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    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 Medicine
    Center for Outcomes Research
    Document Type
    Journal Article
    Publication Date
    2009-05-26
    Keywords
    Acute Coronary Syndrome
    Aged
    Female
    Forecasting
    *Hospital Mortality
    Humans
    Male
    Middle Aged
    *Models, Cardiovascular
    Nomograms
    Prognosis
    *Registries
    Risk Assessment
    Treatment Outcome
    Health Services Research
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    Link to Full Text
    http://dx.doi.org/10.1016/j.ahj.2009.04.004
    Abstract
    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 site
    DOI
    10.1016/j.ahj.2009.04.004
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/27207
    PubMed ID
    19464422
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ahj.2009.04.004
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