A generation ago thrombolytic therapy led to a paradigm shift in myocardial infarction (MI), from Q-wave/non-Q-wave to ST-segment elevation MI (STEMI) vs non-STEMI. Using STE on the electrocardiogram (ECG) as a surrogate marker for acute coronary occlusion (ACO) allowed for rapid diagnosis and treatment. But the vast research catalyzed by the STEMI paradigm has revealed increasing anomalies: 25% of “non-STEMI” have ACO with delayed reperfusion and higher mortality. Studying these limitations has given rise to the occlusion MI (OMI) paradigm, based on the presence or absence of ACO in the patient rather than STE on ECG. The OMI paradigm shift harnesses advanced ECG interpretation aided by artificial intelligence, complementary bedside echocardiography and advanced imaging, and clinical signs of refractory ischemia, and offers the next opportunity to transform emergency cardiology and improve patient care. This State-of-the-Art Review examines the paradigm shifts from Q wave to STEMI to OMI.

ST-elevation Myocardial Infarction (STEMI) guidelines encourage monitoring of false positives (Code STEMI without culprit) but ignore false negatives (non-STEMI with occlusion myocardial infarction [OMI]). We evaluated the hospital course of emergency department (ED) patients with acute coronary syndrome (ACS) using STEMI vs OMI paradigms. This retrospective chart review examined all ACS patients admitted through two academic EDs, from June 2021 to May 2022, categorized as 1) OMI (acute culprit lesion with TIMI 0-2 flow, or acute culprit lesion with TIMI 3 flow and peak troponin I >10,000 ng/L; or, if no angiogram, peak troponin >10,000 ng/L with new regional wall motion abnormality), 2) NOMI (Non-OMI, i.e. MI without OMI) or 3) MIRO (MI ruled out: no troponin elevation). Patients were stratified by admission for STEMI. Initial ECGs were reviewed for automated interpretation of "STEMI", and admission/discharge diagnoses were compared. Among 382 patients, there were 141 OMIs, 181 NOMIs, and 60 MIROs. Only 40.4% of OMIs were admitted as STEMI: 60.0% had "STEMI" on ECG, and median door-to-cath time was 103 min (IQR 71-149). But 59.6% of OMIs were not admitted as STEMI: 1.3% had "STEMI" on ECG (p < 0.001) and median door-to-cath time was 1712 min (IQR 1043-3960; p < 0.001). While 13.9% of STEMIs were false positive and had a different discharge diagnosis, 32.0% of Non-STEMIs had OMI but were still discharged as "Non-STEMI." STEMI criteria miss a majority of OMI, and discharge diagnoses highlight false positive STEMI but never false negative STEMI. The OMI paradigm reveals quality gaps and opportunities for improvement.

Limits to ST-Elevation Myocardial Infarction (STEMI) criteria may lead to prolonged diagnostic time for acute coronary occlusion. We aimed to reduce ECG-to-Activation (ETA) time through audit and feedback on STEMI-equivalents and subtle occlusions, without increasing Code STEMIs without culprit lesions. This multi-centre, quality improvement initiative reviewed all Code STEMI patients from the emergency department (ED) over a one-year baseline and one-year intervention period. We measured ETA time, from the first ED ECG to the time a Code STEMI was activated. Our intervention strategy involved a grand rounds presentation and an internal website presenting weekly local challenging cases, along with literature on STEMI-equivalents and subtle occlusions. Our outcome measure was ETA time for culprit lesions, our process measure was website views/visits, and our balancing measure was the percentage of Code STEMIs without culprit lesions. There were 51 culprit lesions in the baseline period, and 64 in the intervention period. Median ETA declined from 28.0 min (95% confidence interval [CI] 15.0-45.0) to 8.0 min (95%CI 6.0-15.0). The website garnered 70.4 views/week and 27.7 visitors/week in a group of 80 physicians. There was no change in percentage of Code STEMIs without culprit lesions: 28.2% (95%CI 17.8-38.6) to 20.0% (95%CI 11.2-28.8%). Conclusions Our novel weekly web-based feedback to all emergency physicians was associated with a reduction in ETA time by 20 min, without increasing Code STEMIs without culprit lesions. Local ECG audit and feedback, guided by ETA as a quality metric for acute coronary occlusion, could be replicated in other settings to improve care.

According to the STEMI paradigm, only patients whose ECGs meet STEMI criteria require immediate reperfusion. This leads to reperfusion delays and significantly increases the mortality for the quarter of "non-STEMI" patients with totally occluded arteries. The Occlusion MI (OMI) paradigm has developed advanced ECG interpretation to identify this high-risk group, including examining the ECG in totality and assessing ST/T changes in proportion to the QRS. If neural networks are only developed based on STEMI databases and to identify STEMI criteria, they will simply reinforce a failed paradigm. But if deep learning is trained to identify OMI it could revolutionize patient care. This article reviews the paradigm shift from STEMI and OMI, and examines the potential and pitfalls of deep learning. This is based on the Kenichi Harumi Plenary Address at the Annual Meeting of the International Society of Computers in Electrocardiology, given by OMI expert Dr. Stephen Smith.