Epidemiological classification of acute myocardial infarction: time for a change?

Abstract

Aims: The classification of an acute ischaemic cardiac event is traditionally based on cardiac enzymes, electrocardiography (ECG) and clinical symptoms. The impact of new specific cardiac markers on the diagnostic classification of suspected acute myocardial infarction remains poorly studied. We therefore set out to compare the diagnostic and prognostic information provided by the MONICA code and a patient classification based on the maximal level of creatine kinase MB isoenzyme. The significance of typical pain and various ECG algorithms were separately analysed.

Methods and results: The study population consisted of 311 consecutive patients who were evaluated for suspected acute myocardial infarction in a regional referral hospital. Patients were retrospectively classified according to the MONICA criteria, by a simplified code combining symptoms and creatine kinase MB, and solely using the maximal creatine kinase MB concentration. Total mortality was followed for 1 and 5 years. The creatine kinase MB based classification was shown to be the strongest predictor of mortality (OR=2.8-3.7, p<0.001) for outcome both at 1 and 5 years. Typical pain and a positive Minnesota ECG had no prognostic relevance. However, an analysis algorithm of the admission ECG was predictive of 1- and 5-year survival.

Conclusions: The epidemiological classification of suspected acute myocardial infarction could be based solely on a specific cardiac marker, such as creatine kinase MB mass. This approach contains prognostic information and is accurate enough for the structured diagnosis of acute myocardial infarction. Other outcome predictors could be used to identify patient subgroups and assess therapy.