View clinical trials related to Cardiac Amyloidosis.
Filter by:Use samples procured from patients to improve understanding of molecular, cellular, and tissue-level processes produced by cardiac amyloidosis and therapeutic interventions.
This is an open-label, multi-center pivotal Phase 3 study to visually and quantitatively assess PET images obtained after single application of 300 MBq [18F]florbetaben and PET scanning of patients with suspected cardiac amyloidosis.
Despite rapidly advancing developments in targeted therapeutics and genetic sequencing, persistent limits in the accuracy and throughput of clinical phenotyping has led to a widening gap between the potential and the actual benefits realized by precision medicine. Recent advances in machine learning and image processing techniques have shown that machine learning models can identify features unrecognized by human experts and more precisely/accurately assess common measurements made in clinical practice. The investigators have developed an algorithm, termed EchoNet-LVH, to identify cardiac hypertrophy and identify patients who would benefit from additional screening for cardiac amyloidosis and will prospectively evaluate its accuracy in identifying patients whom would benefit from additional screening for cardiac amyloidosis.
This is a non-interventional, prospective, retrospective, non-comparative, multi-center study. In order not to interfere with patient management, the study is observational. Thus, no follow-up visit is imposed. The data collection will be limited to the data related to the management of the patients included throughout their follow-up. This study is intended for all patients with a confirmed or suspected diagnosis of cardiac amyloidosis. Three cohorts will be identified: the HEAR (Healthcare European Amyloidosis Registry)-Retrospective Cohort, the HEAR(Healthcare European Amyloidosis Registry)-Retrospective-Prospective Cohort and the HEAR (Healthcare European Amyloidosis Registry)-Prospective Cohort.
The study team will generate preliminary data on whether patients with cardiac amyloidosis feel better when their beta-blocker is stopped. To achieve this objective, 20 N-of-1 trials (on vs. off) will be conducted, and the study team will subsequently interview participants to better understand their outcomes. Each subject will participate in 2 periods lasting between up to 6 weeks each based on each patient's health profile. We will also engage stakeholders to understand the acceptability and feasibility of deprescribing N-of-1 trials. The N-of-1 trials will be iteratively refined in real-time based on feedback.
Patients with left ventricular hypertrophy are further examined according to an algorithm to check if they have a cardiac amyloidosis
The overall aim of this study is to improve our understanding of the effects of the build-up of amyloid deposits in the heart, in particular, our understanding of the risk of abnormal heart beats, or rhythms, associated with people with cardiac (heart) amyloidosis. Symptoms such as palpitations (fast, strong or irregular heart beat) and blackouts are common in people with cardiac amyloidosis, but there is not enough information on what causes this. At present, there is also not enough information on when they occur, how often they happen, and which patients are at risk of having serious, life-threatening types of abnormal heart rhythms. Some of these abnormal heart rhythms can be treated with medicine; others need electronic devices (e.g. pacemakers) implanted or inserted in the heart to prevent serious harm. The information on when is the best time to implant these life-saving devices remains limited. In this study, a small device known as an implantable loop recorder (ILR) will be implanted under the skin on the chest wall to continuously monitor participants' heart rhythm. This will help us answer some of the questions about what causes the abnormal heart rhythms, when they happen, and which patients are particularly likely to have them. Furthermore, it may help us to identify earlier, rather than later, those who are at risk of developing abnormal heart rhythms. This may lead to improvements in the care of people with cardiac amyloidosis in the future. Participants may not directly benefit from taking part in this study; however, there is a chance that the ILR may reveal heart rhythm abnormalities in some participants which might not be picked up otherwise, and so may lead to a change in their treatment.
Recently, treatment with tafamidis in patients with cardiac ATTR lead to a significant reduction in mortality. The Perugini score is commonly used on planar bone scans to differentiate cardiac ATTR from other amyloidosis or normal patients but fails to evaluate amyloid burden and patient prognosis. Although semi-quantitative methods have been suggested to evaluate the amyloid burden, there a need for quantitative methods for longitudinal assessment of the disease.
There is existing data in the literature that suggests an additional predictive value of three dimensional ECG with respect to the presence of electrical abnormalities and for an existing cardiac disease. Especially regarding patients who suffered from a myocardial infarction in the past (post MI patients), evidence has been provided for a potential association of 3D repolarisation abnormalities and incidence of sudden cardiac death (SCD). In addition, there is some vague evidence of so called 3D ECG and prediction of coronary artery disease. This 3D ECG device is using the technology of 3D ECG vector loops and is assessing the variability of these ECG vector loops in the 3-dimensional space. Based on these data, the parameters of 3D ECG are suggested to carry certain value to predict or to identify individuals already suffering from a cardiac disease or being at risk experiencing a cardiac event in the future. In this context we performed a preliminary study with 3D-ECG device in healthy volunteers evaluating the robustness of this method with respect to reproducibility, intra- and intra-observer variability which could be confirmed. We thus postulate that the 3D ECG technology might bear the potential to serve as a sufficient screening method for diagnosing cardiomyopathy in patients with an unknown heart failure etiology.
Cardiac amyloidosis is an increasingly contributor of degenerative cardiac diseases. However, its frequency remains underestimated, and diagnosis is often realized at late stages of the disease. A larger use of clinical and echographic Red Flag signals during routine echocardiographic examination may enhance the identification of early stage of the disease.