A Bayesian approach to acute coronary occlusion

Jesse T T McLaren; Stephen W Smith

doi:10.1016/j.jelectrocard.2023.10.011

A Bayesian approach to acute coronary occlusion

J Electrocardiol. 2023 Nov-Dec:81:300-302. doi: 10.1016/j.jelectrocard.2023.10.011. Epub 2023 Nov 2.

Authors

Jesse T T McLaren¹, Stephen W Smith²

Affiliations

¹ Department of Family and Community Medicine, University Health Network, Toronto, Ontario, Canada. Electronic address: jesse.mclaren@gmail.com.
² Department of Emergency Medicine, Hennepin Country Medical Centre, Minneapolis, MN, USA. Electronic address: smith253@umn.edu.

PMID: 37951822
DOI: 10.1016/j.jelectrocard.2023.10.011

Abstract

In the STEMI paradigm, the disease (acute coronary occlusion) is defined and named after one element (ST elevation, without regard to the remainder of the QRST) of one imperfect test (the ECG). This leads to delayed reperfusion for patients with acute coronary occlusion whose ECGs don't meet STEMI criteria. In this editorial, we elaborate on the article by Jose Nunes de Alencar Neto about applying Bayesian reasoning to ECG interpretation. The Occlusion MI (OMI) paradigm offers evidencebased advances in ECG interpretation, expert-trained artificial intelligence, and a paradigm shift that incorporates a Bayesian approach to acute coronary occlusion.

Keywords: Electrocardiography; Occlusion MI; ST elevation myocardial infarction.

Publication types

Editorial
Comment

MeSH terms

Artificial Intelligence
Bayes Theorem
Coronary Occlusion*
Electrocardiography
Humans
ST Elevation Myocardial Infarction*