Clinical trial NCT05435391: ROMIAE (Rule-Out Acute Myocardial Infarction Using Artificial Intelligence Electrocardiogram Analysis) Trial
Official title: 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
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Myocardial Infarction or Chest Pain
Keywords: Deep Learning
Lead sponsor: CHA University
Sponsor class: OTHER
Collaborators: name: Medical AI Co., Ltd
First posted: 2022-06-28
Enrollment: 8814
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
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.

Brief summary: 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.


Eligibility criteria: 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

Primary outcomes:
measure: Diagnosis of acute myocardial infarction (Type 1, 2)
timeFrame: Index admission
Secondary outcomes:
measure: Major adverse cardiovascular event (MACE)
timeFrame: 30-day after index admission
Other outcomes:
measure: AI ECG analysis versus clinical risk score (HEART score)
timeFrame: Index admission, 30-day after index admission
measure: AI ECG analysis versus clinical risk score (GRACE 2.0 score)
timeFrame: Index admission, 30-day after index admission
measure: AI ECG analysis versus cardiac biomarker
timeFrame: Index admission
measure: AI ECG analysis versus physician's ECG score
timeFrame: Index admission
Locations:
city: Seongnam
country: Korea, Republic of
facility: CHA Bundang Medical Center
Study officials:
affiliation: CHA University School of Medicine
name: KS Kim, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References: