Clinical trial NCT06178900: Evaluating AI-Gatekeeper Software in Coronary Artery Stenosis Screening: a Multicenter RCT
Official title: A Prospective, Multicenter, Open-label, Randomized, Comparative Clinical Trial to Verify the Effectiveness, Safety, and Cost-effectiveness of AI-Gatekeeper, a Multimodal AI Software, in Assisting the Screening of Coronary Artery Stenosis
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Coronary Artery Disease
Diagnosis
Keywords: Coronary Artery Disease
Artificial Intelligence
Gatekeeper
Lead sponsor: INFINITT Healthcare
Sponsor class: INDUSTRY
Collaborators: name: Korea Medical Device Development Fund
First posted: 2023-12-21
Enrollment: 450
Sex: ALL
Minimum age (years): 19
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: DIAGNOSTIC

Brief summary: The purpose of this study is to determine the efficacy, safety, and cost-effectiveness of AI-Gatekeeper software to assist clinicians in the diagnosis of coronary artery disease by predicting coronary artery stenosis (≥50%) from a multimodal AI technology that integrates clinical risk factors and baseline blood tests, including chest X-ray, electrocardiogram, and echocardiogram, in patients with suspected coronary artery disease (coronary stenosis).

Detailed description: Coronary artery disease (CAD) is a leading cause of global mortality, accounting for over 50% of heart disease-related deaths. Initial evaluations for CAD typically involve chest X-rays, electrocardiograms (ECG), risk factor assessments, and basic blood tests. However, these primary tests can't conclusively diagnose CAD. When CAD is suspected, coronary CTA (CCTA) or invasive coronary angiography (ICA) is performed, determining the need for procedures like stenting or revascularization.

Interestingly, over 50% of patients undergoing CCTA or ICA don't require treatment, as CAD is either absent or not severe enough. This leads to unnecessary procedures and significant healthcare costs. For instance, in the U.S., the cost of unnecessary ICAs reaches billions annually, with similar trends in South Korea.

AI-Gatekeeper software assists clinicians in diagnosing coronary artery disease by predicting coronary artery stenosis (≥50%) using multimodal AI technology. It integrates clinical risk factors and baseline blood tests, including chest X-ray, electrocardiogram, and echocardiogram, in patients with suspected coronary artery disease The purpose of this study is to determine the efficacy, safety, and cost-effectiveness of the AI-Gatekeeper software in a prospective, multicenter, randomized control trial.

Eligibility criteria: Inclusion Criteria:

* A patient with symptoms such as chest pain suggestive of coronary artery disease, who underwent routine evaluations including blood tests, electrocardiogram, chest X-ray, and echocardiography
* Low to Intermediate risk of pretest probabilities of obstructive CAD
* Voluntarily agreed to participate in this clinical trial and signed the written consent form

Exclusion Criteria:

* Acute chest pain (in patients who have not been ruled out for ACS)
* Previously diagnosed and treated coronary artery disease (myocardial infarction, PCI, CABG)
* Patients with a life expectancy of less than 2 years due to conditions other than heart disease
* Those who have not consented to the protocol
* Participated in a drug or medical device clinical trial within the last 3 months
* Pregnant or lactating women
* Allergic to iodine preparations
* Serum creatine level greater than 1.5 mg/dL or eGFR less than 30 mL/min
* Baseline irregular and uncontrolled heart rhythm
* Heart rate greater than 100 beats/minute
* Systolic blood pressure of 90 mm Hg or less
* Contraindications to beta blockers or nitroglycerin
* Patients with complex congenital heart disease
* Body mass index greater than or equal to 35

Primary outcomes:
measure: MACE (major adverse cardiovascular events)
timeFrame: 24 weeks
measure: Unnecessary utilization of advanced cardiac imaging
timeFrame: 24 weeks
Secondary outcomes:
measure: Comparison of total healthcare costs
timeFrame: 24 weeks
measure: Proportion of subjects classified as positive by the AI-Gatekeeper model analysis who are diagnosed with coronary artery stenosis (≥50%)
timeFrame: 24 weeks
measure: Proportion of subjects identified as negative by the AI-Gatekeeper model who are confirmed to have non-significant stenosis (<50%)
timeFrame: 24 weeks
measure: Comparison of changes in angina symptom score
timeFrame: 24 weeks
Other outcomes:
Locations:
city: Bucheon
country: Korea, Republic of
facility: Soonchunhyang University Bucheon Hospital
state: Gyeonggi-do
city: Seongnam
country: Korea, Republic of
facility: Seoul National University Bundang Hospital
state: Gyeonggi-do
city: Yongin
country: Korea, Republic of
facility: Yongin Severance Hospitall, Yonsei University College of Medicine
state: Gyeonggi-do
city: Incheon
country: Korea, Republic of
facility: Catholic Kwandong University International St. Mary's Hospital
city: Seoul
country: Korea, Republic of
facility: Hanyang University Seoul Hospital
Study officials:
affiliation: Yongin Severance Hospital, Yonsei University College of Medicine
name: In Hyun Jung, MD, PhD
role: PRINCIPAL_INVESTIGATOR
References:
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