ROMIAE (Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis) Trial (ROMIAE)

A Prospective, Multicenter, Observational Diagnostic Study to Externally Validate an Artificial Intelligence 12-lead Electrocardiogram Analysis Algorithm to Detect Patients With Acute Myocardial Infarction Who Visit Emergency Medical Center

This study is a prospective multicenter observational study for external validation and model advancement of a deep learning based 12-lead electrocardiogram analysis algorithm targeting adult patients presenting to the emergency department with chest pain and acute myocardial infarction equivalent symptoms.

About 9,000 adult patients will be enrolled at 20 emergency medical centers in Korea. Artificial intelligence algorithms are manufactured by Medical AI Co., Ltd. It is an advanced version based on the model developed and published in 2020. It had the diagnostic performance of area under the receiver operating curve 0.901 and 0.951 for acute myocardial infarction and ST-segment elevation myocardial infarction, respectively. The primary endpoint is a diagnosis of acute myocardial infarction on the day of the emergency center visit, and the secondary endpoint is a 30-day major adverse cardiac event. From March 2022, patient registration will begin at centers that have been approved by the Institutional Review Board.

This is the first prospective multicenter emergency department validation study for a 12-lead electrocardiogram artificial intelligence algorithm to diagnose acute myocardial infarction. This study will give insight into the direction of future development by verifying whether the deep learning algorithm works well for patients visiting the real-world adult emergency medical center.

Study Overview

• Status: Enrolling by invitation
• Conditions: Myocardial Infarction or Chest Pain

• Study Type: Observational
• Enrollment (Anticipated): 8814

Contacts and Locations

Study Locations

• Korea, Republic of
  • Seongnam, Korea, Republic of
    • CHA Bundang Medical Center

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

A total of 20 emergency departments in the Republic of Korea will participate in this study. These centers receive about 800,000 patients annually, and all of these hospitals are capable of their own emergency cardiovascular angiography and percutaneous coronary intervention.

Description

Inclusion Criteria:

• Adults over 18 years of age with suspected chest pain and acute myocardial infarction
• The onset or worsening of the symptom occurs within 24 hours

Exclusion Criteria:

• Out-of-hospital cardiac arrest (OHCA): patients with sustained (>20 minutes) return-of-spontaneous-circulation are not excluded
• Patients in whom acute myocardial infarction can be clearly excluded, such as pneumothorax and traumatic chest pain

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Group 1; Patients with chest pain or who are clinically suspected as acute myocardial infarction with equivalent symptoms.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnosis of acute myocardial infarction (Type 1, 2)	Accuracy metrics include area under the receiver operating characteristics curve, sensitivity, specificity, positive predictive value, and negative predictive value, along with a 95% confidence interval.	Index admission

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Major adverse cardiovascular event (MACE)	MACE is defined as death, myocardial infarction, stroke, target-vessel revascularization, or stent thrombosis occurring within 30 days of index visit. Accuracy metrics include area under the receiver operating characteristics curve, sensitivity, specificity, positive predictive value, and negative predictive value, along with a 95% confidence interval.	30-day after index admission

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
AI ECG analysis versus clinical risk score (HEART score)	HEART score is an acute coronary syndrome risk calculation tool introduced in recent guidelines, and consists of history, electrocardiogram, age, risk factor, and troponin. On a scale of 0 to 10, the higher the score, the higher the risk. Generally, a score of 7 or higher is classified as high risk. The prediction performance for the primary and secondary endpoints of the HEART score will be analyzed by comparing it with AI-ECG analysis.	Index admission, 30-day after index admission
AI ECG analysis versus clinical risk score (GRACE 2.0 score)	GRACE 2.0 score is a tool for estimating short- and long-term risk in acute coronary syndrome. A low score indicates low risk, and a high score indicates a high risk group. Based on recent guidelines, patients with acute coronary syndrome are categorized as low (≤108 GRACE score), medium (109-140 GRACE score) and high risk (>140 GRACE score). The prediction performance for the primary and secondary endpoints of the GRACE 2.0 score will be analyzed by comparing it with AI-ECG analysis.	Index admission, 30-day after index admission
AI ECG analysis versus cardiac biomarker	The performance of cardiac biomarker (hs-troponin I or T) for the diagnosis of acute myocardial infarction during index visit will be compared with AI ECG analysis diagnostic performance.	Index admission
AI ECG analysis versus physician's ECG score	The attending physician determines a score between 0 and 10 for the probability of acute myocardial infarction based on the results of the initial patient assessment and the first 12-lead ECG. A score of 0 indicates that the probability of acute myocardial infarction is 0%, and a score of 10 indicates a probability of 100%. The diagnostic performance of this score for acute myocardial infarction will be compared with AI ECG analysis.	Index admission

Collaborators and Investigators

• Sponsor: CHA University
• Collaborators: Medical AI Co., Ltd
• Investigators: Principal Investigator: KS Kim, MD, PhD, CHA University School of Medicine

Study record dates

Study Major Dates

• Study Start (Actual): March 16, 2022
• Primary Completion (Anticipated): March 1, 2023
• Study Completion (Anticipated): May 1, 2023

Study Registration Dates

• First Submitted: June 13, 2022
• First Submitted That Met QC Criteria: June 22, 2022
• First Posted (Actual): June 28, 2022

Study Record Updates

• Last Update Posted (Actual): June 28, 2022
• Last Update Submitted That Met QC Criteria: June 22, 2022
• Last Verified: April 1, 2022

More Information

Terms related to this study

• Keywords: Deep Learning
• Additional Relevant MeSH Terms: Ischemia; Pathologic Processes; Necrosis; Myocardial Ischemia; Heart Diseases; Cardiovascular Diseases; Vascular Diseases; Pain; Neurologic Manifestations; Myocardial Infarction; Infarction; Chest Pain
• Other Study ID Numbers: MAI-CRP-B0000

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No