Our previous work demonstrated that algorithms combining high sensitivity cardiac troponin T (hs-cTnT) and heart-type fatty acid-binding protein (H-FABP) may help in ruling out Acute Myocardial Infarction (AMI). For those algorithms, the hs-cTnT thresholds were adopted from the ESC guidelines. This time, we present a data-driven approach that also explores hs-cTnT thresholds. The results show a significant improvement when compared to previous algorithms reported. Using a cohort of n=360 patients (288 Non-AMI and 72 AMI), a rule-out algorithm used at presentation identified more ‘low-risk’ patients who presented with chest pain of suspected cardiac origin than the standard ESC algorithm: (199/288 (69.1%) vs. 83/288 (28.8%) (p <0.0005)), respectively. According to our data, our algorithm at the emergency department, would identify additional non-AMI patients in comparison to the ESC algorithm, potentially reducing the number of hospital admissions by 42%.
|Title of host publication||Proceedings of Computing in Cardiology. IEEEE|
|Number of pages||4|
|Publication status||Accepted/In press - 1 Oct 2019|