Multiple Biomarkers at Admission Significantly Improve the Prediction of Mortality in Patients Undergoing Primary Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction

Peter Damman, Marcel A. M. Beijk, Wichert J. Kuijt, Niels J. W. Verouden, Nan van Geloven, José P. S. Henriques, Jan Baan, Marije M. Vis, Martijn Meuwissen, Jan P. van Straalen, Johan Fischer, Karel T. Koch, Jan J. Piek, Jan G. P. Tijssen, Robbert J. de Winter

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Abstract

We investigated whether multiple biomarkers improve prognostication in ST-segment elevation myocardial infarction (STEMI) patients undergoing primary percutaneous coronary intervention. Few data exist on the prognostic value of combined biomarkers. 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. 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 (0.494, p < 0.001) and integrated discrimination improvement (0.0295, p < 0.01). 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
Original languageEnglish
Pages (from-to)29-36
JournalJournal of the American College of Cardiology
Volume57
Issue number1
DOIs
Publication statusPublished - 2011

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