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Not yet recruiting NCT07521488

LLM-Based Intelligent Health Management Assistant in Life-Cycle Health Management of Cardiac Surgery Patients

No phase Interventional Coronary Artery Bypass Grafting Heart Valve Disease Aortic Aneurysm Aortic Dissection

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied
The protocol lists: LLM-Based Intelligent Health Management Assistant.
Who it may be relevant to
Registry conditions: Coronary Artery Bypass Grafting, Heart Valve Disease, Aortic Aneurysm, Aortic Dissection. Basic parameters: from 18 years · All.
What needs checking
Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place
China
Next step
Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Official title

Application of Large Language Model-Based Intelligent Health Management Assistant in Life-Cycle Health Management of Patients After Cardiac Surgery: A Prospective Randomized Controlled Study

Overview

This is a single-center, prospective, randomized, open-label, parallel-controlled clinical study to evaluate the effectiveness of a large language model (LLM)-based intelligent health management assistant in the life-cycle health management of patients after cardiac surgery. A total of 500 adult patients who undergo cardiac surgery (including coronary artery bypass grafting, heart valve surgery, great vessel surgery, congenital heart disease correction, and other cardiac procedures) at Beijing Anzhen Hospital will be randomly assigned in a 1:1 ratio to an intervention group or a control group, stratified by age (\<65 vs ≥65 years) and surgery type. The intervention group will use the LLM-based mobile health management application in addition to standard postoperative care, while the control group will receive standard postoperative care alone. The application integrates multimodal clinical data into a personalized health profile and provides surgery-type-specific postoperative management recommendations, medication adherence reminders, complication early warning, and cardiac rehabilitation guidance. The primary outcome is the composite endpoint of major adverse cardiac and cerebrovascular events (MACCE), defined as all-cause death, non-fatal myocardial infarction, non-fatal stroke, or unplanned cardiovascular reoperation/reintervention, within 12 months after randomization. Secondary outcomes include health-related quality of life (EQ-5D-5L), cardiovascular rehospitalization rate, medication adherence (MMAS-8), postoperative complication rate, and cardiac rehabilitation achievement rate. Follow-up visits are scheduled at 1, 3, 6, 9, and 12 months post-randomization.

Detailed description

Cardiac surgery, including coronary artery bypass grafting (CABG), heart valve replacement/repair, great vessel surgery, and congenital heart disease correction, is a critical treatment for severe cardiovascular diseases. Despite significant improvements in surgical safety and perioperative care, long-term postoperative health management remains challenging. Patients face complex needs including anticoagulation therapy management, cardiac rehabilitation, complication prevention, comorbidity control, and psychological well-being. Current postoperative follow-up models are limited by poor individualization across different surgery types, suboptimal anticoagulation control (particularly after mechanical valve replacement), low cardiac rehabilitation participation, high loss-to-follow-up rates, and insufficient attention to postoperative psychological distress.

Large language models (LLMs) offer new opportunities for personalized health management through their capabilities in natural language understanding, knowledge reasoning, and multimodal data integration. This study evaluates an LLM-based intelligent health management assistant, co-developed by Beijing Anzhen Hospital, Beijing Zhilan Medical Technology Co., Ltd., and Beijing Haitian Ruisheng Technology Co., Ltd., deployed as a mobile application.

This is a single-center, prospective, randomized, open-label, parallel-controlled study enrolling 500 patients discharged after cardiac surgery from Beijing Anzhen Hospital. Eligible participants are adults (≥18 years) who have undergone cardiac surgery, are clinically stable for discharge, have smartphone access, and provide informed consent. Key exclusion criteria include prolonged ICU stay (\>30 days), life expectancy less than 12 months, severe cognitive impairment without caregiver assistance, heart transplantation, concurrent interventional trial participation, or inability to complete 12-month follow-up.

Participants are randomized 1:1 to intervention or control using computer-generated block randomization (block sizes of 4 or 6) via an interactive web response system (IWRS), stratified by age (\<65 vs ≥65 years) and surgery type (CABG vs valve surgery vs great vessel surgery vs other).

The intervention group receives, in addition to standard postoperative care, the LLM-based mobile health management application with the following core functions: (1) construction of a surgery-centered structured personal health profile by uploading operative records, discharge summaries, laboratory results, imaging data, and prescriptions; (2) intelligent postoperative health assessment informed by continuously updated clinical practice guidelines covering post-cardiac surgery rehabilitation, anticoagulation management, valve surgery follow-up, and great vessel postoperative monitoring; (3) surgery-type-specific management recommendations, including secondary prevention and lifestyle interventions for CABG, anticoagulation and International Normalized Ratio (INR) monitoring reminders for valve surgery, blood pressure control and imaging follow-up reminders for great vessel surgery, and activity guidance for congenital heart disease repair; (4) medication adherence management with reminders, drug interaction alerts, and adverse reaction monitoring for anticoagulants, antiplatelets, beta-blockers, ACEI/ARBs, and statins; (5) early warning for common postoperative complications (wound infection, arrhythmia, pericardial effusion, pleural effusion) and individualized cardiac rehabilitation exercise prescriptions.

