An Algorithm Based on Combining hs-cTNT and H-FABP for Ruling Out Acute Myocardial Infarction

Cesar Navarro, Mary Jo Kurth, Mark Ruddock, Sam Fishlock, James McLaughlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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%.
Original languageEnglish
Title of host publicationProceedings of Computing in Cardiology. IEEEE
PublisherIEEE Xplore
Number of pages4
Publication statusAccepted/In press - 1 Oct 2019

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