Development of a Novel Risk Prediction Tool for Emergency Department Patients Symptoms of Coronary Artery Disease

Patients with chest pain and symptoms of acute coronary syndromes (ACS) account for over 600,000 emergency department (ED) visits annually in Canada. 85% of these patients do not have an ACS, and most are discharged from the ED after a thorough evaluation. However, a large proportion of these patients (approximately 180,000 annually) are referred for outpatient objective cardiac testing (exercise stress tests, myocardial perfusion scans, coronary CT angiography) after ED discharge, even though their short-term risk of major adverse cardiac events such as death, new myocardial infarction or need for revascularization is very small. This contributes to substantial low-value healthcare utilization, and limits access for those patients who are likely to benefit from objective testing.

Clinical risk prediction tools can improve the appropriateness of utilization of cardiac testing. However, existing risk prediction tools were developed prior to the advent of new high-sensitivity cardiac troponin assays, were derived in non-representative populations and, when applied to ED patients with low cardiac troponin concentrations, systematically overestimate short-term risk of major adverse cardiac events (MACE).

New, more specific, risk prediction tools are required to accurately guide clinical decision-making for patients who have had an emergency department evaluation for suspected coronary disease. The objective of this research program is to develop individualized risk prediction tools for patients who have had an MI ruled out in the emergency department, to identify patients who are likely to benefit from additional cardiac testing, and to guide the appropriate timing of testing. In other words, the objective is to provide personalized risk estimates to get the Right Patient the Right Test at the Right Time.

We will conduct a multicenter prospective cohort study including emergency department chest pain patients to derive personalized risk prediction tools to distinguish patients at low risk of MACE and not requiring additional cardiac testing from patients who are likely to benefit from additional cardiac testing. We will leverage the existing clinical research infrastructure of the Canadian Emergency Department Rapid Response Network to enrol a large population of representative patients.

The risk prediction tools that we will develop will innovate in the following ways:

1. We will include the right population, namely patients who have had MI ruled out in the ED, as current risk prediction tools were derived in different populations; 2. We will provide improved accounting for sex and the presence of pre-existing coronary disease compared to previous tools; 3. We will incorporate the latest generation cardiac troponin assay; 4. We will investigate the utility of other commonly available biomarkers that have excellent predictive utility in other cardiovascular diseases; 5. We will undertake time-to-event analyses to suggest the optimal timing of additional cardiac testing;

5\) We will provide granular, individualized risk estimates to guide decision-making around which patients need additional testing.

The knowledge product of this work will improve patient outcomes while also optimizing the appropriate utilization of objective cardiac testing modalities.