The control group receives standard postoperative clinical care and follow-up, including routine outpatient visits, standard pharmacotherapy, and conventional discharge education, without access to the application.

Follow-up assessments are conducted at 1, 3, 6, 9, and 12 months post-randomization via clinic visits or remote follow-up (telephone/video). Comprehensive questionnaire assessments are performed at 6 and 12 months. For patients requiring anticoagulation, INR values and anticoagulant dosages are recorded at each visit.

The primary outcome is the composite MACCE endpoint within 12 months, comprising all-cause death, non-fatal myocardial infarction (per the Fourth Universal Definition), non-fatal stroke (imaging-confirmed), and unplanned cardiovascular reoperation or reintervention. Secondary outcomes include change in EQ-5D-5L index and VAS scores, cardiovascular rehospitalization rate, medication adherence by MMAS-8 (with time in therapeutic INR range for anticoagulated patients), postoperative complication rates, and cardiac rehabilitation achievement rate. Exploratory outcomes include application usage patterns, user satisfaction, MACCE differences across surgery-type subgroups, and postoperative anxiety/depression scores (PHQ-9, GAD-7).

Sample size was calculated assuming a 12-month MACCE rate of 13% in the control group and 7% in the intervention group (two-sided alpha=0.05, power=80%), requiring 210 per group, inflated to 250 per group (500 total) to account for 15-20% attrition. The primary analysis uses the intention-to-treat population with Kaplan-Meier estimation and Cox proportional hazards regression adjusting for stratification factors and key baseline covariates. An interim analysis is planned after 50% enrollment completes 6-month follow-up, using the O'Brien-Fleming alpha-spending boundary. The study is self-funded, with technology partners involved only in application development and maintenance, not in study design, data analysis, or result interpretation.

Interventions

  • Other LLM-Based Intelligent Health Management Assistant
    A mobile application integrating large language model technology with individual health records. Participants upload multimodal clinical data including medical records, laboratory results, imaging data, and treatment histories to build a structured personal health profile. The assistant periodically incorporates the latest clinical practice guidelines and provides personalized lifestyle intervention recommendations, medication adherence reminders, and early warnings for potential health-critical

Primary outcome measures

  • Composite Major Adverse Cardiac and Cerebrovascular Events (MACCE) [Time frame: Within 12 months after randomization]
Secondary outcome measures (7)
  • Change in Health-Related Quality of Life Assessed by the European Quality of Life 5-Dimension 5-Level Questionnaire (EQ-5D-5L) Index Score [Time frame: Baseline and 12 months after randomization]
  • Change in Health Status Assessed by the European Quality of Life Visual Analogue Scale (EQ-VAS) [Time frame: Baseline and 12 months after randomization]
  • Cardiovascular Rehospitalization Rate [Time frame: Within 12 months after randomization]
  • Change in Medication Adherence Assessed by the 8-Item Morisky Medication Adherence Scale (MMAS-8) [Time frame: Baseline and 12 months after randomization]
  • Time in Therapeutic INR Range (TTR) Among Anticoagulated Participants [Time frame: Within 12 months after randomization]
  • Postoperative Complication Rate [Time frame: Within 12 months after randomization]
  • Cardiac Rehabilitation Achievement Rate [Time frame: 12 months after randomization]

Eligibility criteria

Inclusion criteria

  • Aged 18 years or older, any sex
  • Underwent cardiac surgery at the Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, including but not limited to: coronary artery bypass grafting (CABG), heart valve replacement or repair (aortic valve, mitral valve, or tricuspid valve surgery), great vessel surgery (aortic dissection or aortic aneurysm repair), congenital heart disease correction, or cardiac assist device implantation
  • Clinically stable after surgery and eligible for hospital discharge
  • Has access to a smartphone and is capable of independently operating a mobile application, or has a family member available to assist with operation
  • Voluntarily participates in the study, understands and signs the informed consent form, and is able to comply with the study protocol requirements

Exclusion criteria

  • Postoperative intensive care unit (ICU) stay exceeding 30 days, or presence of severe uncontrolled postoperative complications such as persistent infection or multi-organ failure
  • Life expectancy less than 12 months due to advanced malignancy or end-stage organ failure
  • Severe cognitive impairment, psychiatric disorder, or inability to understand and use a mobile application without available caregiver assistance
  • Heart transplant recipient
  • Currently participating in another interventional clinical study
  • Anticipated inability to complete 12-month follow-up

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation
Randomized
Model
Parallel assignment
Masking
Open label
Primary purpose
Health services research

Study locations

China · 1 center
  • Beijing Anzhen Hospital, Capital Medical University — Beijing

Identifiers

NCT: NCT07521488 · cFT-LLM-2026-001

Primary sources (government registries)

View this study on ClinicalTrials.gov ↗