Heart Failure - NYHA II - IV

This study will compare two different methods to pace the heart to treat heart failure including: 1. The current standard method of implanting a pacing lead in a vein on the surface of the left lower chamber of the heart (left ventricle) to deliver heart failure therapy. This method is called Cardiac Resynchronization Therapy (CRT). 2. The other method is using a lead implanted in the Left Bundle Branch Area (LBBA) of your heart. This method is called Left Bundle Branch Area Pacing or LBBAP. This lead is approved by the Food and Drug Administration (FDA) to be implanted in this area of the heart, but not to provide heart failure treatment.

The goal of this observational study is to develop and validate a single-feature artificial intelligence algorithm based on data from a wearable ECG patch in patients with heart failure (HF). The main question it aims to answer is: Does the algorithm, using synchronized ECG and accelerometer signals from the patch, achieve accurate detection of heart sounds (S1, S2, and in some patients S3, S4) compared to the Eko CORE500 digital stethoscope in patients with acute exacerbation of HF? Participants with confirmed HF (NYHA class II-IV) will undergo two 2-minute sessions of simultaneous ECG patch and digital stethoscope recordings, followed by standard 12-lead ECG. Data will be used for algorithm training and validation, with the primary endpoint being the sensitivity and specificity of heart sound detection against the reference device.

PEDAL-HF is a registry-based randomized prospective multicenter study. The investigators plan to include 1000 patients who were recently admitted with acute decompensated heart failure at five tertiary heart clinics in Germany. For the randomised part, 750 patients will be randomized to care within a heart failure network or usual care. The primary endpoint of the randomized trial is change in NT-proBNP from baseline to 6 months of follow-up. All patients (randomized or not) will be followed for two years.

The goal of this clinical trial is to learn if increasing the dose of diuretics to achieve a higher urine sodium target produces better clinical results when treating patients hospitalized with acute heart failure when compared to lower urine sodium target and standard of care. The main questions it aims to answer are: 1. Does targeting a higher urine sodium goal achieve greater natriuresis and diuresis? 2. Does targeting a higher urine sodium goal reduce frequency of hospital readmissions? 3. Does targeting a higher urine sodium goal reduce hospital length of stay? Researchers will compare natriuresis-guided arms with standard of care to see if targeting higher natriuresis goals improves significantly over current practice. Participants will submit urine samples at routine intervals after being given diuretics to evaluate urine sodium concentration. If urine sodium is low then diuretic dose will be increased.

Heart Failure (HF) is a complex disease associated with the highest burden of cost to the healthcare system. The cardiopulmonary exercise test (CPET) is instrumental in determining the prognosis of patients with HF. This multicentre study will validate whether aggregate biometric data from the Apple Watch combined with demographic, cardiac, and biomarker testing can improve our ability to predict heart failure outcomes among a diverse outpatient HF population.

Heart failure is a severe heart disease, where the heart's ability to pump blood is unsatisfactory. The consequence is a high risk of hospitalization and death. Heart failure is treated with medicine which relieves symptoms and slows down the disease progression. This medical treatment needs routine adjustment, but in many cases, this adjustment is not done timely, which results in life treating conditions where the patients need acute hospitalization. Remote health monitoring of HF patients has the potential to ensure timely adjustment. However, only sensors placed inside the blood vessels of the lung, have been shown effective. The disadvantage is that the placement of the sensor requires surgery. This makes the method costly and poses a risk for the patient. The aim of the current project is to develop a small intelligent patch, which can measure the heart's function from the outside of the body. The method will be low-cost, simple to use and will not pose a risk to the patient.

This is a pivotal, global, prospective, cross-sectional, multicentric clinical investigation designed to explore a non-invasive, reliable alternative to invasive, catheter-based hemodynamic assessments, which are associated with procedural risks and limited applicability in certain participant populations.

Heart Failure (HF) and Atrial Fibrillation (AF) are two conditions that commonly occur together. Clinical guidelines consider a resting heart rate of 100-110 beats per minute (bpm) acceptable for patients with HF and AF while 72 bpm is considered the average in healthy populations. A higher resting heart rate indicates that the heart is working harder to meet bodily demands, and though it may be considered safe for patients with HF and AF to have a heart rate of 110 bpm, the investigators believe it is having a significant negative impact on patient quality of life and their ability to exercise. The current study will test exercise ability using a treadmill test before and after either a cardioversion, where the patient's heartbeat is reset using electric shocks, or a pace and ablate method, where the patient receives a pacemaker to regulate their heart rhythm and an ablation (intentional damaging) of the node that coordinates the beats within the heart. This will allow investigators to compare how the heart responds to exercise when the patient is on rate-control and anticoagulation medication therapy (before cardioversion or pace and ablate) and after the procedures. During exercise, the investigators will do a blood test that lets investigators know how efficiently the heart is working and record any symptoms experienced. The investigators will also collect information about the patient's quality of life. Using this information, the investigators hope to better understand whether the current standard of a resting heart rate of 100-110 bpm is ideal for patient quality of life.

The primary goals of this clinical trial are to evaluate the safety and efficacy of a low dose whole-heart radiotherapy with a single fraction in ten participants with advanced heart failure.

Heart failure (HF) is a chronic condition that leads to incapacity. Despite significant progress in optimizing pharmacological treatment for HF patients, the personal and social burden of this disease is still characterized by debilitating symptoms and rehospitalizations. Today, many patients with heart failure use non-pharmacological methods for managing common symptoms. Due to the increased interest in non-pharmacological methods among individuals in society, it has become essential for healthcare professionals, including nurses as part of the healthcare team, to play a role in these methods to meet the health needs of the community. One of the interventions nurses can offer for symptom management is mindfulness-based breathing exercises. In this mind-body-based practice, attention is focused on the breath, helping individuals develop awareness of their negative thoughts and emotions. The study population will consist of patients admitted to the Cardiology Department of Firat University Hospital. The sample size was determined by a power analysis, with a 0.05 margin of error, a 0.95 confidence interval, and a 0.5 effect size, representing 80% of the population, resulting in 72 patients for both the experimental and control groups. Data collection tools for the study will include a Personal Information Form, the Dyspnea-12 Scale, the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) Scale, and the Richard-Campbell Sleep Scale. SPSS (Statistical Programme for Social Sciences) software will be used to analyze the data obtained from the study. The aim of this study is to determine the effects of a 20-minute mindfulness-based breathing exercise on dyspnea, fatigue, and sleep quality in patients with heart failure.

The goal of the study is to calibrate the algorithmic model of the TakeCoeur AI device to detect early heart failure decompensation in patients with heart failure, using physiological data (clinical) actively and passively collected through connected medical devices (watch, blood pressure monitor, and scale).