Background: In the emergency department discrimination of patients with type 1 myocardial infarction (T1MI) or type 2 myocardial infarction (T2MI) is difficult. In prior work we developed a model, which allows discrimination of T1MI and T2MI based on clinical variables and cardiac troponin concentrations. We now sought to investigate the discriminative value of multi biomarker panel including 28 biomarkers in this setting.

Methods: We recruited patients presenting to the emergency department with suspected MI. The final diagnosis of all patients was adjudicated by two physicians in a blinded fashion and based on the fourth universal definition of MI. A panel of 28 biomarkers were measured in blood samples collected directly at admission. We used multivariable logistic regression analysis to evaluate the association of these biomarkers with the diagnosis of MI. Biomarkers were chosen via backward step-down selection maximizing the Akaike Information Criteria.

Results: 748 patients were recruited, and 138 patients were diagnosed as having MI (107 T1MI and 31 T2MI). The median age was 64 years and 63.1% were males. Hypertension was present in 65.9% and dyslipidemia in 37.0%. In the multivariable model four biomarkers (apolipoprotein A-II, n-terminal prohormone of brain natriuretic peptide, copeptin and high-sensitivity troponin I) remained as significant discriminators between T1MI and T2MI after backward selection (Table 1). Internal validation of the model via bootstrap showed a for overoptimism corrected area under the curve of 0.82.

Conclusion: Among 28 biomarkers, we identified apolipoprotein A-II, n-terminal prohormone of brain natriuretic peptide, copeptin and high-sensitivity troponin I to be the most relevant discriminators between T1MI and T2MI. A regression model based on these biomarkers allowed a good discrimination and could improve the diagnostic evaluation in the emergency department. 

Table 1: Results of multivariable logistic regression model for T1MI vs T2MI as the dependent variable.