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    Predictors of hospital mortality in the global registry of acute coronary events

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    Authors
    Granger, Christopher B.
    Goldberg, Robert J.
    Dabbous, Omar H.
    Pieper, Karen S.
    Eagle, Kim A.
    Cannon, Christopher P.
    Van de Werf, Frans
    Avezum, Alvaro
    Goodman, Shaun G.
    Flather, Marcus
    Fox, Keith A. A.
    Show allShow less
    UMass Chan Affiliations
    Department of Medicine, Division of Cardiovascular Medicine
    Document Type
    Journal Article
    Publication Date
    2003-10-29
    Keywords
    Aged
    Female
    *Hospital Mortality
    Humans
    Logistic Models
    Male
    Middle Aged
    Multivariate Analysis
    Myocardial Ischemia
    Prognosis
    Risk Assessment
    Risk Factors
    Bioinformatics
    Biostatistics
    Epidemiology
    Health Services Research
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    Metadata
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    Link to Full Text
    http://dx.doi.org/10.1001/archinte.163.19.2345
    Abstract
    BACKGROUND: Management of acute coronary syndromes (ACS) should be guided by an estimate of patient risk. OBJECTIVE: To develop a simple model to assess the risk for in-hospital mortality for the entire spectrum of ACS treated in general clinical practice. METHODS: A multivariable logistic regression model was developed using 11 389 patients (including 509 in-hospital deaths) with ACS with and without ST-segment elevation enrolled in the Global Registry of Acute Coronary Events (GRACE) from April 1, 1999, through March 31, 2001. Validation data sets included a subsequent cohort of 3972 patients enrolled in GRACE and 12 142 in the Global Use of Strategies to Open Occluded Coronary Arteries IIb (GUSTO-IIb) trial. RESULTS: The following 8 independent risk factors accounted for 89.9% of the prognostic information: age (odds ratio [OR], 1.7 per 10 years), Killip class (OR, 2.0 per class), systolic blood pressure (OR, 1.4 per 20-mm Hg decrease), ST-segment deviation (OR, 2.4), cardiac arrest during presentation (OR, 4.3), serum creatinine level (OR, 1.2 per 1-mg/dL [88.4- micro mol/L] increase), positive initial cardiac enzyme findings (OR, 1.6), and heart rate (OR, 1.3 per 30-beat/min increase). The discrimination ability of the simplified model was excellent with c statistics of 0.83 in the derived database, 0.84 in the confirmation GRACE data set, and 0.79 in the GUSTO-IIb database. CONCLUSIONS: Across the entire spectrum of ACS and in general clinical practice, this model provides excellent ability to assess the risk for death and can be used as a simple nomogram to estimate risk in individual patients.
    Source
    Arch Intern Med. 2003 Oct 27;163(19):2345-53. Link to article on publisher's site
    DOI
    10.1001/archinte.163.19.2345
    Permanent Link to this Item
    http://hdl.handle.net/20.500.14038/47166
    PubMed ID
    14581255
    Related Resources
    Link to Article in PubMed
    ae974a485f413a2113503eed53cd6c53
    10.1001/archinte.163.19.2345
    Scopus Count
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    Population and Quantitative Health Sciences Publications

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