Evaluation Of Risk Scores For Risk Stratification Of Acute Coronary Syndromes In The Myocardial Infarction National Audit Project (MINAP) Database

¹ University of Leeds, United Kingdom
² Swansea University, United Kingdom
³ National Institute for Clinical Outcomes Research, United Kingdom
⁴ Pinderfields General Hospital, United Kingdom

^* To whom correspondence should be addressed. E-mail: c.p.gale{at}leeds.ac.uk.

Accepted 15 April 2008

	Abstract

Objective To compare the discriminative performance of the PURSUIT, GUSTO-1, GRACE, SRI and EMMACE risk models, assess their performance among risk supergroups, and evaluate the EMMACE risk model over the wider spectrum of acute coronary syndrome (ACS).

Design Observational study of a national registry.

Setting All acute hospitals in England and Wales.

Patients 100,686 cases of ACS between 2003 and 2005. Main outcome measures: Model performance (C index) in predicting the likelihood of death over the time period for which they were designed. The C index, or area under the receiver operating curve, range 0 to 1, is a measure of the discriminative performance of a model.

Results The C-indices were: PURSUIT C index = 0.79 (95% confidence interval = 0.78 to 0.80); GUSTO-1 = 0.80 (0.79 to 0.81); GRACE in-hospital = 0.80 (0.80 to 0.81); GRACE 6 month = 0.80 (0.79 to 0.80); SRI = 0.79 (0.78 to 0.80); and EMMACE = 0.78 (0.77 to 0.78). EMMACE maintained its ability to discriminate 30-day mortality throughout different ACS diagnoses. Recalibration of the model offered no notable improvement in performance over the original risk equation. For all models the discriminative performance was reduced in patients with diabetes, chronic renal failure or angina.

Conclusion The 5 ACS risk models maintained their discriminative performance in a large unselected English and Welsh ACS population, but performed less well in higher risk supergroups. Simpler risk models had comparable performance to more complex risk models. The EMMACE risk score performed well across the wider spectrum of ACS diagnoses.