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Effectiveness of an AI-enhanced management system for coronary heart disease (AIM-CHD): rationale and design of a

Zhengqing Ba1, Sheng Zhao1, Mengyuan Liu1

  • 1Department of Cardiology, Chinese Academy of Medical Sciences and Peking Union Medical College Fuwai Hospital, Beijing, Beijing, China.

BMJ Open
|September 15, 2025
PubMed

Insights

This study evaluates an AI-enhanced platform for coronary heart disease (CHD) management, aiming to improve risk factor control and reduce cardiovascular events compared to usual care.

Area of Science:

  • Cardiology
  • Medical Informatics
  • Artificial Intelligence

Background:

  • Coronary heart disease (CHD) secondary prevention faces challenges due to limited resources and poor patient adherence.
  • An artificial intelligence (AI)-enhanced CHD management platform (AIM-CHD) was developed to address these limitations.
  • AIM-CHD automates data capture, enables closed-loop risk factor management, and personalizes follow-up intensity.

Purpose of the Study:

  • To evaluate the effectiveness of the AIM-CHD platform in improving risk factor control.
  • To assess whether AIM-CHD reduces cardiovascular events compared to usual care.
  • To investigate the impact of AI-driven interventions on CHD patient outcomes.

Main Methods:

  • A prospective, single-centre, open-label, randomized controlled trial involving 1100 CHD patients (aged 18-85 years).
  • Patients were randomized 1:1 to either the AIM-CHD group (n=550) or usual care group (n=550) for a 3-month post-discharge intervention.
  • The primary outcome is low-density lipoprotein cholesterol (LDL-C) level at 3 months; secondary outcomes include various risk factor targets and cardiovascular endpoints.

Main Results:

  • Primary outcome: Low-density lipoprotein cholesterol (LDL-C) level at 3 months.
  • Secondary outcomes: Target achievement for LDL-C, blood pressure, glycosylated haemoglobin, smoking status, body mass index, composite cardiovascular endpoint, and medication adherence.
  • Data collection methods include AI-driven voice calls, optical character recognition, and wearable sensor streams.

Conclusions:

  • The AIM-CHD platform offers a novel approach to secondary CHD prevention.
  • Automated data capture and personalized interventions may enhance risk factor management.
  • Further analysis will determine the clinical impact on cardiovascular events and patient adherence.
Abstract

Keywords:
Artificial IntelligenceCoronary heart diseaseMobile ApplicationsPreventive Health ServicesRandomized Controlled Trial

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