High sensitivity cardiac troponin T in patients not having an acute coronary syndrome : results from the TRAPID-AMI study

  • Richard Nowak
  • , Christian Mueller
  • , Evangelos Giannitsis
  • , Michael Christ
  • , Jordi Ordonez-Llanos
  • , Christopher DeFilippi
  • , James McCord
  • , Richard Body
  • , Mauro Panteghini
  • , Tomas Jernberg
  • , Mario Plebani
  • , Franck Verschuren
  • , John K. French
  • , Robert Christenson
  • , Gordon Jacobsen
  • , Carina Dinkel
  • , Bertil Lindahl

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Purpose: To describe the baseline, 1 hr and delta high sensitivity cardiac troponin (hs-cTnT) values in patients with suspected acute myocardial infarction (AMI) but without a final acute coronary syndrome (ACS) diagnosis. Materials and methods: hs-cTnT assay for RAPID rule out of acute myocardial infarction (TRAPID-AMI) was a prospective diagnostic trial that enrolled emergency department (ED) patients with suspected AMI. Final patient diagnoses were adjudicated by a clinical events committee and subjects placed in different clinical groups: AMI, unstable angina, non-ACS cardiac, non-cardiac and unknown origin. The baseline, 1 hr and delta hs-cTnT values were analysed in the 902 non-ACS patients. Results: Amongst the 1282 studied the patient groups were 213 (17%) AMI, 167 (13%) unstable angina, 113 (9%) non-ACS cardiac, 288 (22%) non-cardiac and 501 (39%) unknown origin. The hs-cTnT values in the non-cardiac and unknown origin groups were combined. The median hs-cTnT values (ng/L) were higher (p < 0.001) in the non-ACS cardiac compared to the non-cardiac/unknown origin group at baseline (11.8, <5) and 1 hr (12.3, <5). Their negative predictive values were 0.955 (baseline) and 0.954 (1 hr) for predicting non-ACS cardiac versus non-cardiac/unknown origin diagnoses. Conclusions: Hs-cTnT may help predict whether non-ACS ED patients have a final non-ACS cardiac or non-cardiac/unknown origin diagnoses.
Original languageEnglish
Pages (from-to)709-714
Number of pages6
JournalBiomarkers
Volume22
Issue number8
DOIs
Publication statusPublished - 2017

Open Access - Access Right Statement

©2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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