A feasibility study for CODE-MI: High-sensitivity cardiac troponin–Optimizing the diagnosis of acute myocardial infarction/injury in women

Abstract

CODE-MI is a pan-Canadian, multicentre, stepped-wedge, cluster randomized trial that evaluates the impact of using the female-specific 99th percentile threshold for high-sensitivity cardiac troponin (hs-cTn) on the diagnosis, treatment and outcomes of women presenting to the emergency department (ED) with symptoms suggestive for myocardial ischemia. A feasibility study was conducted to estimate the number of eligible patients, the rate of the study's primary outcome under control conditions, and the statistical power to detect a clinically important difference in the primary outcome. Using linked administrative data from 11 hospitals in Ontario, Canada, from October 2014 to September 2017, the following estimates were obtained: number of women presenting to the ED with symptoms suggestive of myocardial ischemia and a 24-hour peak hs-cTn value within the female-specific and overall thresholds (ie, primary cohort); the rate of the 1-year composite outcome of all-cause mortality, re-admission for nonfatal myocardial infarction, incident heart failure, or emergent/urgent coronary revascularization. Study power was evaluated via simulations. Overall, 2,073,849 ED visits were assessed. Among women, chest pain (with or without cardiac features) and shortness of breath were the most common complaints associated with a diagnosis of acute coronary syndrome. An estimated 7.7% of women with these complaints are eligible for inclusion in the primary cohort. The rate of the 1-year outcome in the primary cohort varied significantly across hospitals with a median rate of 12.2% (95%CI: 7.9%-17.7%). With 30 hospitals, randomized at 5-month intervals in 5 steps, approximately 19,600 women are expected to be included in CODE-MI, resulting in >82% power to detect a 20% decrease in the odds of the primary outcome at a 0.05 significance level. This feasibility study greatly enhanced the design of CODE-MI, allowed accurate evaluation of the study power, and demonstrated the strength of using linked administrative health data to guide the design of pragmatic clinical trials.