THE COMBINATION OF CARDIOVASCULAR AND GLYCEMIC BIOMARKERS FOR EARLY DECISION MAKING IN PATIENTS PRESENTING TO THE EMERGENCY DEPARTMENT WITH SYMPTOMS OF ACUTE CORONARY SYNDROME

Abstract

Chest pain is a common presenting complaint to emergency departments (EDs) and is a symptom of serious cardiovascular events such as myocardial infarction (MI) and possibly cardiovascular death. Early decision-making regarding patient disposition is crucial for early intervention and to avoid ED congestion. The Third Universal Definition of MI states that MI diagnosis be made using electrocardiogram (ECG) findings and/or a rise and/or fall in cardiac troponin (cTn) concentrations. However, patients with ECG abnormalities represent less than 1/3 of all ACS patients, leaving the remaining to be diagnosed using multiple measurements of cTn over several hours. I therefore aimed to develop a strategy to identify patients at low-risk for major adverse cardiovascular events (early rule-out), as well as those at greatest short-term cardiac risk (early rule-in). In this thesis I present published work on the clinical utility of glycogen phosphorylase Isoenzyme BB (metabolic marker) in combination with high-sensitivity cTn (hs-cTn) to rule-out adverse cardiac events within 72hrs for patients presenting to the ED within 6hrs of ACS symptom onset. I further assessed the utility of metabolic markers using glucose in this setting. Preliminary results show that using a “healthy” hs-cTn concentration with a normal glucose measurement at presentation can be used to rule-out patients who present to the ED with clinical suspicion of ischemia. Further expansion of this hypothesis demonstrated that an algorithm incorporating both glucose and cTn can effectively rule-in/rule-out MI or MI/cardiovascular death in patients who present to the ED with symptoms of ACS. In addition, presentation hemoglobin A1c identified previously unknown diabetes; which may have overall health implications for these patients. I also demonstrate that using glucose in combination with cTn is a cost-effective decision-making tool in the ED as compared to cTn alone. Application of these rule-in/rule-out algorithms can improve morbidity/mortality rates, and alleviate healthcare burdens.