The Benefits of Wearable AI in Post-Discharge Management of AMI Patients

NCT07288229 | Not Yet Recruiting

• 1 other identifier: EARLY-MYO Wearable AI
• Study Type: interventional
• Target: 200
• Locations: 0 countries
• Sites: N/A

Brief 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. 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.

Conditions

Acute Myocardial Infarction; Heart Failure

Outcome Measures

Primary Outcomes (1)

• 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.

  From the date of hospital discharge to 3 months post-discharge (90 days).

Secondary Outcomes (2)

• Change in LVEF

  At baseline and at 3 months post-discharge

• Change in the score of Kansas City Cardiomyopathy Questionnaire-12

  At baseline and at 3 months post-discharge.

Study Arms (2)

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.

Combination Product: Optimized Integrated Management Based on AI-Guided Wearable Data

Interventions

Optimized Integrated Management Based on AI-Guided Wearable Data COMBINATION_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.

The guideline-guided and wearable-assisted management group

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• RenJi Hospital: lead

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Central Study Contacts

ZHIGUO ZOU, MD, PhD

CONTACT

+86 13524596108; zouzhiguo@renji.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Doctor

Study Record Dates

• First Submitted: November 14, 2025
• First Posted: December 17, 2025
• Study Start: December 30, 2025
• Primary Completion (Estimated): June 30, 2026
• Study Completion (Estimated): December 30, 2026
• Last Updated: December 17, 2025

Record last verified: 2025-12