Open AccessPredictive Ability of Novel Cardiac Biomarkers ST 2, Galectin‐3, and NT ‐Pro BNP Before Cardiac Surgery
Author(s) -
Polineni Sai,
Parker Devin M.,
Alam Shama S.,
ThiessenPhilbrook Heather,
McArthur Eric,
DiScipio Anthony W.,
Malenka David J.,
Parikh Chirag R.,
Garg Amit X.,
Brown Jeremiah R.
Publication year - 2018
Publication title -
journal of the american heart association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.494
H-Index - 85
ISSN - 2047-9980
DOI - 10.1161/jaha.117.008371
Subject(s) - medicine , natriuretic peptide , odds ratio , confidence interval , cardiology , cardiac surgery , coronary artery disease , prospective cohort study , biomarker , predictive value of tests , receiver operating characteristic , surgery , heart failure , biochemistry , chemistry
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 ‐Pro BNP ), and soluble ST 2 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 ‐Pro BNP , and ST 2. In‐hospital mortality and adverse events occurring after coronary artery bypass graft were the outcomes. After adjustment, NT ‐Pro BNP and ST 2 showed a statistically significant association with both their median and third tercile categories with NT ‐Pro BNP odds ratios of 2.89 (95% confidence interval [ CI ]: 1.04–8.05) and 5.43 (95% CI : 1.21–24.44) and ST 2 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 ‐pro BNP and ST 2 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.