• Chee Tang Chin, Anita Y Chen, Tracy Y Wang, Karen P Alexander, Robin Mathews, John S Rumsfeld, Christopher P Cannon, Gregg C Fonarow, Eric D Peterson, and Matthew T Roe.
• Duke Clinical Research Institute, Durham, NC; National Heart Centre Singapore, Singapore.
• Am. Heart J. 2011 Jan 1; 161 (1): 113-122.e2.

Backgroundaccurate 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.Methodsthe 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).Resultsfactors 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%).Conclusionthe ACTION Registry-GWTG™ in-hospital mortality model and risk score represent simple, accurate risk adjustment tools for contemporary patients with acute MI.

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