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

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 proceeding › Conference contribution › peer-review

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 language	English
Title of host publication	Proceedings of Computing in Cardiology. IEEEE
Publisher	IEEE Xplore
Number of pages	4
Publication status	Accepted/In press - 1 Oct 2019

Cite this

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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 {\textquoteleft}low-risk{\textquoteright} 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",

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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

PB - IEEE Xplore

ER -

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

Abstract

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