Early Diagnosis of Myocardial Infarction With Point-of-Care High-Sensitivity Cardiac Troponin I.

Aged Aged, 80 and over Biomarkers / blood Early Diagnosis Emergency Service, Hospital Female Follow-Up Studies Humans Male Middle Aged Myocardial Infarction / blood Point-of-Care Systems Prospective Studies Troponin I / blood
0/1-h algorithm diagnosis of myocardial infarction guidelines high-sensitivity cardiac troponin I point of care rule in rule out

Journal

Journal of the American College of Cardiology
ISSN: 1558-3597
Titre abrégé: J Am Coll Cardiol
Pays: United States
ID NLM: 8301365

Informations de publication

Date de publication:
17 03 2020
Historique:
received: 18 10 2019
revised: 16 12 2019
accepted: 17 12 2019
entrez: 14 3 2020
pubmed: 14 3 2020
medline: 15 12 2020
Statut: ppublish

Résumé

Until now, high-sensitivity cardiac troponin (hs-cTn) assays were mainly developed for large central laboratory platforms. This study aimed to assess the clinical performance of a point-of-care (POC)-hs-cTnI assay in patients with suspected myocardial infarction (MI). This study enrolled patients presenting to the emergency department with symptoms suggestive of MI. Two cardiologists centrally adjudicated the final diagnosis using all clinical data including cardiac imaging. The primary objective was to directly compare diagnostic accuracy of POC-hs-cTnI-TriageTrue versus best-validated central laboratory assays. Secondary objectives included the derivation and validation of a POC-hs-cTnI-TriageTrue-specific 0/1-h algorithm. MI was the adjudicated final diagnosis in 178 of 1,261 patients (14%). The area under the curve (AUC) for POC-hs-cTnI-TriageTrue at presentation was 0.95 (95% confidence interval [CI]: 0.93 to 0.96) and was at least comparable to hs-cTnT-Elecsys (AUC: 0.94; 95% CI: 0.93 to 0.96; p = 0.213) and hs-cTnI-Architect (AUC: 0.92; 95% CI: 0.90 to 0.93; p < 0.001). A single cutoff concentration <3 ng/l at presentation identified 45% of patients at low risk with a negative predictive value (NPV) of 100% (95% CI: 99.4% to 100%). A single cutoff concentration >60 ng/l identified patients at high risk with a positive predictive value (PPV) of 76.8% (95% CI: 68.9% to 83.6%). The 0/1-h algorithm ruled out 55% of patients (NPV: 100%; 95% CI: 98.8% to 100%), and ruled in 18% of patients (PPV: 76.8%; 95% CI: 67.2% to 84.7%). Ruled-out patients had cumulative event rates of 0% at 30 days and 1.6% at 2 years. This study confirmed these findings in a secondary analysis including hs-cTnI-Architect for central adjudication. The POC-hs-cTnI-TriageTrue assay provides high diagnostic accuracy in patients with suspected MI with a clinical performance that is at least comparable to that of best-validated central laboratory assays. (Advantageous Predictors of Acute Coronary Syndromes Evaluation Study [APACE]; NCT00470587).

Sections du résumé

BACKGROUND
Until now, high-sensitivity cardiac troponin (hs-cTn) assays were mainly developed for large central laboratory platforms.
OBJECTIVES
This study aimed to assess the clinical performance of a point-of-care (POC)-hs-cTnI assay in patients with suspected myocardial infarction (MI).
METHODS
This study enrolled patients presenting to the emergency department with symptoms suggestive of MI. Two cardiologists centrally adjudicated the final diagnosis using all clinical data including cardiac imaging. The primary objective was to directly compare diagnostic accuracy of POC-hs-cTnI-TriageTrue versus best-validated central laboratory assays. Secondary objectives included the derivation and validation of a POC-hs-cTnI-TriageTrue-specific 0/1-h algorithm.
RESULTS
MI was the adjudicated final diagnosis in 178 of 1,261 patients (14%). The area under the curve (AUC) for POC-hs-cTnI-TriageTrue at presentation was 0.95 (95% confidence interval [CI]: 0.93 to 0.96) and was at least comparable to hs-cTnT-Elecsys (AUC: 0.94; 95% CI: 0.93 to 0.96; p = 0.213) and hs-cTnI-Architect (AUC: 0.92; 95% CI: 0.90 to 0.93; p < 0.001). A single cutoff concentration <3 ng/l at presentation identified 45% of patients at low risk with a negative predictive value (NPV) of 100% (95% CI: 99.4% to 100%). A single cutoff concentration >60 ng/l identified patients at high risk with a positive predictive value (PPV) of 76.8% (95% CI: 68.9% to 83.6%). The 0/1-h algorithm ruled out 55% of patients (NPV: 100%; 95% CI: 98.8% to 100%), and ruled in 18% of patients (PPV: 76.8%; 95% CI: 67.2% to 84.7%). Ruled-out patients had cumulative event rates of 0% at 30 days and 1.6% at 2 years. This study confirmed these findings in a secondary analysis including hs-cTnI-Architect for central adjudication.
CONCLUSIONS
The POC-hs-cTnI-TriageTrue assay provides high diagnostic accuracy in patients with suspected MI with a clinical performance that is at least comparable to that of best-validated central laboratory assays. (Advantageous Predictors of Acute Coronary Syndromes Evaluation Study [APACE]; NCT00470587).

