Predictors of hospital mortality in the global registry of acute coronary events.
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.
Division of Cardiology, University Medical Center, Durham, NC, USA.
Christopher B
CB
Granger
Robert J
RJ
Goldberg
Omar
O
Dabbous
Karen S
KS
Pieper
Kim A
KA
Eagle
Christopher P
CP
Cannon
Frans
F
Van De Werf
Alvaro
A
Avezum
Shaun G
SG
Goodman
Marcus D
MD
Flather
Keith A A
KA
Fox
D000368:Aged; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D017202:Myocardial Ischemia / Q000401:mortality*; D011379:Prognosis; D018570:Risk Assessment; D012307:Risk Factors