Active clinical trials for "Hypertrophy, Left Ventricular"

Studying the causal roles of components of the renin-angiotensin-aldosterone system (including angiotensin-(1-7) (Ang-(1-7)), angiotensin-converting enzyme 2 (ACE2), Ang II, and ACE), uric acid, and klotho in pediatric hypertension and related target organ injury, including in the heart, kidneys, vasculature, and brain. Recruiting children with a new hypertension diagnosis over a 2-year period from the Hypertension and Pediatric Nephrology Clinics affiliated with Brenner Children's Hospital at Atrium Health Wake Forest Baptist and Atrium Health Levine Children's Hospital. Healthy control participants will be recruited from local general primary care practices. Collecting blood and urine samples to analyze components of the renin-angiotensin-aldosterone system (Ang-(1-7), ACE2, Ang II, ACE), uric acid, and klotho, and measuring blood pressure, heart structure and function, autonomic function, vascular function, and kidney function at baseline, year 1, and year 2. Objectives are to investigate phenotypic and treatment response variability and to causally infer if Ang-(1-7), ACE2, Ang II, ACE, uric acid, and klotho contribute to target organ injury due to hypertension.

This multicenter clinical study aims to evaluate the multi-modality echocardiographic parameters in patients with different pathological left ventricular hypertrophy (LVH) and investigate the correlation between echocardiographic parameters and different etiologies, providing an important theoretical basis for early identification and risk assessment in LVH patients.

The investigators' goal is to show that in hypertensive men and women with left ventricular hypertrophy (LVH) treatment with a mineralocorticoid receptor (MR) antagonist, versus a thiazide-like diuretic, will improve coronary microvascular function and cardiac efficiency, which will associate with improvements in LV structure and function. The investigators will achieve this through a randomized, controlled, basic experimental study involving humans (BESH).

The objective of the proposed project is to quantify the prevalence and disparities of undiagnosed left ventricular hypertrophy (LVH) in Emergency Department (ED) patients with persistently elevated asymptomatic BP, and to measure the effect of disclosure, education, and expedited referral on 3-month outpatient follow-up and treatment rates for ED patients with newly diagnosed LVH by POCUS. Additionally, investigators will create a database of annotated clips for future development of a machine learning algorithm for LVH detection on POCUS.

"Chang Gung ECG Abnormality Detection Software" is a is an artificial intelligence medical signal analysis software that detect whether patients have abnormal ECG signals of 14 diseases by static 12-lead ECG. The 14 diseases were Long QT syndrome Sinus bradycardia Sinus Tachycardia Premature atrial complexes Premature ventricular complexes Atrial Flutter, Right bundle branch block Left bundle branch block Left Ventricular hypertrophy Anterior wall Myocardial Infarction Septal wall Myocardial Infarction Lateral wall Myocardial Infarction Inferior wall Myocardial Infarction Posterior wall Myocardial Infarction The main purpose of this study is to verify whether "Chang Gung ECG Abnormality Detection Software" can correctly identify abnormal ECG signals among patients of 14 diseases. The interpretation standard is the consensus of 3 cardiologists. The results of the software analysis will be used to evaluate the performance of the primary and secondary evaluation indicators.

The study aims to test the diagnostic accuracy of native T1 mapping for the diagnosis of cardiac amyloidosis prospectively. The hypothesis is that native T1 mapping with a cut-off value of 1341ms (3 tesla CMR) in older patients with symptomatic heart failure, increased LV wall thickness and elevated cardiac biomarkers is non-inferior to the reference method to diagnose cardiac amyloidosis (CA). As secondary measure, a web-based ATTR probability estimator for the diagnosis of CA will be evaluated.

This is a non-invasive/observational study in healthy and mild HF subjects utilizing clinical and ambulatory measurements to improve detection, monitoring, and management of HF risks.

Research hypothesis - Recent studies have shown that high-dimensional descriptors of the cardiac function can be efficiently exploited to characterize targeted pathologies. In this project, the investigators hypothesize that echocardiograms possess a wealth of information that is currently under-exploited and that, combined with relevant patient data, will allow the development of robust and accurate digital tools for etiological diagnosis. Objectives - Based on key advances recently obtained in image analysis, notably by members of the consortium, the objective of this project is to develop rigorous and explainable cardiac disease prediction models from echocardiography based on the transformer paradigm (AI). The strength of this study lies in the development of a strong AI framework to model the complex interactions between high-quality image-based measurements extracted from echocardiograms and relevant patient data to automatically predict etiological diagnosis of cardiac diseases

The aim of the study is to determine the analytical characteristics of the microRNA enzymatic immunoassay (miREIA) method and to determine various relations among miRNA biomarkers and heart failure (HF) with reduced ejection fraction(HFrEF). The investigators assume that there are correlations between levels of selected miRNA and HFrEF. These correlations provide information to formulate pathophysiological conclusions, which will significantly contribute to early diagnostics and also the treatment of this disease.

This is a clinical, randomised, double-blinded study in which patients eligible for aortic valve replacement are enrolled. Patients receive infusion of either levosimendan or placebo 4 hours prior to surgery and until the end of surgery.