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Evaluating AI-Gatekeeper Software in Coronary Artery Stenosis Screening: A Multicenter RCT (AIGatekeeper)

I

INFINITT Healthcare

Status

Enrolling

Conditions

Coronary Artery Disease
Diagnosis

Treatments

Diagnostic Test: Assisted by the AI-Gatekeeper software group

Study type

Interventional

Funder types

Industry
Other

Identifiers

NCT06178900
AI-Gatekeeper

Details and patient eligibility

About

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).

Full 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.

Enrollment

450 estimated patients

Sex

All

Ages

19 to 80 years old

Volunteers

No Healthy Volunteers

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

Trial design

Primary purpose

Diagnostic

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

None (Open label)

450 participants in 2 patient groups

Assisted by the AI-Gatekeeper software group
Experimental group
Description:
After a baseline examination (chest X-ray, electrocardiogram, echocardiogram, clinical risk factors and blood test), the AI-Gatekeeper software will be used to guide clinical care.
Treatment:
Diagnostic Test: Assisted by the AI-Gatekeeper software group
Usual care group
No Intervention group
Description:
The usual care group will be managed based on established guidelines.

Trial contacts and locations

5

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Central trial contact

Hyung-Bok Park, MD, PhD; SungA Bae, MD, PhD

Data sourced from clinicaltrials.gov

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