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NCT07396792
It is a prospective, controlled, single-center, observational, non-randomized study. The study is planned to include at least 4000 patients 18 years old and older in the training sample and 1000 patients over 18 years old in the test sample (the total number of patients is at least 5000 people). Patients will be included in the study if they have undergone a full examination (laboratory, clinical and instrumental), allowing for the verification or exclusion of cardiac and cardiac-associated pathology in accordance with current recommendations. During the course of the study, the authors of the work do not interfere with the above-mentioned scope of the examination, which is carried out on patients in accordance with clinical guidelines. All patients included in the study will undergo ECG recording in standard lead I for 1 minute twice, followed by spectral analysis of the obtained data, which will be stored at the remote monitoring center of Sechenov University without being linked to the personal data of patients. A spectral analysis of the electrocardiogram will be performed using a continuous wavelet transform. The result of this study will be the identification of ECG parameters that will correlate with cardiac and cardiac-associated pathology
NCT07197736
Heart disease is the leading cause of death in the United States, and echocardiography (or "echo") is the most common way doctors look at the heart. Echo is safe, painless, and can detect major heart problems, including weak heart pumping and valve disease. Valve disease, especially aortic stenosis (narrowing) and mitral regurgitation (leakage), is common in older adults but often goes undiagnosed. While echo is the main tool for finding valve problems, it takes time, requires expert training, and results can vary between readers. Recent advances in artificial intelligence (AI), especially deep learning (DL), have shown promise in automatically analyzing heart images. However, past research hasn't fully tackled key echo techniques-like color Doppler and spectral Doppler-that are crucial for measuring how blood moves through heart valves. AI tools also face challenges in being used in everyday medical practice because of workflow issues, lack of real-world testing, and concerns about how the algorithms make decisions. At Columbia University Irving Medical Center, researchers have built a large database of heart tests over the last six years and developed AI programs to analyze echocardiograms. The current study will test whether providing AI analysis to cardiologists in real time during echo reading can make the process faster and more consistent.
NCT07516145
Valvular heart disease (VHD), caused by abnormalities in heart valves, can lead to severe complications such as heart failure and death, with approximately 220 million affected patients worldwide. The prevalence of VHD continues to grow alongside the aging global population. Transcatheter heart valve interventions have emerged as minimally invasive alternatives, offering benefits like shorter recovery times and reduced discomfort. However, current manual catheter-based techniques are complex, highly dependent on clinicians' expertise, and involve significant physical risk due to prolonged exposure to X-ray radiation and cumbersome protective gear. To address these challenges, a novel, universal intracardiac robotic system is proposed to improve precision, safety, and procedural efficiency. This system integrates a high-dexterity, load-capacity catheter instrument, a modular concentric robotic platform, and an augmented reality (AR) navigation interface. The catheter's design balances flexibility for navigating complex intracardiac paths with the rigidity needed for device deployment. The robotic platform's modular architecture enhances versatility, enabling control across various procedures and anatomical variations, while the AR system facilitates intuitive preoperative planning and real-time intraoperative guidance through multimodal image fusion. The core innovation lies in overcoming existing limitations: balancing catheter flexibility and load capacity, expanding robotic system adaptability for different valve procedures, and improving integration with imaging modalities like computed tomography, transesophageal echocardiogram, and fluoroscopy. The project aims to develop sophisticated models for instrument design, control strategies for multi-instrument coordination, and advanced navigation tools. These technological advancements are intended to elevate the clinical utility of robotic intracardiac interventions, making them safer, more efficient, and easier to adopt widely. By establishing a systematic approach for intelligent, multimodal, robotic-assisted valvular procedures, this work promises significant contributions to minimally invasive cardiology and holds substantial potential for clinical translation.
NCT07462260
Pulmonary hypertension secondary to left heart disease is associated with increased morbidity and mortality, particularly in patients with rheumatic chronic valvular heart disease, which remains highly prevalent in low- and middle-income countries. These patients often present late with severe pulmonary hypertension, limiting surgical options and worsening outcomes. Sildenafil, a phosphodiesterase-5 inhibitor, has demonstrated benefit in various forms of pulmonary hypertension; however, its role in pulmonary hypertension secondary to rheumatic valvular disease remains inadequately studied. This double-blind, placebo-controlled randomized clinical trial aims to evaluate the efficacy and safety of sildenafil as an adjunct to standard medical therapy in patients with severe pulmonary hypertension due to rheumatic chronic valvular heart disease. Eligible participants will be randomized in a 1:1 ratio to receive either sildenafil (25 mg three times daily) or placebo for six weeks. The primary outcome is change in six-minute walk distance, while secondary outcomes include changes in right ventricular function and dimensions, systolic pulmonary artery pressure, NYHA functional class, and hospitalization rates. The study seeks to generate evidence to support medical optimization and bridging therapy in this high-risk population awaiting definitive surgical intervention.
