Multiple biomarkers at admission significantly improve the prediction of mortality in patients undergoing primary percutaneous coronary intervention for acute ST-segment elevation myocardial infarction.

OBJECTIVES

We investigated whether multiple biomarkers improve prognostication in ST-segment elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention.

BACKGROUND

Few data exist on the prognostic value of combined biomarkers.

METHODS

We used data from 1,034 STEMI patients undergoing primary percutaneous coronary intervention in a high-volume percutaneous coronary intervention center in the Netherlands and investigated whether combining N-terminal pro-brain natriuretic peptide, glucose, C-reactive protein, estimated glomerular filtration rate, and cardiac troponin T improved the prediction of mortality. A risk score was developed based on the strongest predicting biomarkers in multivariate Cox regression. The additional prognostic value of the strongest predicting biomarkers to the established prognostic factors (age, body weight, diabetes, hypertension, systolic blood pressure, heart rate, anterior myocardial infarction, and time to treatment) was assessed in multivariable Cox regression.

RESULTS

During follow-up (median, 901 days), 120 of the 1,034 patients died. In Cox regression, glucose, estimated glomerular filtration rate, and N-terminal pro-brain natriuretic peptide were the strongest predictors for mortality (p < 0.05, for all). A risk score incorporating these biomarkers identified a high-risk STEMI subgroup with a significantly higher mortality when compared with an intermediate- or low-risk subgroup (p < 0.001). Addition of the 3 biomarkers to established prognostic factors significantly improved prediction for mortality, as shown by the net reclassification improvement (0.481, p < 0.001) [corrected] and integrated discrimination improvement (0.0226, p = 0.03) [corrected].

CONCLUSIONS

Our data suggest that addition of a multimarker to a model including established risk factors improves the prediction of mortality in STEMI patients undergoing primary percutaneous coronary intervention. Furthermore, the use of a simple risk score based on these biomarkers identifies a high-risk subgroup.