View clinical trials related to Ischemic Heart Disease.
Filter by:Sudden cardiac death (SCD) is the final result of cardiac arrest (CA) , defined as an abrupt and unexpected loss of cardiovascular function resulting in circulatory collapse and death. Up to 50% of cardiac deaths in Europe are due to CA. The estimated mortality of CA is approximately 90%, and significant functional and/or cognitive disabilities often persist among those who survive. The advent of the implantable cardioverter-defibrillator (ICD) has revolutionized the prevention of SCD in high-risk patients with reduced left ventricular ejection fraction (LVEF<35%). However, the algorithm recommended by current guidelines based on LVEF, considered the only parameter to identify high-risk patients, cannot stratify the population and the spectrum of risk with high accuracy. Although the risk of CA is higher among patients with LVEF<35% and NYHA class>1, because of the enormity of the population size at risk (i.e., with organic heart disease and LVEF>35%), most SCD does occur in patients with LVEF>35%. Additionally, the majority of pts who receive the ICD for primary prevention of SCD will not benefit from the device (in the Sudden Cardiac Death in Heart Failure Trial published in 2005, the rate of appropriate ICD therapy was 21% at five years), and/or will experience some side effects of it. In the Israeli registry of patients who underwent ICD (n= 1729) or cardiac resynchronization therapy (n= 1326), the 12-year cumulative incidence of adverse events was 20% for inappropriate shock, 6% for device-related infection, and 17% for lead failure. Moreover, recent improvements in drug treatment for HF and myocardial revascularization have further reduced the incidence of SCD in pts with low LVEF. Finally, pts with advanced HF are unlikely to benefit from ICD therapy because of the high rates of non-arrhythmic deaths. Therefore, improved risk stratification approaches to guide the selection of pts for ICD implantation are needed, and only a multiparametric approach may aim to personalize the risk prediction of SCD across the broad spectrum of the phenotypes of HF patients. The RESPECT project has been designed to personalize the risk of SCD by integrating and interpreting information highly multidisciplinary: clinical and bio-humoral, genetics and electrocardiography, conventional and advanced cardiac imaging, and data science. The investigators hypothesized that machine learning models capable of dealing with non-linearities and complex interactions among predictors, including genetic, clinical, electrocardiographic, bio-humoral, echocardiographic, cardiac magnetic resonance (CMR), and nuclear cardiology data, would have superior accuracy in predicting the occurrence of SCD compared with the currently recommended metrics of NYHA class and LVEF by two-dimensional echocardiography and that the personalized risk prediction of SCD will translate in more cost-effective use of ICDs. In addition, the investigators will use the multiparametric predictive models to develop a cloud-computing app that will allow clinicians to predict the risk of occurrence of SCD based on specific covariate profiles of individual patients.
The aim of this observational study is to assess in patients with a documented athero-thrombotic event: coronary artery disease (CAD), cerebrovascular disease (CVD), peripheral artery disease (PAD): - the level of adherence to guideline recommendations with the assumption to improve the rate of patients at goal for cholesterol levels. - the level of adherence to guideline recommendations and the rate of patients at goal for the other relevant and modifiable risk factors for cardiovascular event recurrence.
The present study is testing spermidine treatment in elderly patients with coronary artery disease. The study is a randomized, double-blind, placebo-controlled, two-armed, parallel-group, single centre, clinical study.
This is a Phase IIA, randomized, double blind, placebo controlled, multicenter study designed to assess the safety, feasibility, and efficacy of umbilical cord derived mesenchymal stromal cells (UC MSCs), administered intravenously (IV) as a single dose or repeated doses, in patients with ischemic cardiomyopathy (ICM).
This study will be an observational registry to investigate the ability of magnetocardiography (MCG) in determining the presence of myocardial ischemia with the absence of obstructive coronary artery disease, by using an invasive reference standard coronary flow reserve (CFR) measured using thermodilution for diagnosis. Up to 200 participants in a 1:1 ratio of CMD positive to CMD negative will be enrolled. The device is a magnetocardiography (MCG) scanner named CardioFlux, which is paired with cloud processing software. A CardioFlux scan appointment shall last approximately 15 minutes in duration and include a patient questionnaire following the scan.
Coronary computed tomography angiography (CCTA) is a widely accepted initial diagnostic test for individuals suspected of having chronic coronary syndromes. However, there is limited evidence supporting its use in the acute setting. So far, no large-scale randomized trial has examined the performance of CCTA as an alternative to invasive coronary angiography (ICA) in individuals with non-ST-segment elevation myocardial infarction (NSTEACS). If CCTA were to replace ICA as a routine procedure for individuals with NSTEACS, it could reduce the risk of complications related to ICA, improve patient comfort, expedite decision-making, and reduce healthcare expenses and interhospital transfers.
This study will test a controlled investigation of the efficacy and effectiveness of iATROS digital therapy management for risk factor adjustment in patients with coronary heart disease (CHD).
The purpose of this study is to analyze the changes in right ventricular strain before and after milrinone administration in order to find out whether milrinone improves RV systolic performance in patients undergoing cardiac surgery.
This study aims to investigate the potential of using hyperpolarized [1-13C]-pyruvate magnetic resonance imaging (MRI) to assess metabolic alterations in patients with ischemic heart disease (IHD). Altered myocardial metabolism is recognized as a crucial factor in heart failure and IHD, and modulating cardiac metabolism offers a new approach to treatment. However, current diagnostic modalities use ionizing radiation and have shown limited prognostic value. Hyperpolarization through dynamic nuclear polarization (DNP) enables highly sensitive in vivo detection of metabolic processes. Hyperpolarized [1-13C]-pyruvate allows visualization of glycolysis-related metabolism, providing insights into the breakdown of glucose and its derivatives. By using this technique, the study aims to differentiate viable from non-viable myocardium in patients with IHD. The objectives include implementing hyperpolarized [1-13C]-pyruvate cardiac MRI to image metabolic flux in the human heart and investigating the potential of this method to distinguish viable from non-viable myocardium in patients with IHD. The study endpoints involve assessing metabolic flux through the pyruvate dehydrogenase complex (PDC) and analyzing ratios of different metabolites, which can indicate the extent of pyruvate oxidation and lactate production. A cross-sectional study design involving patients with CHF and ischemic heart disease will be used. Patients will undergo hyperpolarized [1-13C]-pyruvate MRI, PET imaging, late gadolinium enhancement (LGE) MRI, and cardiac magnetic resonance imaging (CMR). The study will compare [1-13C]-pyruvate MRI findings with PET results, allowing for a correlation between metabolic data and traditional imaging techniques. This innovative approach could provide valuable insights into the metabolic changes associated with ischemic heart disease
The PM-Heart algorithm (PMHeartIHD) is an in-house developed software that predict the survival prognosis for the individual patient hospitalized with ischemic heart disease (IHD) after a coronary arteriography has been performed. The software is intended to be used as a clinical decision support system i.e. the calculated survival prognosis is expected to enhance the quality of the treating physician's therapeutic considerations concerning (minor) adjustments to the patients treatment and follow-up - all within the framework of the current medical guidelines. Thus, the algorithm does not "show the physician specifically what to do", but rather ensures a better knowledgebase for the overall interpretation and choice of management of the patient.