title: Risk adjustment for in-hospital mortality of contemporary patients with acute myocardial infarction: the acute coronary treatment and intervention outcomes network (ACTION) registry-get with the guidelines (GWTG) acute myocardial infarction mortality model and risk score.
abstract: BACKGROUND
  accurate risk adjustment is needed to guide quality improvement initiatives and research to improve care of patients with acute myocardial infarction (MI). We developed and validated a model to predict the risk of in-hospital mortality for contemporary patients with acute MI treated in routine clinical practice.
  
  
  METHODS
  the Acute Coronary Treatment and Intervention Outcomes Network (ACTION) Registry-Get With The Guidelines (GWTG) database of patients with acute MI was used to derive (n = 65,668 from 248 US sites) and validate (n = 16,336) a multivariable logistic regression model to predict the likelihood of in-hospital mortality (4.9% in each cohort).
  
  
  RESULTS
  factors with the highest independent significance in terms of mortality prediction included age, baseline serum creatinine, systolic blood pressure, troponin elevation, heart failure and/or cardiogenic shock at presentation, ST-segment changes, heart rate, and prior peripheral arterial disease. The model showed very good discrimination, with c statistics of 0.85 and 0.84 in the derivation and validation cohorts, respectively. The model calibrated well overall and in key patient subgroups including males versus females, age <75 versus ≥ 75 years, diabetes versus no diabetes, and ST-elevation MI versus non-ST-elevation MI. The ACTION Registry-GWTG in-hospital mortality risk score was also developed from the model. Patients with a risk score of ≤ 40 had an observed mortality rate of <4% compared with those with a risk score of 41-50 (12%) and risk scores >50 (34%).
  
  
  CONCLUSIONS
  the ACTION Registry-GWTG™ in-hospital mortality model and risk score represent simple, accurate risk adjustment tools for contemporary patients with acute MI.
authors.affiliation: Duke Clinical Research Institute, Durham, NC; National Heart Centre Singapore, Singapore.
authors.forename: Chee Tang
authors.initials: CT
authors.lastname: Chin
authors.forename: Anita Y
authors.initials: AY
authors.lastname: Chen
authors.forename: Tracy Y
authors.initials: TY
authors.lastname: Wang
authors.forename: Karen P
authors.initials: KP
authors.lastname: Alexander
authors.forename: Robin
authors.initials: R
authors.lastname: Mathews
authors.forename: John S
authors.initials: JS
authors.lastname: Rumsfeld
authors.forename: Christopher P
authors.initials: CP
authors.lastname: Cannon
authors.forename: Gregg C
authors.initials: GC
authors.lastname: Fonarow
authors.forename: Eric D
authors.initials: ED
authors.lastname: Peterson
authors.forename: Matthew T
authors.initials: MT
authors.lastname: Roe
mesh_terms: D000368:Aged; D005260:Female; D005500:Follow-Up Studies; D017052:Hospital Mortality / Q000639:trends; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000401:mortality* / Q000628:therapy; D009204:Myocardial Revascularization / Q000379:methods*; D012042:Registries; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D014481:United States / Q000453:epidemiology