Clinical Research Directory

The Cardio-share Telemedicine Cross-sector Collaboration Model for Managing Vulnerable Patients With Heart Failure

The goal of this observational study is to explore the potential of implementing a telemedicine-based cross-sector collaboration model to manage patients with frequent admissions with decompensated heart failure. The main question(s) it aims to answer are: * Characterization of conditions that make these patients vulnerable * Description of key-elements that makes possible to manage the patients with the cardio-share model Participants are: * Patients - will be helped to use the available telemedicine tools * General Practitioners - will be offered teleconferences with cardiologists (chat and video) on demand * Community health workers (caregivers at the patient home or in elderly home) - will be guided to assist the patients to use the available telemedicine tools Researchers will compare readmission rates (primary outcome) and quality of life of patients where the cardio-share management model is successfully implemented one year before and after the implementation.

HEARTBiT: Multi-Marker Blood Test for Acute Cardiac Transplant Rejection

Heart transplantation is a life saving therapy for people with end stage heart failure. Acute rejection, a process where the immune system recognizes the transplanted heart as foreign and mounts a response against it, remains a clinical problem despite improvements in immunosuppressive drugs. Acute rejection occurs in 20-30% of patients within the first 3 months post-transplant, and is currently detected by highly invasive heart tissue biopsies that happen 12-15 times in the first year post-transplant. Replacing the biopsy with a simple blood test is of utmost value to patients and will reduce healthcare costs. The goal of our project is to develop a new blood test to monitor heart transplant rejection. Advances in biotechnology have enabled simultaneous measurement of many molecules (e.g., proteins, nucleic acids) in blood, driving the development of new diagnostics. Our team is a leader in using computational tools to combine information from numerous biological molecules and clinical data to generate "biomarker panels" that are more powerful than existing diagnostic tests. Our sophisticated analytic methods has recently derived HEARTBiT, a promising test of acute rejection comprising 9 RNA biomarkers, from the measurement of 30,000 blood molecules in 150 Canadian heart transplant patients. Our objective is to study a custom-built HEARTBiT test in a setting and on a technology that enable clinical adoption. We will evaluate the new test on 400 new patients from 5 North American transplant centres. We will also track patients' HEARTBiT scores over time to help predict future rejection, and explore use of proteins and micoRNAs to improve HEARTBiT. Our work will provide the basis for a future clinical trial. The significance of this work rests in that it will provide a tool to identify acute cardiac rejection in a fast, accurate, cost-effective and minimally invasive manner, allowing for facile long-term monitoring and therapy tailoring for heart transplant patients.

AB-1002 in Patients With Class III Heart Failure

This is a Phase 1, prospective, multi-center, open-label, sequential dose escalation study to explore the safety, feasibility, and efficacy of a single intracoronary infusion of AB-1002 in patients with NYHA Class III heart failure. Patients with non-ischemic cardiomyopathy will be enrolled until up to 17 subjects have received infusions of investigational product. All patients will be followed until 12 months post treatment intervention, and then undergo long-term follow-up via semi-structured telephone questionnaires every 6 months for an additional 24 months (+/- 30 days).

Prediction of Heart-Failure with Machine Learning

In this monocentric observational study the research question is to what extent data collected via Apple Watch can predict the heart failure status of decompensated HF patients. For this purpose, physiological data from the Apple Watch (such as single-lead electrocardiogram, SpO2, respiratory rate, step count, nighttime temperature, etc.) will be extracted and used as predictor variables to forecast outcomes like risk of decompensation and rehospitalization within the follow-up period. Since this is a data-driven study, additional data collected as part of guideline-compliant treatment will also be included.

