View clinical trials related to Ventricular Dysfunction, Left.
Filter by:This is a single-center, prospective, observational study to explore the clinical features and risk factors of impaired cardiac function detected by two-dimensional speckle tracking echocardiography in patients with diabetes mellitus. The risk factors include traditional cardiovascular risk factors, bone metabolism hormones, sex hormones, adrenal and pituitary hormones, and novel serum biomarkers.
Cardiac resynchronization therapy (CRT) via biventricular (BiV) pacing significantly reduces morbidity and mortality in patients with left bundle branch block (LBBB), impaired LV function and heart failure in spite of optimal medical treatment. CRT positive effects are based on the existence of an electromechanical dyssynchrony induced by the abnormal activation sequence associated with the presence of a left bundle branch block (LBBB), which is thought to be responsible for a negative LV remodeling leading to LVEF impairment and heart failure progression. However, one third of patients undergoing CRT are considered non responders due to different reasons. Recently, left bundle branch area pacing (LBBAP) has emerged as a novel physiological pacing modality aiming for conduction system recruitment in patients with normal or impaired atrioventricular conduction, including patients with LBBB. LBBAP achieves LBBB correction in up to 85% of the cases and thus could be a promising pacing modality for CRT candidates.
The proposed mechanistic trial will test the effect of dietary sodium reduction on cardiac and vascular structure and function in those with elevated blood pressure or hypertension. Findings from this study will fill the knowledge gap on the underlying mechanisms of dietary sodium intake on cardiovascular disease risk in addition to blood pressure and could provide further evidence on sodium reduction for the prevention of cardiovascular disease.
Left ventricular ejection fraction (LVEF) is one of the strongest predictors of mortality and morbidity in patients with acute coronary syndrome (ACS). Transthoracic echocardiography (TTE) remains the gold standard for LVEF measurement. Currently, LVEF can be estimated at the time of the coronary angiogram but requires a ventriculography. This latter is performed at the price of an increased amount of contrast media injected and puts the patients at risk for mechanical complications, ventricular arrhythmia or atrio-ventricular blocks. Artificial intelligence (AI) has previously been shown to be an accurate method for determining LVEF using different data sources. Fur the purpose of this study, we aim at validating prospectively an AI algorithm, called CathEF, for the prediction of real-time LVEF (AI-LVEF) compared to TTE-LVEF and ventriculography in patients undergoing coronary angiogram for ACS.
Heart Valve Disease and Heart failure contribute to 25% of hospital emergency admissions while heart failure alone has become one of the most common causes for hospitalisation in people over the age of 65. The burden of disease is likely to be high in a multi-ethnic community but there is a paucity of data. Management of heart valve disease requires appropriate surveillance and timely surgery. Similarly heart failure management requires treatment with medications aimed at slowing prevention of symptoms and preventing premature death. The NHS long term plan priorities early detection and treatment of valve disease and heart failure in order to reduce the burden on emergency services and improve the health of the population. Diagnosis is made using cardiac ultrasound, however staff with the required skills-set are critically limited in the community. The investigators will train non-expert staff within primary care to perform abbreviated cardiac ultrasound to detect heart valve disease or heart failure. This will be opportunistic scanning to reduce healthcare footfall. All scans will be reviewed by an expert and the investigators will use the anonymised data to develop machine learning tools to begin working with academic partners to develop tools that can improve the reliability of diagnosis from ultrasound. The investigators hope to identify the proportion with the above conditions in a multi-ethnic community and assess the feasibility of developing a program where staff can be trained for community detection, streamlined referrals can be created bridging the gap between primary and secondary care, reducing hospital emergency admissions, while ensuring patients are managed optimally.
The C-MIC System is a medical device used to treat heart failure per the intended purpose which is to treat heart failure by applying an electrical micro-current to the heart. Target patients for this study are patients who have received the device in a prior study.
A randomized, controlled, double-blinded clinical trial evaluating the effect of the administration of a Maltodextrin solution on cardiac function in patients presenting for coronary artery bypass grafting surgery with a reduced left ventricular ejection fraction.
This is a randomized controlled trial (RCT) to test a novel artificial intelligence (AI)-enabled electrocardiogram (ECG)-based screening tool for improving the diagnosis and management of left ventricular systolic dysfunction.
This clinical study will utilize a new cell therapy approach (Human embryonic stem cells derived cardiomyocytes or hESC-CMs) to improve survival and cardiac function in patients with chronic left ventricular dysfunction secondary to MI (Myocardial Infarction).
300 STIMI patients with LV systolic dysfunction will be divided into two equal groups (Group I (Study arm, n=150); will receive dapagliflozin plus conventional therapy and group (II) Control arm (n=150); will receive conventional therapy only to detect an improvement in the LVEF by ≥ 5