Despite advances in their treatment, acute coronary syndromes (ACS) continue to carry significant mortality and morbidity. Identifying higher risk patients, and hence selecting those who would most benefit from more aggressive therapies, forms an integral approach to ACS management and outcome[1 2]. Such stratification of patients on admission (near-point testing) is based on patient-specific variables which have been shown in randomised controlled trials (RCT) and observational databases to be associated with mortality. The logistic regression of these variables on clinical outcomes to generate scores of risk has sought to help physicians identify patients for whom tailored therapy would offer a reduction in mortality risk.
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