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

Fingerprint

Fatty Acid-Binding Proteins
Myocardial Infarction
Troponin T
Chest Pain
Hospital Emergency Service
Guidelines

Cite this

Navarro, C., Kurth, M. J., Ruddock, M., Fishlock, S., & McLaughlin, J. (Accepted/In press). An Algorithm Based on Combining hs-cTNT and H-FABP for Ruling Out Acute Myocardial Infarction. In Proceedings of Computing in Cardiology. IEEEE
@inproceedings{4929f40608c24ba3813953939b1e02ae,
title = "An Algorithm Based on Combining hs-cTNT and H-FABP for Ruling Out Acute Myocardial Infarction",
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{\%}.",
author = "Cesar Navarro and Kurth, {Mary Jo} and Mark Ruddock and Sam Fishlock and James McLaughlin",
year = "2019",
month = "10",
day = "1",
language = "English",
booktitle = "Proceedings of Computing in Cardiology. IEEEE",

}

An Algorithm Based on Combining hs-cTNT and H-FABP for Ruling Out Acute Myocardial Infarction. / Navarro, Cesar; Kurth, Mary Jo; Ruddock, Mark; Fishlock, Sam; McLaughlin, James.

Proceedings of Computing in Cardiology. IEEEE. 2019.

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

TY - GEN

T1 - An Algorithm Based on Combining hs-cTNT and H-FABP for Ruling Out Acute Myocardial Infarction

AU - Navarro, Cesar

AU - Kurth, Mary Jo

AU - Ruddock, Mark

AU - Fishlock, Sam

AU - McLaughlin, James

PY - 2019/10/1

Y1 - 2019/10/1

N2 - 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%.

AB - 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%.

M3 - Conference contribution

BT - Proceedings of Computing in Cardiology. IEEEE

ER -