Validity of a risk-prediction tool for hospital mortality: the Global Registry of Acute Coronary Events
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Authors
Pieper, Karen S.Gore, Joel M.
Fitzgerald, Gordon
Granger, Christopher B.
Goldberg, Robert J.
Steg, Phillippe Gabriel
Eagle, Kim A.
Anderson, Frederick A. Jr.
Budaj, Andrzej
Fox, Keith A. A.
UMass Chan Affiliations
Department of Medicine, Division of Cardiovascular MedicineCenter for Outcomes Research
Document Type
Journal ArticlePublication Date
2009-05-26Keywords
Acute Coronary SyndromeAged
Female
Forecasting
*Hospital Mortality
Humans
Male
Middle Aged
*Models, Cardiovascular
Nomograms
Prognosis
*Registries
Risk Assessment
Treatment Outcome
Health Services Research
Metadata
Show full item recordAbstract
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.Source
Am Heart J. 2009 Jun;157(6):1097-105. Link to article on publisher's siteDOI
10.1016/j.ahj.2009.04.004Permanent Link to this Item
http://hdl.handle.net/20.500.14038/27207PubMed ID
19464422Related Resources
Link to Article in PubMedae974a485f413a2113503eed53cd6c53
10.1016/j.ahj.2009.04.004