BACKGROUND: For patients presenting with acute coronary syndrome (ACS) to the emergency department, early identification of those that are at high risk for subsequent myocardial necrosis or adverse outcomes would allow earlier or more aggressive treatment. We determined if a panel of biomarkers can be used to identify high risk patients. METHODS: A cohort (84 females/132 males) from our 1996 ACS study population that had EDTA specimens stored (-70 degrees C) was selected and the earliest available specimen was analyzed for 11 biomarkers (IL-6, IL-8, MCP-1, VEGF, L-selectin, P-selectin, E-selectin, ICAM-1, VCAM-1, NT-proBNP, cTnT). These data were linked to the existing cTnI and health outcome databases for this population. ROC curve analysis for myocardial necrosis (i.e., peak cTnI >0.04 microg/l) identified 3 candidate biomarkers. These 3 biomarkers were applied together to generate a panel test (2 of the 3 biomarkers increased for a positive result) and assessed for its ability to identify patients at risk for myocardial necrosis and the combined endpoint of death, myocardial infarction (MI) and heart failure (HF). RESULTS: The panel test (IL-6, NT-proBNP, E-selectin) alone detected 60% (95% CI: 49-69; false positive rate: 26%) of subjects that would be classified with myocardial necrosis. Kaplan-Meier and Cox proportional analyses indicated that patients positive by the biomarker panel (including those with cTnI < or =0.04 microg/l) had significantly worse outcomes (death/MI/HF) as compared to those negative by both cTnI and the panel test. CONCLUSION: A biomarker panel analyzed early after pain onset can identify individuals at risk for both myocardial necrosis and the combined endpoint of death/MI/HF. Additional prospective studies are required to assess this panel for both early MI detection and to further refine which health outcomes (death, MI, HF) are associated with positive panel results.
BACKGROUND: For patients presenting with acute coronary syndrome (ACS) to the emergency department, early identification of those that are at high risk for subsequent myocardial necrosis or adverse outcomes would allow earlier or more aggressive treatment. We determined if a panel of biomarkers can be used to identify high risk patients. METHODS: A cohort (84 females/132 males) from our 1996 ACS study population that had EDTA specimens stored (-70 degrees C) was selected and the earliest available specimen was analyzed for 11 biomarkers (IL-6, IL-8, MCP-1, VEGF, L-selectin, P-selectin, E-selectin, ICAM-1, VCAM-1, NT-proBNP, cTnT). These data were linked to the existing cTnI and health outcome databases for this population. ROC curve analysis for myocardial necrosis (i.e., peak cTnI >0.04 microg/l) identified 3 candidate biomarkers. These 3 biomarkers were applied together to generate a panel test (2 of the 3 biomarkers increased for a positive result) and assessed for its ability to identify patients at risk for myocardial necrosis and the combined endpoint of death, myocardial infarction (MI) and heart failure (HF). RESULTS: The panel test (IL-6, NT-proBNP, E-selectin) alone detected 60% (95% CI: 49-69; false positive rate: 26%) of subjects that would be classified with myocardial necrosis. Kaplan-Meier and Cox proportional analyses indicated that patients positive by the biomarker panel (including those with cTnI < or =0.04 microg/l) had significantly worse outcomes (death/MI/HF) as compared to those negative by both cTnI and the panel test. CONCLUSION: A biomarker panel analyzed early after pain onset can identify individuals at risk for both myocardial necrosis and the combined endpoint of death/MI/HF. Additional prospective studies are required to assess this panel for both early MI detection and to further refine which health outcomes (death, MI, HF) are associated with positive panel results.
Authors: P Aukrust; R K Berge; T Ueland; E Aaser; J K Damås; L Wikeby; A Brunsvig; F Müller; K Forfang; S S Frøland; L Gullestad Journal: J Am Coll Cardiol Date: 2001-02 Impact factor: 24.094
Authors: I Malik; J Danesh; P Whincup; V Bhatia; O Papacosta; M Walker; L Lennon; A Thomson; D Haskard Journal: Lancet Date: 2001-09-22 Impact factor: 79.321
Authors: Tomas Jernberg; Bertil Lindahl; Agneta Siegbahn; Bertil Andren; Gunnar Frostfeldt; Bo Lagerqvist; Mats Stridsberg; Per Venge; Lars Wallentin Journal: J Am Coll Cardiol Date: 2003-12-03 Impact factor: 24.094
Authors: Peter A Kavsak; Andrew Worster; John J You; Mark Oremus; Adell Elsharif; Stephen A Hill; P J Devereaux; Andrew R MacRae; Allan S Jaffe Journal: Clin Biochem Date: 2009-12-21 Impact factor: 3.281
Authors: Peter A Kavsak; Alice M Newman; Dennis T Ko; Glenn E Palomaki; Viliam Lustig; Andrew R MacRae; Allan S Jaffe Journal: Clin Chem Date: 2008-04 Impact factor: 8.327
Authors: Dominika Kanikowska; Małgorzata Pyda; Katarzyna Korybalska; Stefan Grajek; Maciej Lesiak; Andrzej Bręborowicz; Janusz Witowski Journal: Immun Ageing Date: 2014-12-04 Impact factor: 6.400