Acute Myocardial InfarctionNCT07288229
The Benefits of Wearable AI in Post-Discharge Management of AMI Patients
A study testing Optimized Integrated Management Based on AI-Guided Wearable Data in people with Acute Myocardial Infarction and Heart Failure, run by RenJi Hospital.
Trial summary
Myocardial infarction (MI) remains a major threat to human health. Although interventional treatment techniques have advanced rapidly, many patients still experience major adverse cardiovascular events (MACE) and require hospital readmission after discharge. Read more about this study
- Who is it for?
- Ages 18 to 75 years
- Conditions the study is for
- Acute Myocardial Infarction, Heart Failure
- What is being tested?
- Optimized Integrated Management Based on AI-Guided Wearable Data
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 200 participants
- Where
- No sites listed yet
- Study dates
- 30 Dec 2025to 30 Dec 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 75 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Adults aged 18 to 75 years.
- Confirmed diagnosis of acute myocardial infarction (AMI), including both ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI).
- Underwent successful percutaneous coronary intervention (PCI) during index hospitalization.
- Hemodynamically stable at the time of hospital discharge.
- Willing and able to wear a smartwatch continuously for the study period.
- Compatible with the data collection application and have stable internet access.
Who cannot join
- Planned staged or elective PCI or any coronary revascularization scheduled within 3 months after discharge.
- Unable to tolerate or contraindicated for wearing metal or electronic monitoring devices.
- Pregnant or breastfeeding women.
- Residence in an area without stable network connectivity or inability to use a smartphone for data upload and communication.
- Severe comorbidities that limit 3-month survival or follow-up.
Trial locations and contacts
No sites are listed yet. Contact the study team or a site near you to ask about taking part.
About this study
Official title: The Benefits of Wearable Device-Based Artificial Intelligence in Post-Discharge Management of Patients With Acute Myocardial Infarction
Myocardial infarction (MI) remains a major threat to human health. Although interventional treatment techniques have advanced rapidly, many patients still experience major adverse cardiovascular events (MACE) and require hospital readmission after discharge. Artificial intelligence (AI) based on wearable device data has shown great potential in the diagnosis and management of cardiovascular diseases.
This study aims to explore the clinical value of wearable device-based data analysis and AI-driven risk stratification models in post-discharge management of acute myocardial infarction (AMI) patients.
Read the detailed description
This prospective, open-label, randomized controlled study aims to evaluate the clinical benefits of wearable device-based AI risk models in post-discharge management of AMI patients. A total of 200 patients who have undergone PCI and provided informed consent will be enrolled, including those with both preserved and reduced left ventricular ejection fraction (LVEF).
Participants will be randomly assigned to either the control group or the intervention group in a 1:1 ratio. All patients will be equipped with a wearable smartwatch and continuously monitored for 3 months after discharge. Data collected will include physiological signals, sleep and activity parameters. In both groups, patients will receive weekly telephone follow-ups and monthly office visits to record symptoms, medication use, and adverse events.
In the intervention group, wearable data and AI analytical results will be made available to both patients and their physicians. These insights will be discussed during follow-ups and used to support lifestyle modification, medication adjustment, and clinical decision-making. In the control group, AI data will be collected but not shared or used for clinical management during the study period.
The primary study endpoint is the time to first unplanned hospital readmission within 3 months, including readmissions due to chest pain, heart failure, arrhythmia, recurrent myocardial infarction, or death. The secondary endpoints include: Change in Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) score from baseline to 3 months; change in left ventricular ejection fraction (LVEF) measured by echocardiography between baseline and 3 months.
The investigators hypothesize that AI-assisted, wearable-based monitoring and feedback will improve early detection of adverse cardiovascular events, reduce unplanned hospitalizations, increase LVEF in patients with reduced LVEF at discharge, and enhance quality of life compared with standard post-discharge care.
