About this trial
Patients with acute decompensated heart failure (HF) have a significantly high risk of death and HF re-hospitalization during the vulnerable phase post discharge. Therefore, early post-discharge management is crucial, and the cornerstone of HF treatment-particularly for HF with reduced ejection fraction (HFrEF)-is guideline-directed medical therapy (GDMT), a comprehensive pharmacotherapeutic strategy supported by robust clinical evidence. Timely titration of GDMT, especially within the first few weeks after discharge, has been shown to improve clinical outcomes, reduce readmissions, and enhance long-term prognosis. However, ensuring optimal follow-up and therapeutic adjustments remains a major challenge in real-world practice. Atrial fibrillation (AF) is a common comorbidity in patients with HF, especially in those with severe HF. The presence of AF significantly complicates the clinical course and worsens the prognosis of HF.
Advances in wearable technology have made continuous, non-invasive monitoring of vital signs, arrhythmia burden, and physical status increasingly feasible. Devices such as smartwatches and ECG belts can provide real-time physiological data, offering new opportunities for remote and proactive disease management. Despite the growing availability of such data, the complex interplay between AF and HF demands highly personalized management. Currently, there is a lack of high-quality clinical evidence on how to effectively integrate wearable device data into personalized strategies for this specific patient population.
This is an open-label, multi-center, endpoint-blinded, parallel-group randomized clinical trial supported by the American Heart Association. The primary objective is to determine whether wearable device-assisted digital consultations can optimize GDMT in patients with AF complicated by acute decompensated HF. The study plans to enroll 400 participants, who will be randomly assigned to either a wearable device-assisted intervention group or a conventional treatment control group. The primary endpoint is the change in HF GDMT score 3 months after randomization.
Apple Inc. provided funding, devices, and technical support for this study. Apple was not a sponsor of the trial and was not involved in its execution, data analysis, interpretation, or manuscript preparation.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Age ≥ 18 years
Subjects diagnosed with acute decompensated heart failure (ADHF) :1)Heart failure with reduced ejection fraction (HFrEF), defined as left ventricular ejection fraction (LVEF) ≤ 40%;2)New York Heart Association (NYHA) functional class II-IV;3)NT-proBNP > 2500 pg/mL or BNP > 600 pg/mL
Atrial fibrillation (AF) diagnosed during hospitalization (documented AF episode lasting > 30 seconds on electrocardiogram [ECG] within the past 12 months)
Disqualifiers
Intolerance to heart failure pharmacotherapy
Severe anemia, uncorrected thyroid disease
ST-segment elevation myocardial infarction (STEMI) within 3 months
Known complex congenital/secondary heart disease; infiltrative cardiomyopathy (e.g., cardiac amyloidosis, sarcoidosis, lymphoma, or endomyocardial fibrosis); myocarditis; constrictive pericarditis; cardiac tamponade; hypertrophic cardiomyopathy; stress cardiomyopathy (Takotsubo cardiomyopathy); or uncorrected primary valvular heart disease requiring surgical intervention.
Trial design
Parallel
Treatments tested in this trial
Wearable Device-Assisted Intervention
Other interventionThis intervention comprises two core components: (A) A data collecting system via smartwatch and ECG belt; and (B) A decision-support algorithms for risk stratification and medication dose adjustment based on real-time data. Participants will be instructed to wear both the Apple Watch and ECG belt for a minimum of 12-18 hours per day to monitor parameters, such as heart rhythm and respiratory rate. Participants will be prompted via the research APP to complete questionnaires for symptom, blood pressure, and body weight data. All collected data are automatically uploaded to a secure cloud-based platform. A centralized decision-support system analyzes the integrated information using a suite of predefined, multi-layered algorithms to identify patients requiring intervention. Patients will be stratified into three tiers based on integrated physiological metrics and symptom reports: Normal subgroup, Abnormal subgroup, and E-alarm subgroup.
Treatment groups
Trial outcomes
Primary outcomes
Changes in Heart Failure Guideline-directed Medical Therapy (GDMT) Score
High score favorable
Secondary outcomes
AF recurrence monitored by Apple Watch and ECG belt
AF burden monitored by ECG belt
Time to first HF hospitalization and/or cardiovascular death
Other outcomes
Change in NT-proBNP level
Change in 6-minute walk test (6MWT) result
Change in Kansas City Cardiomyopathy Questionnaire Overall Summary (KCCQ-OS)
High score favorable
Change in Minnesota Heart Failure Quality of Life Scale (MLHFQ)
Low score favorable
Locations
Sponsors and contacts
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