Clinical trial NCT06995495: Wearable Devices Faciliate the Management of AMI Patients
Official title: Wearable Device for Characterizing AMI Patients After Primary PCI and Predicting the Clinical Outcomes
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Acute Myocardial Infarction
Lead sponsor: RenJi Hospital
Sponsor class: OTHER
First posted: 2025-05-29
Enrollment: 400
Sex: ALL
Minimum age (years): 18
Maximum age (years): 75
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients who are diagnosed with AMI, including ST-elevation myocardial infarction (STEMI) or non-ST-elevation myocardial infarction (NSTEMI), and admitted to cardiac Cardiac Intensive Care Unit (CICU) after primary PCI.

Brief summary: The study will explore the use of wearable technology to consistently monitor patients with acute myocardial infarction (AMI) receiving primary percutaneous coronary intervention (PCI). Parameters such as heart rate, sleep time, physical activity, and blood pressure will be collected and analyzed to characterize the patients and predict clinical outcomes.

Detailed description: The aim of this study is to explore in-hospital patient management and predict clinical outcomes in AMI patients receiving primary PCI through wearable technology (e.g., smart watches and wristband devices). The investigators expect to involve patients diagnosed with AMI, including ST-elevation myocardial infarction (STEMI) and non-ST-elevation myocardial infarction (NSTEMI), who are admitted to the cardiac Cardiac Intensive Care Unit (CICU) after primary PCI.

With written consent, eligible participants will be consistently monitored by a wearable device during the CICU stay, in addition to a conventional monitoring system. Vital signs including heart rate (beats/minute), oxygen saturation (%) blood pressure (mmHg), and other crucial parameters such as sleep patterns will be recorded. The collected data will be analyzed using AI-assisted and machine learning techniques, integrated with other clinical data to construct models that support risk stratification, guide clinical decision-making, improve the quality of nursing care, and predict long-term prognosis for these patients. Serial follow-ups (6-month, annual, and long-term) will be performed, and important information such as cardiac function assessed by echocardiography, the incidence of major adverse cardiovascular events, and life qualities will be collected for each follow-up.

Eligibility criteria: Inclusion Criteria:

* Aged 18-75 years old
* Diagnosed with STEMI or NSTEMI (ACC/AHA guidelines)
* Half male and half female
* Undergo CAG and PCI treatment;
* Written informed consent.

Exclusion Criteria:

* People under the age of 18 years old;
* Patients who are pregnant/breastfeeding;
* Patients who are allergic to the metallic or plastic components of the wearable devices

Primary outcomes:
measure: Heart Rate Pattern assessed artificial intelligence (AI)-assisted analysis
timeFrame: Throughout the full course of hospitalization, with an average of 1 week.
Secondary outcomes:
measure: Cardiac function assessed by echocardiography
timeFrame: At 1-month, 6-month and 1-year follow-ups.
measure: The event rate of coronary revascularization
timeFrame: From date of enrollment until the date of follow-ups at 1-month, 6-month and 1-year post discharge.
measure: The event rate of heart failure
timeFrame: From date of enrollment until the date of follow-ups at 1-month, 6-month and 1-year post discharge.
measure: The event rate of re-infarction
timeFrame: From date of enrollment until the date of follow-ups at 1-month, 6-month and 1-year post discharge.
measure: Cardiovascular mortality (%)
timeFrame: From date of enrollment until date of death from cardiovascular causes, or assessed up to 12 months.
Other outcomes:
Locations:
city: Shanghai
country: China
facility: Renji Hospital
Study officials:
References: