title: Current status of risk stratification methods in acute coronary syndromes.
abstract: Distinguishing which patients with chest pain are at high risk versus which are at low risk remains an important clinical problem despite modern risk stratification strategies. Current approaches often over-utilize hospital resources, yet still miss a significant number of true acute coronary syndromes (ACS). This review focuses on important developments in risk stratification in ACS from 2004 through 2005. Risk models have been developed that use readily available patient characteristics, and head to head comparisons of the various models have been performed to guide clinicians in selecting between the different options. The most powerful models now include measurement of renal function, which has emerged as an important marker of risk. In addition to cardiac troponins, B-type natriuretic peptide (BNP) clearly augments risk prediction, and in the past year serial BNP measurement after discharge has shown promise as a simple way to monitor patient risk following ACS. Newer biomarkers are on the horizon but have not yet established their clinical value. Finally, advances in coronary CT angiography and bedside echocardiography offer hope that noninvasive imaging may play a more important role in early risk stratification in the near future.
authors.affiliation: Cardiology Division , UT Southwestern Medical Center, 5909 Harry Hines Boulevard, HA 9.133, Dallas, TX 75390-9047, USA. james.delemos@utsouthwestern.edu
authors.forename: Raphael
authors.initials: R
authors.lastname: See
authors.forename: James A
authors.initials: JA
authors.lastname: de Lemos
mesh_terms: D000418:Albumins / Q000032:analysis; D015415:Biomarkers / Q000032:analysis*; D002097:C-Reactive Protein / Q000032:analysis; D017023:Coronary Angiography; D003404:Creatinine / Q000032:analysis; D010450:Endopeptidases / Q000032:analysis; D006801:Humans; D009203:Myocardial Infarction / Q000175:diagnosis*; D020097:Natriuretic Peptide, Brain / Q000032:analysis; D000072483:Placenta Growth Factor; D011237:Predictive Value of Tests; D011257:Pregnancy Proteins / Q000032:analysis; D011266:Pregnancy-Associated Plasma Protein-A / Q000032:analysis; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D048008:TNF Receptor-Associated Factor 3; D014336:Troponin / Q000032:analysis; D047988:Tumor Necrosis Factor Receptor-Associated Peptides and Proteins / Q000032:analysis
chemical_list: D000418:Albumins; D015415:Biomarkers; C000608036:PGF protein, human; D011257:Pregnancy Proteins; D048008:TNF Receptor-Associated Factor 3; C090656:TRAF3 protein, human; D014336:Troponin; D047988:Tumor Necrosis Factor Receptor-Associated Peptides and Proteins; D020097:Natriuretic Peptide, Brain; D000072483:Placenta Growth Factor; D002097:C-Reactive Protein; D003404:Creatinine; D010450:Endopeptidases; C430889:PAPPA2 protein, human; D011266:Pregnancy-Associated Plasma Protein-A