An interventional study of Optimized Integrated Management Based on AI-Guided Wearable Data in Acute Myocardial Infarction and Heart Failure, sponsored by RenJi Hospital. Not yet recruiting. Open to participants aged 18 Years to 75 Years. Per ClinicalTrials.gov, last updated 2025-12-17.
Sponsored by RenJi Hospital · Not applicable, Interventional, and Treatment
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.
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.
5,697 studies on the registry are indexed under Heart Failure; 1,219 are open to participants now.
This study's planned enrollment of 200 is above the median of 72 across 3,733 interventional studies indexed under Heart Failure.
Browse Heart Failure studies →RenJi Hospital is the lead sponsor of 535 studies on the registry; 244 are open to participants now.
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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.
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
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.
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.
Time frame: From the date of hospital discharge to 3 months post-discharge (90 days).
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.
Time frame: 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.
Time frame: At baseline and at 3 months post-discharge.
No study locations are listed for this record.
This study is not yet recruiting, as verified in Dec 2025. You cannot join it, but the record below documents what was studied.
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