Overview

The goal of this clinical trial is to evaluate whether an artificial intelligence (AI)-based ECG interpretation tool improves the early diagnosis and treatment of occlusion myocardial infarction (OMI) in adults presenting with suspected acute coronary syndrome (ACS) who do not meet traditional ST-elevation myocardial infarction (STEMI) criteria.

The main questions it aims to answer are:

1. Does AI-assisted ECG interpretation enable more timely identification and treatment of OMI, as defined by earlier initiation of coronary intervention?
2. Does AI-assisted diagnosis reduce infarct size, measured by peak high-sensitivity troponin T (hsTnT) levels?

Researchers will compare AI-assisted ECG interpretation to standard care to determine if the AI tool improves clinical outcomes and care timelines.

Participants will:

1. Present with symptoms suggestive of ACS but without clear STEMI criteria
2. Be randomized 1:1 to either AI-assisted or standard ECG interpretation
3. Undergo follow-up assessments for cardiovascular outcomes, including 30-day death, time to treatment of total coronary occlusion, and peak hsTnT levels

Eligibility

Inclusion Criteria:

1. Symptoms suspected of ongoing acute myocardial ischemia: Patients presenting with symptoms such as chest pain, dyspnoea, sweating, nausea or vomiting, pain radiating to the shoulder/arm/jaw/back, fatigue, or light-headedness
2. Age: Patients aged 18 years or older.
3. Informed Consent: Patients able to provide informed consent

Exclusion Criteria:

1. Clear diagnosis of ST-segment elevation MI (STEMI) according to managing physicians.
2. Pregnancy or Lactation.
3. Legally incompetent to provide informed consent.
4. Symptoms onset\>24 hrs prior to clinical presentation.