Predictors of outcome in patients with acute coronary syndromes without persistent ST-segment elevation. Results from an international trial of 9461 patients. The PURSUIT Investigators
BACKGROUND: Appropriate treatment policies should include an accurate
estimate of a patient's baseline risk. Risk modeling to date has been
underutilized in patients with acute coronary syndromes without persistent
ST-segment elevation. METHODS AND RESULTS: We analyzed the relation
between baseline characteristics and the 30-day incidence of death and the
composite of death or myocardial (re)infarction in 9461 patients with
acute coronary syndromes without persistent ST-segment elevation enrolled
in the PURSUIT trial [Platelet glycoprotein IIb/IIIa in Unstable angina:
Receptor Suppression Using Integrilin (eptifibatide) Therapy]. Variables
examined included demographics, history, hemodynamic condition, and
symptom duration. Risk models were created with multivariable logistic
regression and validated by bootstrapping techniques. There was a 3.6%
mortality rate and 11.4% infarction rate by 30 days. More than 20
significant predictors for mortality and for the composite end point were
identified. The most important baseline determinants of death were age
(adjusted chi(2)=95), heart rate (chi(2)=32), systolic blood pressure
(chi(2)=20), ST-segment depression (chi(2)=20), signs of heart failure
(chi(2)=18), and cardiac enzymes (chi(2)=15). Determinants of mortality
were generally also predictive of death or myocardial (re)infarction.
Differences were observed, however, in the relative prognostic importance
of predictive variables for mortality alone or the composite end point;
for example, sex was a more important determinant of the composite end
point (chi(2)=21) than of death alone (chi(2)=10). The accuracy of the
prediction of the composite end point was less than that of mortality
(C-index 0.67 versus 0.81). CONCLUSIONS: The occurrence of adverse events
after presentation with acute coronary syndromes is affected by multiple
factors. These factors should be considered in the clinical
decision-making process