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

Arch Intern Med. 2003 Oct 27;163(19):2345-53. doi: 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Female
  • Hospital Mortality*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Myocardial Ischemia / mortality*
  • Prognosis
  • Risk Assessment
  • Risk Factors