgroundCurrent preoperative models use clinical risk factors alone in estimating risk of inâhospital mortality following cardiac surgery. However, novel biomarkers now exist to potentially improve preoperative prediction models. An assessment of Galectinâ3, Nâterminal pro bâtype natriuretic peptide (NTâProBNP), and soluble ST2 to improve the predictive ability of an existing prediction model of inâhospital mortality may improve our capacity to riskâstratify patients before surgery.Methods and ResultsWe 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 galectinâ3, NTâProBNP, and ST2. Inâhospital mortality and adverse events occurring after coronary artery bypass graft were the outcomes. After adjustment, NTâProBNP and ST2 showed a statistically significant association with both their median and third tercile categories with NTâProBNP odds ratios of 2.89 (95% confidence interval [CI]: 1.04â8.05) and 5.43 (95% CI: 1.21â24.44) and ST2 odds ratios of 3.96 (95% CI: 1.60â9.82) and 3.21 (95% CI: 1.17â8.80), respectively. The model receiver operating characteristic score of the base prediction model (0.80 [95% CI: 0.72â0.89]) varied significantly from the new multiâmarker model (0.85 [95% CI: 0.79â0.91]). Compared with the Northern New England (NNE) model alone, the full prediction model with biomarkers NTâproBNP and ST2 shows significant improvement in model classification of inâhospital mortality.ConclusionsThis study demonstrates a significant improvement of preoperative prediction of inâhospital mortality in patients undergoing coronary artery bypass graft and suggests that biomarkers can be used to identify patients at higher risk.