International evaluation of an artificial intelligence-powered electrocardiogram model detecting acute coronary occlusion myocardial infarction.

Acute coronary syndrome Artificial intelligence Electrocardiogram Myocardial infarction NSTEMI Occlusion myocardial infarction

Journal

European heart journal. Digital health
ISSN: 2634-3916
Titre abrégé: Eur Heart J Digit Health
Pays: England
ID NLM: 101778323

Informations de publication

Date de publication:
Mar 2024
Historique:
received: 14 09 2023
revised: 13 10 2023
accepted: 02 11 2023
medline: 20 3 2024
pubmed: 20 3 2024
entrez: 20 3 2024
Statut: epublish

Résumé

A majority of acute coronary syndromes (ACS) present without typical ST elevation. One-third of non-ST-elevation myocardial infarction (NSTEMI) patients have an acutely occluded culprit coronary artery [occlusion myocardial infarction (OMI)], leading to poor outcomes due to delayed identification and invasive management. In this study, we sought to develop a versatile artificial intelligence (AI) model detecting acute OMI on single-standard 12-lead electrocardiograms (ECGs) and compare its performance with existing state-of-the-art diagnostic criteria. An AI model was developed using 18 616 ECGs from 10 543 patients with suspected ACS from an international database with clinically validated outcomes. The model was evaluated in an international cohort and compared with STEMI criteria and ECG experts in detecting OMI. The primary outcome of OMI was an acutely occluded or flow-limiting culprit artery requiring emergent revascularization. In the overall test set of 3254 ECGs from 2222 patients (age 62 ± 14 years, 67% males, 21.6% OMI), the AI model achieved an area under the curve of 0.938 [95% confidence interval (CI): 0.924-0.951] in identifying the primary OMI outcome, with superior performance [accuracy 90.9% (95% CI: 89.7-92.0), sensitivity 80.6% (95% CI: 76.8-84.0), and specificity 93.7 (95% CI: 92.6-94.8)] compared with STEMI criteria [accuracy 83.6% (95% CI: 82.1-85.1), sensitivity 32.5% (95% CI: 28.4-36.6), and specificity 97.7% (95% CI: 97.0-98.3)] and with similar performance compared with ECG experts [accuracy 90.8% (95% CI: 89.5-91.9), sensitivity 73.0% (95% CI: 68.7-77.0), and specificity 95.7% (95% CI: 94.7-96.6)]. The present novel ECG AI model demonstrates superior accuracy to detect acute OMI when compared with STEMI criteria. This suggests its potential to improve ACS triage, ensuring appropriate and timely referral for immediate revascularization.

Identifiants

pubmed: 38505483
doi: 10.1093/ehjdh/ztad074
pii: ztad074
pmc: PMC10944682
doi:

Types de publication

Journal Article

Langues

eng

Pagination

123-133

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.

Déclaration de conflit d'intérêts

Conflict of interest: R.H. is the co-founder and Chief Medical Officer of Powerful Medical; M.M., J.B., A.I., B.V., V.B., V.K., and A.D. are employees and shareholders of Powerful Medical. S.W.S., H.P.M., and L.P. are shareholders in Powerful Medical.

Auteurs

Robert Herman (R)

Department of Advanced Biomedical Sciences, University of Naples Federico II, C.so Umberto I, 40, 80138 Naples, Italy.
Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.
Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.

Harvey Pendell Meyers (HP)

Department of Emergency Medicine, Carolinas Medical Center, Charlotte, NC, USA.

Stephen W Smith (SW)

Department of Emergency Medicine, University of Minnesota, Minneapolis, MN, USA.
Department of Emergency Medicine, Hennepin Healthcare, Minneapolis, MN, USA.

Dario T Bertolone (DT)

Department of Advanced Biomedical Sciences, University of Naples Federico II, C.so Umberto I, 40, 80138 Naples, Italy.
Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Attilio Leone (A)

Department of Advanced Biomedical Sciences, University of Naples Federico II, C.so Umberto I, 40, 80138 Naples, Italy.
Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Konstantinos Bermpeis (K)

Department of Advanced Biomedical Sciences, University of Naples Federico II, C.so Umberto I, 40, 80138 Naples, Italy.
Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Michele M Viscusi (MM)

Department of Advanced Biomedical Sciences, University of Naples Federico II, C.so Umberto I, 40, 80138 Naples, Italy.
Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Marta Belmonte (M)

Department of Advanced Biomedical Sciences, University of Naples Federico II, C.so Umberto I, 40, 80138 Naples, Italy.
Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Anthony Demolder (A)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.

Vladimir Boza (V)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.
Faculty of Mathematics, Physics and Informatics, Comenius University in Bratislava, Bratislava, Slovakia.

Boris Vavrik (B)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.

Viera Kresnakova (V)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.
Department of Cybernetics and Artificial Intelligence, Technical University of Kosice, Kosice, Slovakia.

Andrej Iring (A)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.

Michal Martonak (M)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.

Jakub Bahyl (J)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.

Timea Kisova (T)

Powerful Medical, Bratislavska 81/37, 931 01 Samorin, Slovakia.
Faculty of Medicine and Dentistry, Barts and The London School of Medicine and Dentistry, London, UK.

Dan Schelfaut (D)

Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Marc Vanderheyden (M)

Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Leor Perl (L)

Department of Cardiology, Rabin Medical Center, Petah Tikvah, Israel.

Emre K Aslanger (EK)

Department of Cardiology, Basaksehir Cam and Sakura City Hospital, Istanbul, Turkey.

Robert Hatala (R)

Department of Arrhythmia and Pacing, National Institute of Cardiovascular Diseases, Bratislava, Slovakia.

Wojtek Wojakowski (W)

Department of Cardiology and Structural Heart Diseases, Medical University of Silesia, Katowice, Poland.

Jozef Bartunek (J)

Cardiovascular Centre Aalst, OLV Hospital, Moorselbaan 164, Aalst 9300, Belgium.

Emanuele Barbato (E)

Department of Clinical and Molecular Medicine, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy.

Classifications MeSH