The ACTION Registry–GWTG (Acute Coronary Treatment and Interventions Outcomes Network—Get With the Guidelines) database proved to be a credible measure for risk adjustment and stratification in patients with acute myocardial infarction (MI), according to an analysis published in the Journal of the American College of Cardiology.
The database is an update on the ACTION–GWTG mortality risk model. It is a voluntary, hospital-based registry that receives data on consecutive patients admitted with acute MI, either ST-segment elevation MI (STEMI) or non–ST-segment elevation MI (NSTEMI), from participating hospitals across the United States.
“The new ACTION Registry–GWTG in-hospital mortality risk model and risk score represent robust, parsimonious, and contemporary risk adjustment methodology for use in routine clinical care and hospital quality assessment,” researchers wrote.
“The addition of risk adjustment for patients presenting after cardiac arrest is critically important and enables a fairer assessment across hospitals with varied case mix. This new model should enable improved assessment of hospital quality and enhance research into best practices to further reduce mortality in patients with acute MI.”
Robert McNamara, MD, MHS, of Yale University School of Medicine in New Haven, Connecticut, and colleagues also built a parsimonious risk score that could be used prospectively for risk stratification. The final model included age, heart rate, systolic blood pressure, presentation after cardiac arrest, presentation in cardiogenic shock, presentation in heart failure, presentation with STEMI, creatinine clearance, and troponin ratio as factors for risk adjustment.
Data on 243 440 patients with acute MI treated from January 2012 to December 2013 at 665 participating hospitals are included in the new database. The patiently population was randomly divided into a derivation cohort (n=145 952) and a validation cohort (n=97 288).
The final ACTION Registry–GWTG model had high discrimination in both the derivation and validation populations, with a C statistic of 0.88 for both. Researchers added that there was “excellent calibration of the model in the validation cohort” with a slope of 0.996 (P=.74) and an intercept of –0.025 (P=.42).
“The C statistics are high in this model in part because overall mortality is relatively low, except for some patients with very high risk characteristics, such as presentation in cardiogenic shock and presentation with cardiac arrest,” Dr McNamara and colleagues wrote. “Thus, the model may be more useful for benchmarking mortality outcomes, rather than prospective clinical decision making, given that it is often not difficult to identify patients with these high-risk characteristics.”
Researchers added that the model “performed well” in various subgroups, including patients with STEMI or NSTEMI and patients with and without cardiac arrest.
McNamara RL, Kennedy KL, Cohen DJ, et al. Predicting in-hospital mortality in patients with acute myocardial Infarction. J Am Coll Cardiol. 2016;68(6):626-635. doi: 10.1016/j.jacc.2016.05.049.