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A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry
GRACE Publications
  • Kim A. Eagle, University of Michigan
  • Michael J. Lim, Saint Louis University
  • Omar H. Dabbous, University of Massachusetts Medical School
  • Karen S. Pieper, Duke University
  • Robert J. Goldberg, University of Massachusetts Medical School
  • Frans Van de Werf, Universitair Ziekenhuis Gasthuisberg
  • Shaun G. Goodman, University of Toronto
  • Christopher B. Granger, Duke University
  • Phillippe Gabriel Steg, Centre Hospitalier Bichat-Claude Bernard
  • Joel M. Gore, University of Massachusetts Medical School
  • Andrzej Budaj, Grochowski Hospital
  • Alvaro Avezum, Dante Pazzanese Institute of Cardiology
  • Marcus D. Flather, Royal Brompton and Harefield National Health Service Trust
  • Keith A. A. Fox, University of Edinburgh
UMMS Affiliation
Center for Outcomes Research; Department of Medicine, Division of Cardiovascular Medicine
Date
6-10-2004
Document Type
Article
Medical Subject Headings
Aged; Angina, Unstable; Cause of Death; *Decision Support Techniques; Female; Hospitalization; Humans; Male; Middle Aged; Myocardial Ischemia; Registries; *Risk Assessment
Abstract
CONTEXT: Accurate estimation of risk for untoward outcomes after patients have been hospitalized for an acute coronary syndrome (ACS) may help clinicians guide the type and intensity of therapy. OBJECTIVE: To develop a simple decision tool for bedside risk estimation of 6-month mortality in patients surviving admission for an ACS. DESIGN, SETTING, AND PATIENTS: A multinational registry, involving 94 hospitals in 14 countries, that used data from the Global Registry of Acute Coronary Events (GRACE) to develop and validate a multivariable stepwise regression model for death during 6 months postdischarge. From 17,142 patients presenting with an ACS from April 1, 1999, to March 31, 2002, and discharged alive, 15,007 (87.5%) had complete 6-month follow-up and represented the development cohort for a model that was subsequently tested on a validation cohort of 7638 patients admitted from April 1, 2002, to December 31, 2003. MAIN OUTCOME MEASURE: All-cause mortality during 6 months postdischarge after admission for an ACS. RESULTS: The 6-month mortality rates were similar in the development (n = 717; 4.8%) and validation cohorts (n = 331; 4.7%). The risk-prediction tool for all forms of ACS identified 9 variables predictive of 6-month mortality: older age, history of myocardial infarction, history of heart failure, increased pulse rate at presentation, lower systolic blood pressure at presentation, elevated initial serum creatinine level, elevated initial serum cardiac biomarker levels, ST-segment depression on presenting electrocardiogram, and not having a percutaneous coronary intervention performed in hospital. The c statistics for the development and validation cohorts were 0.81 and 0.75, respectively. CONCLUSIONS: The GRACE 6-month postdischarge prediction model is a simple, robust tool for predicting mortality in patients with ACS. Clinicians may find it simple to use and applicable to clinical practice.
Rights and Permissions
Citation: JAMA. 2004 Jun 9;291(22):2727-33. Link to article on publisher's site
Related Resources
Link to Article in PubMed
PubMed ID
15187054
Citation Information
Kim A. Eagle, Michael J. Lim, Omar H. Dabbous, Karen S. Pieper, et al.. "A validated prediction model for all forms of acute coronary syndrome: estimating the risk of 6-month postdischarge death in an international registry" Vol. 291 Iss. 22 (2004) ISSN: 0098-7484 (Linking)
Available at: http://works.bepress.com/robert_goldberg/314/