Active clinical trials for "Heart Failure"

Heart failure is a common cardiac condition affecting nearly 6 million Americans. Silent blood volume overload is common in patients with heart failure and is associated with increased risk of death. This study is designed to determine if adjustment of therapy based on direct measurement of blood volume will reduce risk of hospitalization and death when compared with therapy based on clinical assessment of blood volume in patients with chronic heart failure.

It is well known that 20-25% of patients hospitalized for acute myocardial infarction will develop acute heart failure during their hospitalization. Currently, the investigators have no reliable parameter for prediction of evolving acute heart failure in such a group of patients. As a result, the investigators have no way of preventing acute heart failure. Treatment of these patients only begins after appearance of clinical signs of acute heart failure. Lung impedance monitoring may be a good non-invasive parameter for prediction of evolving acute heart failure. This study will attempt to address whether preemptive lung impedence-guided therapy may prevent the development of overt acute heart failure and improve their clinical outcome.

The primary objective of this study is to evaluate whether metabolic modulation improves hemodynamics and outcome in acute heart failure

The objective of the study is to determine if the addition of peritoneal ultrafiltration to standard therapy in treatment-resistant severe heart failure patients will improve fluid balance and functional capacity such that they will spend less time in the hospital and have an improved ambulatory quality of life in comparison to patients who remain on standard therapy alone.

Out-of-hospital care of complex diseases, such as heart failure, is transitioning from an individual patient-doctor relationship to population health management strategies. As an example, at our institution, medication therapy management (MTM) pharmacists are being deployed to patients with heart failure with the intent of improving patient outcomes (through proper medication management and adherence) while reducing cost (e.g., keeping these patients out of the hospital). The success of such strategies will be dependent on the ability to effectively direct scarce resources to deliver appropriate/needed care to patients. In this prospective, pragmatic randomized and matched controlled study, the investigators hypothesize that the combination of accurate, data-driven benefit models and MTM pharmacist intervention in patients with heart failure will result in reduced 1-year mortality and hospital admissions. Using our extensive historical electronic health record data, the investigators have developed a machine learning model that, for individual patients with heart failure, predicts risk and benefit (that is, reduction in risk) associated with closing specific "care gaps". These care gaps represent standard evidence-based treatments that may be missing for an individual patient, such as beta blockers or flu shots. The investigators will use this model to define three cohorts to be studied: 1) a high risk/high benefit group to be referred for MTM pharmacist intervention, 2) a high risk/high benefit group to continue with existing standard of care (not necessarily involving MTM pharmacy), and 3) a high risk/low benefit group to be referred for MTM pharmacist intervention. Comparison of groups 1 and 2 (for which assignment is randomized) will evaluate the effectiveness of the MTM pharmacy intervention, while comparison of groups 1 and 3 will evaluate the accuracy of the benefit model prediction and importance of appropriate patient selection for treatment. The primary study outcomes will be mortality and number of hospital admissions during 1-year follow-up following study enrollment.

This study was planned as a descriptive and correlational type study to reveal the effect of perceived uncertainty by heart failure (HF) patients with reduced ejection fraction on quality of life and self-care behaviors. In this study, which aimed to reach 122 inpatients with HF, the dependent variables were quality of life and self-care behaviors, the independent variable will be perceived uncertainty. Data will be collected by Mishel Uncertainty in Illness Scale-Community Form (MUIS-C), Left Ventricular Disfunction Scale (LVD-36) and European Heart Failure Self-Care Behavior Scale (EHFSeBS). Data analysis will basically be done with Multivariate Analysis of Variance (MANOVA).

The primary goal is to build and test a previously developed and validated risk model and clinical decision support tool embedded within the electronic health record to improve risk stratification of emergency department (ED) patients with acute heart failure (AHF).

This study is to evaluate the safety and effectiveness of the Corheart 6 Left Ventricular Assist System (Corheart 6 LVAS) when used for the treatment of advanced refractory heart failure.

Heart failure represents a growing public health problem within the UK and particularly within the North West of England. A major challenge is that heart failure is currently diagnosed too late. The researchers have previously developed a risk calculator that accurately identifies individuals at risk of heart failure admission or death before they have developed heart failure. Most risk calculators are never implemented into clinical practice. The researchers will l perform a pilot study to evaluate the risk calculator within primary care in Greater Manchester.

The goal of this observational study is to learn about the factors which determine how well ventricular tachycardia (VT) is tolerated. The main questions it aims to answer are: What impact does coronary artery disease have on the ability for a patient to tolerate VT? Does treatment of coronary artery disease with stents improve the tolerability of VT? Participants who are undergoing a clinically indicated coronary angiogram or coronary angioplasty procedure will have measurements of blood pressure, coronary pressure and coronary flow made during pacing at a range of heart rates.