<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Ba Z</submitter><funding>Artificial Intelligence and Information Technology Application Fund of Fuwai Hospital and Chinese Academy of Medical Sciences</funding><funding>Noncommunicable Chronic Diseases-National Science and Technology Major Project</funding><funding>CAMS Innovation Fund for Medical Sciences</funding><funding>the National High Level Hospital Clinical Research Funding</funding><pagination>e105597</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12434780</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>15(9)</volume><pubmed_abstract>&lt;h4>Introduction&lt;/h4>Effective secondary prevention of coronary heart disease (CHD) is often hindered by limited healthcare resources and poor patient adherence. We therefore developed an artificial intelligence (AI)-enhanced CHD management platform (AIM-CHD) that (i) automatically captures follow-up data through AI-driven voice calls, optical character recognition of laboratory reports and wearable sensor streams; (ii) enables closed-loop, automated risk factor management; and (iii) dynamically personalises follow-up intensity via continuously updated risk stratification and achievement of treatment targets. This trial aims to evaluate whether AIM-CHD improves risk factor control and reduces cardiovascular events compared with usual care.&lt;h4>Methods and analysis&lt;/h4>In this prospective, single-centre, open-label, randomised controlled trial, 1100 CHD patients aged 18-85 years will be enrolled at Fuwai Hospital and randomised 1:1 to either the AIM-CHD group (n=550) or the 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 target achievement for LDL-C and blood pressure, as well as glycosylated haemoglobin level, nonsmoking status, body mass index, composite cardiovascular endpoint and medication adherence.&lt;h4>Ethics and dissemination&lt;/h4>Ethical approval was approved by the Ethics Committee of Fuwai Hospital on 4 November 2024 (2024-2422). The findings will be disseminated in peer-reviewed publications. An anonymised template of the written informed-consent form (Chinese and English versions) is available as Supplementary Material 1.&lt;h4>Trial registration number&lt;/h4>ClinicalTrial, NCT06686056.</pubmed_abstract><journal>BMJ open</journal><pubmed_title>Effectiveness of an AI-enhanced management system for coronary heart disease (AIM-CHD): rationale and design of a single-centre, open-label, randomised, parallel-controlled trial.</pubmed_title><pmcid>PMC12434780</pmcid><funding_grant_id>2024-I2M-C&amp;amp;T-B-040</funding_grant_id><funding_grant_id>2023ZD0504000</funding_grant_id><funding_grant_id>2024-GSP-GG-4</funding_grant_id><funding_grant_id>2024-AI22</funding_grant_id><funding_grant_id>2024-I2M-ZH-004</funding_grant_id><pubmed_authors>Yang L</pubmed_authors><pubmed_authors>Liu M</pubmed_authors><pubmed_authors>Ba Z</pubmed_authors><pubmed_authors>Lian X</pubmed_authors><pubmed_authors>Chen G</pubmed_authors><pubmed_authors>Yu F</pubmed_authors><pubmed_authors>Zhao W</pubmed_authors><pubmed_authors>Yuan J</pubmed_authors><pubmed_authors>Zhao S</pubmed_authors><pubmed_authors>Zhang X</pubmed_authors><pubmed_authors>Wang X</pubmed_authors><pubmed_authors>Gao X</pubmed_authors><pubmed_authors>Su Y</pubmed_authors><pubmed_authors>Wang Z</pubmed_authors><pubmed_authors>Wu Y</pubmed_authors></additional><is_claimable>false</is_claimable><name>Effectiveness of an AI-enhanced management system for coronary heart disease (AIM-CHD): rationale and design of a single-centre, open-label, randomised, parallel-controlled trial.</name><description>&lt;h4>Introduction&lt;/h4>Effective secondary prevention of coronary heart disease (CHD) is often hindered by limited healthcare resources and poor patient adherence. We therefore developed an artificial intelligence (AI)-enhanced CHD management platform (AIM-CHD) that (i) automatically captures follow-up data through AI-driven voice calls, optical character recognition of laboratory reports and wearable sensor streams; (ii) enables closed-loop, automated risk factor management; and (iii) dynamically personalises follow-up intensity via continuously updated risk stratification and achievement of treatment targets. This trial aims to evaluate whether AIM-CHD improves risk factor control and reduces cardiovascular events compared with usual care.&lt;h4>Methods and analysis&lt;/h4>In this prospective, single-centre, open-label, randomised controlled trial, 1100 CHD patients aged 18-85 years will be enrolled at Fuwai Hospital and randomised 1:1 to either the AIM-CHD group (n=550) or the 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 target achievement for LDL-C and blood pressure, as well as glycosylated haemoglobin level, nonsmoking status, body mass index, composite cardiovascular endpoint and medication adherence.&lt;h4>Ethics and dissemination&lt;/h4>Ethical approval was approved by the Ethics Committee of Fuwai Hospital on 4 November 2024 (2024-2422). The findings will be disseminated in peer-reviewed publications. An anonymised template of the written informed-consent form (Chinese and English versions) is available as Supplementary Material 1.&lt;h4>Trial registration number&lt;/h4>ClinicalTrial, NCT06686056.</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Sep</publication><modification>2026-06-01T14:03:07.086Z</modification><creation>2026-04-08T13:16:15.386Z</creation></dates><accession>S-EPMC12434780</accession><cross_references><pubmed>40953879</pubmed><doi>10.1136/bmjopen-2025-105597</doi></cross_references></HashMap>