- Conditions
- Acute Myocardial Infarction, Heart Failure
- Being tested
- Optimized Integrated Management Based on AI-Guided Wearable Data
- Medical subject headings
- Heart Failure
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Optimized Integrated Management Based on AI-Guided Wearable DataCombination product
The collected data will be shared with both patients and their treating physicians during follow-up visits. Based on these insights, the clinical team will offer personalized recommendations regarding medication adjustment, lifestyle modification, diet optimization, and physical activity guidance.
| Study group | Role | What they receive |
|---|---|---|
| The guideline-guided traditional management group | No intervention | As the control group, wearable data will be collected but not shared with the participant and responding physician or used for clinical management during the study period. All management in the participants is based on updated clinical guidelines. |
| The guideline-guided and wearable-assisted management group | Experimental | As the intervention group, in addition to clinical guidelines, wearable data and AI analytical results will be made available to both patients and their physicians. These insights will be discussed during follow-ups and used to support lifestyle modification, medication adjustment, and clinical decision-making. Receives: Combination Product: Optimized Integrated Management Based on AI-Guided Wearable Data |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time to First Unplanned Re-hospitalization event
The primary study endpoint is the time to first unplanned hospital readmission within 3 months, including readmissions due to chest pain, heart failure, arrhythmia, recurrent myocardial infarction, or death.
Measured: From the date of hospital discharge to 3 months post-discharge (90 days).
Secondary outcomes (2)
Change in LVEF
LVEF will be assessed by transthoracic echocardiography at discharge (baseline) and at 3 months post-discharge follow-up. The change in LVEF will be calculated as the difference between the two measurements.
Measured: At baseline and at 3 months post-discharge
Change in the score of Kansas City Cardiomyopathy Questionnaire-12
The KCCQ-12, a validated patient-reported outcome measure, will be administered during the index hospitalization (prior to discharge) and again at 3 months post-discharge follow-up.
Measured: At baseline and at 3 months post-discharge.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Dec 2025
- Study start30 Dec 2025 (estimated)
- Primary completion30 Jun 2026 (estimated)
- Study completion30 Dec 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Acute Myocardial InfarctionStudies of the same condition, open and under way.
- More trials run by RenJi HospitalThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- RenJi Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Zhiguo Zou, RenJi Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07288229
- Sponsor's protocol ID
- EARLY-MYO Wearable AI
- Status last verified
- Dec 2025
- First submitted
- 14 Nov 2025
- Last updated
- 17 Dec 2025
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 17 Dec 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Benefits of Wearable Device-Based Artificial Intelligence in Post-Discharge Management of Patients With Acute Myocardial Infarction
- ClinicalTrials.gov ID
- NCT07288229
- Acronym / sponsor ID
- EARLY-MYO Wearable AI
- Conditions
- Acute Myocardial Infarction, Heart Failure
- Study type
- Interventional
- Recruitment status
- Not yet recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- RenJi HospitalUniversity, hospital or other
- Study start
- 30 Dec 2025 (estimated)
- Primary completion
- 30 Jun 2026 (estimated)
- Study completion
- 30 Dec 2026 (estimated)
- First posted
- 17 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Myocardial infarction (MI) remains a major threat to human health. Although interventional treatment techniques have advanced rapidly, many patients still experience major adverse cardiovascular events (MACE) and require hospital readmission after discharge. Artificial intelligence (AI) based on wearable device data has shown great potential in the diagnosis and management of cardiovascular diseases.
This study aims to explore the clinical value of wearable device-based data analysis and AI-driven risk stratification models in post-discharge management of acute myocardial infarction (AMI) patients.
Detailed description
This prospective, open-label, randomized controlled study aims to evaluate the clinical benefits of wearable device-based AI risk models in post-discharge management of AMI patients. A total of 200 patients who have undergone PCI and provided informed consent will be enrolled, including those with both preserved and reduced left ventricular ejection fraction (LVEF).
