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Validity of a risk-prediction tool for hospital mortality: the Global Registry of Acute Coronary Events
GRACE Publications
  • Karen S. Pieper, Duke University
  • Joel M. Gore, University of Massachusetts Medical School
  • Gordon Fitzgerald, University of Massachusetts Medical School
  • Christopher B. Granger, Duke University
  • Robert J. Goldberg, University of Massachusetts Medical School
  • Phillippe Gabriel Steg, Centre Hospitalier Bichat-Claude Bernard
  • Kim A. Eagle, University of Michigan
  • Frederick A. Anderson, Jr., University of Massachusetts Medical School
  • Andrzej Budaj, Grochowski Hospital
  • Keith A. A. Fox, University of Edinburgh
UMMS Affiliation
Center for Outcomes Research; Department of Medicine, Division of Cardiovascular Medicine
Document Type
Medical Subject Headings
Acute Coronary Syndrome; Aged; Female; Forecasting; *Hospital Mortality; Humans; Male; Middle Aged; *Models, Cardiovascular; Nomograms; Prognosis; *Registries; Risk Assessment; Treatment Outcome
BACKGROUND: The Global Registry of Acute Coronary Events (GRACE) risk model provides a simple method for determining the probability of hospital death in acute coronary syndrome (ACS). The aim of this study was to explore the impact of modeling techniques on the risk model when generating predictions. METHODS: Patients with ACS (n = 48,023) with or without ST-segment elevation myocardial infarction (STEMI) were enrolled (123 hospitals, 14 countries) between April 1999 and June 2006. The original GRACE model did not include terms to account for possible differences in outcomes between patients with STEMI, non-STEMI, and unstable angina, nor did it account for changing risk across continuous measures. RESULTS: In this cohort, the influence on outcome of region of hospitalization and cardiac arrest at presentation changed over the 7-year study. Other interactions included previous percutaneous coronary intervention and age with type of ACS. However, these interactions were insufficient to affect the final risk score. The same variables as in the original score comprise the new score. Inclusion of nonlinearity and differential effects did little to change the model's discrimination but influenced predictions for patients at extremes of risk. CONCLUSIONS: Irrespective of the inclusion of nonlinear and interaction terms, the updated GRACE risk model provides an excellent means to discriminate risk of death in patients with ACS and can be used as a simple nomogram to estimate risk in patients seen in clinical practice.
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Citation: Am Heart J. 2009 Jun;157(6):1097-105. Link to article on publisher's site
Related Resources
Link to Article in PubMed
PubMed ID
Citation Information
Karen S. Pieper, Joel M. Gore, Gordon Fitzgerald, Christopher B. Granger, et al.. "Validity of a risk-prediction tool for hospital mortality: the Global Registry of Acute Coronary Events" Vol. 157 Iss. 6 (2009) ISSN: 0002-8703 (Linking)
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