External validation of the myocardial-ischaemic-injury-index machine learning algorithm for the early diagnosis of myocardial infarction: a multicentre cohort study.

BACKGROUND

The myocardial-ischaemic-injury-index (MI

METHODS

In this secondary analysis of a multicentre international diagnostic cohort study, adult patients (age >18 years) presenting to the emergency department with symptoms suggestive of myocardial infarction were prospectively enrolled from April 21, 2006, to Feb 27, 2019 in 12 centres from five European countries (Switzerland, Spain, Italy, Poland, and Czech Republic). Patients were excluded if they presented with ST-segment-elevation myocardial infarction, did not have at least two serial high-sensitivity cardiac troponin I (hs-cTnI) measurements, or if the final diagnosis remained unclear. The final diagnosis was centrally adjudicated by two independent cardiologists using all available medical records, including serial hs-cTnI measurements and cardiac imaging. The primary outcome was type 1 NSTEMI. The performance of MI

FINDINGS

Among 6487 patients, (median age 61·0 years [IQR 49·0-73·0]; 2122 [33%] female and 4365 [67%] male), 882 (13·6%) patients had type 1 NSTEMI. The median time difference between the first and second hs-cTnI measurement was 60·0 mins (IQR 57·0-70·0). MI

INTERPRETATION

MI

FUNDING

Swiss National Science Foundation, Swiss Heart Foundation, the EU, the University Hospital Basel, the University of Basel, Abbott, Beckman Coulter, Roche, Idorsia, Ortho Clinical Diagnostics, Quidel, Siemens, and Singulex.

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests PL-A has received research grants from the Swiss Heart Foundation (FF20079 and FF21103) and speaker's honoraria from Quidel, paid to their institution and outside the submitted work. JB has received research grants from the University of Basel and the Division of Internal Medicine, the Swiss Academy of Medical Sciences, and the Gottfried and Julia Bangerter-Rhyner-Foundation; and speaker honoraria from Siemens, outside the submitted work. TN has received research support from the Swiss National Science Foundation (P400PM_191037/1), the Prof Dr Max Cloëtta Foundation, the Margarete und Walter Lichtenstein-Stiftung (3MS1038), and the University Hospital Basel; and speaker or consulting honoraria or research support from Edwards Lifesciences, Boston Scientific, Medtronic, Abbott, Beckman Coulter, Bayer, Ortho Clinical Diagnostics, and Orion Pharma, outside the submitted work. LK has received a research grant from the Swiss Heart Foundation, University of Basel, the Swiss Academy of Medical Sciences, the Gottfried and Julia Bangerter-Rhyner-Foundation, and the Freiwillige Akademische Gesellschaft Basel; and speaker honoraria from Roche Diagnostics, Abbott, and Siemens, paid to their institution and outside the submitted work. PB has received a research grant from the Swiss Heart Foundation (FF23062). CM reports receiving research support from the Swiss National Science Foundation, the Swiss Heart Foundation, the University of Basel, the University Hospital Basel, Abbott, Beckman Coulter, Brahms, Idorsia, LSI Medience Corporation, Novartis, Ortho Diagnostics, Quidel, Roche, Siemens, Singulex, and Sphingotec; and speaker honoraria or consulting honoraria from Abbott, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Idorsia, Novartis, Osler, Roche, and Sanofi, all paid to their institution. All other authors declare no competing interests.