Smart Monitoring and Analysis System Based on Artificial Intelligence for Patients With Chronic Heart Failure Using Advanced Mini-Invasive and Wearable Medical Devices
Trial ID: NCT06909682
Status: RECRUITING
Study type: OBSERVATIONAL
Start date: 2025-08-01
Completion date: 2027-02-02
Sponsor: University of Salerno
Conditions: Chronic Heart Failure; Cardiovascular Diseases; Heart Failure With Reduced Ejection Fraction (HFrEF); Heart Failure With Preserved Ejection Fraction (HFPEF); Congestive Heart Failure Chronic
Interventions: Intervention Group (Device Group - AI-Based Remote Monitoring); Standard Clinical Follow-Up
Locations: Hospital University San Giovanni di Dio and Ruggi d'Aragona
Countries: Italy
Enrollment: 205
Age range: 19 Years - None
Sex: ALL

Summary:
The goal of this observational, multicenter study is to evaluate whether AI-driven remote monitoring using a mini-invasive wearable device can improve clinical outcomes in adult patients (≥18 years) with chronic heart failure (CHF).

The main questions it aims to answer are:

* Can continuous remote monitoring reduce hospital admissions (emergency visits and hospitalizations) by 20% compared to standard care?
* Does wearable-based remote monitoring improve functional, biochemical, and instrumental parameters in CHF patients? Researchers will compare patients using the wearable device (intervention group) to those receiving standard clinical follow-up (control group) to assess whether AI-driven monitoring leads to fewer hospitalizations, better disease management, and improved quality of life.

Participants will:

* Wear the EmbracePlus (Empatica Inc.) device continuously for six months (intervention group only).
* Have their biometric data (SpO₂, HRV, EDA, respiratory rate, temperature, sleep quality) monitored remotely.
* Receive automated alerts and teleconsultations if abnormal physiological changes are detected.
* Attend scheduled follow-up visits (remote and in-person) for clinical evaluation and treatment adjustments.

The study aims to provide real-world evidence on whether integrating wearable health technology with AI analytics can enhance CHF management and improve patient outcomes.

Eligibility criteria:
Inclusion Criteria

* Age ≥ 18 years (adults of any sex)
* Confirmed diagnosis of chronic heart failure (CHF) for at least 6 months prior to screening
* Stable on optimized heart failure therapy for at least one month before enrollment
* Any left ventricular ejection fraction (LVEF) classification, including:

  * Heart Failure with Reduced Ejection Fraction (HFrEF)
  * Heart Failure with Mid-Range Ejection Fraction (HFmrEF)
  * Heart Failure with Preserved Ejection Fraction (HFpEF)
* NYHA Functional Class I, II, or III
* History of at least one hospital admission or outpatient visit in the past 12 months requiring intravenous (IV) diuretics, vasodilators, or inotropes for CHF exacerbation
* Ability to provide written informed consent or availability of a legally authorized representative Exclusion Criteria
* NYHA Functional Class IV or anticipated heart transplant or ventricular assist device (VAD) implantation within 6 months of screening
* Severe renal impairment (eGFR \< 30 mL/min/1.73 m²) or dialysis dependence
* Terminal comorbidities (e.g., advanced cancer, end-stage pulmonary disease) significantly limiting life expectancy
* Pregnancy
* Presence of skin conditions or allergies preventing prolonged use of a wearable device
* Inability to comply with study procedures (e.g., cognitive impairment, significant psychiatric disorders)

Outcomes:
Change in Hospital Admissions with AI-Based Remote Monitoring