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NCT Number: NCT07031531

Effectiveness of an AI-Enabled Stratified Management System for Premature Coronary Artery Disease

The goal of this clinical trial is to learn if an AI-enabled stratified management system (SMART-CHD) can improve post-discharge outcomes in adults aged 18-45 with premature coronary artery disease. The main questions it aims to answer are:

1. Does SMART-CHD reduce the combined rate of all-cause death, myocardial infarction, stroke and rehospitalization within 12 months? 2. Does SMART-CHD achieve better control of modifiable risk factors compared with usual care?

Researchers will compare SMART-CHD to standard discharge management (verbal and printed instructions on medications, follow-up timelines and lifestyle advice) to see if the AI-driven platform leads to fewer adverse events and improved risk-factor profiles.

Participants will:

1. Install and use the SMART-CHD mobile app after a 10-minute structured orientation session with supervised simulations. 2. Complete regular in-app surveys on lifestyle behaviors, laboratory/imaging results and clinical events (with OCR-powered LLM assistance). 3. Wear paired sensors for continuous monitoring of blood pressure, heart rate and other physiologic metrics. 4. Receive automated EHR data harvesting, AI-driven voice-call reminders, and real-time CRC support via a dedicated WeChat group. 5. Follow personalized, guideline-based risk-factor recommendations (diet, exercise, sleep, weight, smoking, alcohol, hypertension, dyslipidemia, diabetes).

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Key information

Conditions

Premature Coronary Heart Disease

Age range

18 year–45 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

The First Affiliated Hospital of University of Science and Technology of China, Hefei, Anhui, China

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Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients with coronary heart disease aged 18-45 years;
  • The patient or a close family member is capable of using a smartphone and mobile application (App);
  • Willing to participate in the study and able to provide written informed consent.

Exclusion criteria

  • Severe cognitive impairment;
  • Advanced-stage malignancy;
  • Life expectancy less than 12 months;
  • Severe multi-organ failure;
  • Refusal to provide written informed consent.

Treatment and study plan

AI-Enabled Stratified Management System

Combination Product

After discharge, participants install SMART-CHD, sync their EHR data, and complete a 10-minute orientation. They then use the app's OCR-assisted surveys to report lifestyle, lab, and event data, while paired wearables stream continuous vitals. AI voice calls and a CRC-managed WeChat group deliver reminders and support. The app's embedded predictive models stratify them into risk tiers and generate tier-specific follow-up schedules. Personalized lifestyle modification guidance, dietary plans, and medication adjustment recommendations are generated by the platform's module. Automated alerts and teleconsultation options are triggered upon detection of high-risk signs or abnormal results, ensuring timely clinical intervention and enhanced secondary prevention.

Usual post-discharge care

Combination Product

Usual discharge protocol comprising verbal and printed discharge instructions addressing medication schedules, follow-up timelines, and lifestyle optimization strategies.

Primary outcomes

  1. Cardiovascular Composite Endpoint Events

    Time frame: Assessed at 12 months post-discharge

    A composite of all-cause death, myocardial infarction, stroke, and unplanned cardiovascular-related rehospitalization.

Secondary outcomes

  1. Individual components of cardiac events

    Time frame: Assessed at 12 months post-discharge

    All-cause death, myocardial infarction, stroke, and unplanned cardiovascular-related rehospitalization

  2. LDL-C level

    Time frame: Assessed at 12 months post-discharge

    Low-density lipoprotein cholesterol level. Unit of Measure: mmol/L.

  3. LDL-C Goal Attainment

    Time frame: Assessed at 12 months post-discharge

    Achieving LDL-C < 1.8 mmol/L.

  4. Blood pressure level

    Time frame: Assessed at 12 months post-discharge

    Systolic blood pressure and Diastolic blood pressure. Unit of Measure: mmHg.

  5. Blood pressure goal attainment

    Time frame: Assessed at 12 months post-discharge

    Achieving target BP <130/80 mmHg.

  6. Hemoglobin A1c level

    Time frame: Assessed at 12 months post-discharge

    Glycated hemoglobin (HbA1c). Unit of Measure: Percentage (%).

  7. Smoking

    Time frame: Assessed at 12 months post-discharge

    Self-reported current smoking status. Unit of Measure: Number and percentage of current smokers

  8. Medication adherence to antiplatelet agents and statins

    Time frame: Assessed at 12 months post-discharge

    Adherence is defined as self-reported use of the medication for more than 80% of the time during the past month

Study contacts

Contact information is provided by the study sponsor or research team.

Gao Prof. Gao, MD, PhD

CONTACT

[email protected]

010-88322413

Sponsors and collaborators

Lead sponsor

China National Center for Cardiovascular Diseases

Other Gov

Registry information

Official study title

Effectiveness of an AI-Enabled Stratified Management System for Premature Coronary Artery Disease (SMART-CHD): A Prospective, Multicenter, Open-Label, Randomized Controlled Trial

Acronym: SMART-CHD

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Jun 22, 2025
Registry last updated
Sep 23, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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