Identifiants

DOI: 10.1016/j.jacc.2019.12.065 PMID: 32164884
pubmed: 32164884
pii: S0735-1097(20)30252-7
doi: 10.1016/j.jacc.2019.12.065
pii:
doi:

Substances chimiques

Biomarkers 0
Troponin I 0

Banques de données

ClinicalTrials.gov
['NCT00470587']

Types de publication

Journal Article Multicenter Study Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1111-1124

Investigateurs

Mario Meier (M)
Christian Puelacher (C)
Jeanne du Fay de Lavallaz (J)
Nikola Kozhuharov (N)
Katharina Rentsch (K)
Claudia Stelzig (C)
Kathrin Meissner (K)
Caroline Kulangara (C)
Petra Hillinger (P)
Eleni Michou (E)
Dayana Flores (D)
Tobias Reichlin (T)
Beatriz López (B)
Carolina Fuenzalida (C)
Esther Rodriguez Adrada (ER)
Eva Ganovská (E)
Jens Lohrmann (J)
Jeffrey Huber (J)
Jana Steude (J)
Andreas Buser (A)
Arnold von Eckardstein (A)
Beata Morawiec (B)
Ewa Nowalany-Kozielska (E)
Piotr Muzyk (P)
Franz Bürgler (F)
Nicolas Geigy (N)

Commentaires et corrections

Type : CommentIn
Type : ErratumIn

Informations de copyright

Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.

Auteurs

Jasper Boeddinghaus (J)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy. Electronic address: https://twitter.com/J_Boeddinghaus.

Thomas Nestelberger (T)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy. Electronic address: https://twitter.com/thomas_nest.

Luca Koechlin (L)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Department of Cardiac Surgery, University Hospital Basel, University of Basel, Basel, Switzerland.

Desiree Wussler (D)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Division of Internal Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.

Pedro Lopez-Ayala (P)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy.

Joan Elias Walter (JE)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Division of Internal Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.

Valentina Troester (V)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy.

Paul David Ratmann (PD)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy.

Funda Seidel (F)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy.

Tobias Zimmermann (T)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Division of Internal Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.

Patrick Badertscher (P)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Division of Cardiology, Medical University of South Carolina, Charleston, South Carolina.

Karin Wildi (K)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Critical Care Research Group, the Prince Charles Hospital, Brisbane and the University of Queensland, Brisbane, Queensland, Australia.

Maria Rubini Giménez (M)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Leipzig Heart Center, Leipzig, Germany.

Eliska Potlukova (E)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Division of Internal Medicine, University Hospital Basel, University of Basel, Basel, Switzerland.

Ivo Strebel (I)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy.

Michael Freese (M)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy.

Òscar Miró (Ò)

GREAT Network, Rome, Italy; Emergency Department, Hospital Clinic, Barcelona, Catalonia, Spain.

F Javier Martin-Sanchez (FJ)

GREAT Network, Rome, Italy; Servicio de Urgencias, Hospital Clínico San Carlos, Madrid, Spain.

Damian Kawecki (D)

GREAT Network, Rome, Italy; Second Department of Cardiology, School of Medicine with the Division of Dentistry in Zabrze, Medical University of Katowice, Katowice, Poland.

Dagmar I Keller (DI)

Emergency Department, University Hospital Zurich, Zurich, Switzerland.

Danielle M Gualandro (DM)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy; Heart Institute (InCor), University of Sao Paulo Medical School, Sao Paulo Brazil.

Michael Christ (M)

GREAT Network, Rome, Italy; Emergency Department, Kantonsspital Luzern, Luzern, Switzerland.

Raphael Twerenbold (R)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy.

Christian Mueller (C)

Cardiovascular Research Institute Basel and Department of Cardiology, University Hospital Basel, University of Basel, Switzerland; GREAT Network, Rome, Italy. Electronic address: christian.mueller@usb.ch.

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Classifications MeSH

questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Sujet âgé › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Sujet âgé › Sujet âgé de 80 ans ou plus › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Facteurs biologiques › Marqueurs biologiques › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Diagnostic › Diagnostic précoce › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Administration des services de santé › Organisation et administration › Administration d'établissement de santé › Administration hospitalière › Services hospitaliers › Service hospitalier d'urgences › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études de suivi › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Personnes › Tranches d'âge › Adulte › Adulte d'âge moyen › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › États, signes et symptômes pathologiques › Processus pathologiques › Nécrose › Infarctus › Infarctus du myocarde › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Administration des services de santé › Gestion des soins aux patients › Systèmes automatisés lit malade › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études de cohortes › Études prospectives › Early Diagnosis of Myocardial Infarction With...
questionsmedicales.fr › Acides aminés, peptides et protéines › Protéines › Protéines du cytosquelette › Protéines des microfilaments › Troponine › Troponine I › Early Diagnosis of Myocardial Infarction With...