Participants will be randomly assigned to either the control group or the intervention group in a 1:1 ratio. All patients will be equipped with a wearable smartwatch and continuously monitored for 3 months after discharge. Data collected will include physiological signals, sleep and activity parameters. In both groups, patients will receive weekly telephone follow-ups and monthly office visits to record symptoms, medication use, and adverse events.
In the intervention group, wearable data and AI analytical results will be made available to both patients and their physicians. These insights will be discussed during follow-ups and used to support lifestyle modification, medication adjustment, and clinical decision-making. In the control group, AI data will be collected but not shared or used for clinical management during the study period.
The primary study endpoint is the time to first unplanned hospital readmission within 3 months, including readmissions due to chest pain, heart failure, arrhythmia, recurrent myocardial infarction, or death. The secondary endpoints include: Change in Kansas City Cardiomyopathy Questionnaire-12 (KCCQ-12) score from baseline to 3 months; change in left ventricular ejection fraction (LVEF) measured by echocardiography between baseline and 3 months.
The investigators hypothesize that AI-assisted, wearable-based monitoring and feedback will improve early detection of adverse cardiovascular events, reduce unplanned hospitalizations, increase LVEF in patients with reduced LVEF at discharge, and enhance quality of life compared with standard post-discharge care.
Study design
- Primary purpose
- Treatment
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| The guideline-guided traditional management group | No intervention | –As the control group, wearable data will be collected but not shared with the participant and responding physician or used for clinical management during the study period. All management in the participants is based on updated clinical guidelines. |
| The guideline-guided and wearable-assisted management group | Experimental | Combination Product: Optimized Integrated Management Based on AI-Guided Wearable DataAs the intervention group, in addition to clinical guidelines, wearable data and AI analytical results will be made available to both patients and their physicians. These insights will be discussed during follow-ups and used to support lifestyle modification, medication adjustment, and clinical decision-making. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (6 listed)
- Adults aged 18 to 75 years.
- Confirmed diagnosis of acute myocardial infarction (AMI), including both ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI).
- Underwent successful percutaneous coronary intervention (PCI) during index hospitalization.
- Hemodynamically stable at the time of hospital discharge.
- Willing and able to wear a smartwatch continuously for the study period.
Key exclusion criteria (5 listed)
- Planned staged or elective PCI or any coronary revascularization scheduled within 3 months after discharge.
- Unable to tolerate or contraindicated for wearing metal or electronic monitoring devices.
- Pregnant or breastfeeding women.
- Residence in an area without stable network connectivity or inability to use a smartphone for data upload and communication.
- Severe comorbidities that limit 3-month survival or follow-up.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Optimized Integrated Management Based on AI-Guided Wearable DataThe collected data will be shared with both patients and their treating physicians during follow-up visits. Based on these insights, the clinical team will offer personalized recommendations regarding medication adjustment, lifestyle modification, diet optimization, and physical activity guidance. | Combination product | The guideline-guided and wearable-assisted management group |
Primary outcome
Time to First Unplanned Re-hospitalization event
Time frame: From the date of hospital discharge to 3 months post-discharge (90 days).
The primary study endpoint is the time to first unplanned hospital readmission within 3 months, including readmissions due to chest pain, heart failure, arrhythmia, recurrent myocardial infarction, or death.
2 secondary outcomes
Change in LVEF
Time frame: At baseline and at 3 months post-discharge
Change in the score of Kansas City Cardiomyopathy Questionnaire-12
Time frame: At baseline and at 3 months post-discharge.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Dec 2025.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Questions about this trial
What is this clinical trial studying?
A study testing Optimized Integrated Management Based on AI-Guided Wearable Data in people with Acute Myocardial Infarction and Heart Failure, run by RenJi Hospital.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 17 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact ZHIGUO ZOU, MD, PhD (+86 13524596108, zouzhiguo@renji.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time to First Unplanned Re-hospitalization event (time frame: From the date of hospital discharge to 3 months post-discharge (90 days).). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Dec 2025.