The ROle of Compression StocKings in Heart Failure Patients

Congestive heart failure (CHF) occurs when the heart is weak and not able to effectively pump blood to the body. One of the common manifestations of CHF is fluid overload and swelling of the legs. Diuretics or "water pills" are usually the treatment for fluid overload and leg swelling; however, in some patients' diuretics are no longer effective or the effectiveness is limited due to poor kidney function. The presence of chronic swelling of the legs could potentially damage the veins; additionally, it could lead to chronic skin changes in the legs and in the worst cases to a leg ulcer. Compression stockings are used in patients with venous diseases to reduce the swelling of the legs and improve mobility and quality of life. Although, there is a theoretical risk that compression stockings might push the fluid of the legs back to the heart and lungs worsening the CHF. The purpose of this study is to determine whether the use of knee-high tight socks (tight stockings with strong compression) vs. knee-high soft socks (soft stockings with minimum compression) are effective in preventing swelling and skin changes and safe in patients with CHF. During the first visit (in-person) a routine medical test will be performed including blood tests, review of the medication doses, current weight, an ultrasound images of the veins, (venous reflux ultrasound), questions about health status and a brief physical exam. The participants will be randomly assigned to receive tight compression vs. soft compression socks. Participants will be asked to wear the socks at least 8 hours a day for 5 days a week. There will be a total of 3 virtual visit (by video or telephone); the first one after one week, then after one month and two months. During the virtual visit participants will be asked about symptoms, current medications and doses, and current weight. The participants are expected to return to the clinic after 3 months for a second in-person visit. During this visit the investigators will ask questions about participant's health, they will perform a brief physical exam of their legs, and check participants weight and medicines; also, a venous ultrasound of the legs, questions about health status will be performed. The duration of the study is 3 months.

ConTempoRary Cardiac Stimulation in Clinical practicE: lEft, BivEntriculAr, Right, and conDuction System Pacing

The goal of this observational study is to evaluate the clinical characteristics of patients undergoing permanent cardiac pacing and to compare procedural efficacy and safety of different implantation approaches in the clinical practice of the participating centres. The contribution of non-fluoroscopic anatomical and electrophysiological reconstruction systems to device implantation procedures will also be evaluated. Participants \[patients over 18 years old with an indication to receive a definitive pacemaker/intracardiac defibrillator implant\] will receive a permanent cardiac pacing implant as requested according to European Society of Cardiology (ESC) guidelines; the investigators will evaluate procedural efficacy and safety of different implantation approaches.

Artificial Intelligence and Smart Wearable Technologies for Early Detection of Acute Heart Failure

Heart failure is the major pandemic of the 21st century. The number of patients and of Heart Failure-related deaths is progressively increasing. This means a devastating economic and health organization burden. In fact, chronic heart failure patients are at high risk of death, and the course of the disease is often insidious and uncertain with a progressive deterioration requiring the need for repeated and successive hospitalizations with an ominous prognosis: with each admission for acute heart failure there is a short-term improvement, a phase characterized by a degree of stability, and then a worsening phase follows until a new need for a new hospitalization. Moreover, with each subsequent hospitalization, myocardial function progressively declines, gradually worsening the patient's quality of life until the fatal event. For these reasons, one of the major unmet needs is the identification of patients with a negative trajectory of Heart Failure. Accordingly, early identification of Heart Failure worsening is mandatory to improve patient condition and reduce Heart Failure costs, which are mainly associated with hospitalizations. Our main goal through this project is to create clinical tool for detection of early signs of chronic heart failure (CHF) worsening that will allow timely therapeutic intervention. This timely manner intervention can lead to a much better outcome for the patient, possibly reducing the need for hospitalization or lower the number of hospitalization days. The aim of this project is to develop clinical decision tool based on artificial intelligence (AI) algorithms to early detect the signs of exacerbation of chronic heart failure and predict the risk of its progression, by integrating high quality medical data obtained through a wearable device (L.I.F.E. Italia Srl's "wearable clinic" - a vest with accessories, which is a TRL 9 medical grade sensorized garment, already available on the market). Specifically, the focus will be on the early detection of CHF worsening in patients who have already been diagnosed with CHF.