Predictors of hospital mortality in the global registry of acute coronary events
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.
UMass Chan Affiliations
Department of Medicine, Division of Cardiovascular MedicineDocument Type
Journal ArticlePublication Date
2003-10-29Keywords
AgedFemale
*Hospital Mortality
Humans
Logistic Models
Male
Middle Aged
Multivariate Analysis
Myocardial Ischemia
Prognosis
Risk Assessment
Risk Factors
Bioinformatics
Biostatistics
Epidemiology
Health Services Research
Metadata
Show full item recordAbstract
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 siteDOI
10.1001/archinte.163.19.2345Permanent Link to this Item
http://hdl.handle.net/20.500.14038/47166PubMed ID
14581255Related Resources
Link to Article in PubMedae974a485f413a2113503eed53cd6c53
10.1001/archinte.163.19.2345