NCT07057466
This study aims to improve the early detection of undiagnosed heart disease, which causes serious health issues, hospital admissions, and high healthcare costs. Researchers are exploring how artificial intelligence (AI) can analyse routine heart tests, called electrocardiograms (ECGs), to detect heart problems. These tests can be done using both traditional ECG machines and portable, wearable devices like smartwatches, making it easier for people to monitor their heart health at home. While AI has shown promise using past data, this study will involve the collection of ECG data and subsequent testing of its accuracy in real-world settings to ensure it works well for both doctors and patients. The goal is to see if AI can identify conditions like heart muscle weakness, valve issues, and high lung pressure from the ECG data of patients. The researchers will also compare AI's detections with other blood tests commonly used to diagnose heart disease. The AI models that will be used are being tested for research and validation purposes only. They will not be used for clinical decision-making or providing information to influence diagnosis, treatment, or patient care during the study. The AI outputs are not shared with clinicians and will have no impact on the care pathway. This research will demonstrate if AI-powered ECG analysis - whether from traditional or portable devices - can provide a low-cost, non-invasive way to detect heart disease early and improve health assessments.
NCT04843371
The investigators are aiming to investigate the association between ejection fraction (EF) determined by echocardiography and signals obtained from Photoplethysmography (PPG) in the general population. The investigators are also aiming to investigate the association between blood pressure and signals obtained from PPG in the general population. Finally, the investigators are also aiming to investigate the association between signals obtained from PPG in the general population to cardioechographic findings such as, valvular heart disease, structural heart diseases, cardiomyopathies, pericardial disease etc.
NCT07379112
This study, called the EuroDafodil Registry, is being conducted to understand how safe and effective the Dafodil™ and Dafodil Neo™ Pericardial Bioprosthetic heart valves are when used in routine medical practice. The registry includes adult patients (18 years or older) who require surgical replacement of their aortic or mitral heart valve, either because their natural valve is severely diseased or because a previously implanted valve is no longer working properly. All patients in this registry will receive a Dafodil™ heart valve as part of their standard surgical treatment. No experimental procedures are involved beyond usual clinical care. This is a prospective, multi-centre registry being conducted at approximately 50 hospitals across Europe, with a planned enrollment of at least 500 patients. The study does not compare treatments; instead, it follows patients who receive the Dafodil™ valve to collect real-world information on outcomes. Doctors will monitor patients during their hospital stay and through regular follow-up visits at 1 or 3 months, 1 year, 3 years, and up to 5 years after surgery. Information collected includes survival, heart valve function, complications such as blood clots or infections, heart performance on echocardiography, and quality of life. Participation in this registry is voluntary. All patients must provide written informed consent before joining. Patient privacy will be protected: personal identifiers will not be shared, and data will be coded so individuals cannot be directly identified. The results of this registry will help doctors and health authorities better understand the long-term safety, performance, and durability of the Dafodil™ heart valves in real-world clinical use.
NCT06590467
The Abbott Structural Heart (SH) Registry is being conducted to confirm the safety and performance of Abbott's SH devices in a post-market, real-world setting. The Registry primarily involves gathering data from routine hospital practices and standard-of-care (SOC) procedures administered to patients. All devices used in these procedures must be commercially available to the participating site. A list of specific devices covered by the Registry are available upon request from the Sponsor. Data generated by the Registry will be used to meet regulatory requirements, such as the European Union Medical Device Regulations 2017/745, that require active post-market clinical follow-up (PMCF) for all commercially available devices.
NCT04936815
Non-obstetrical drivers of adverse pregnancy outcomes are underappreciated. Latent structural heart disease may account for a substantial proportion of adverse pregnancy outcomes in low-resource settings. Pregnant women presenting to B.P. Koirala Institute of Health Sciences will be prospectively included into a registry upon their visit for antenatal care. Women will be followed until 6 weeks after the time of delivery. Nested within this registry, the investigators will perform a registry-based adaptive cluster randomized crossover trial. The trial compares an experimental condition (echocardiographic screening) and a control condition (routine antenatal care).
NCT05330468
Regent China Post-Market Clinical Follow-Up (RC-PMCF): this clinical study is to confirm the safety and performance of Abbott's Regent MHV for replacement of native or prosthetic aortic valves in a Chinese population.
NCT05430568
Robotic surgery is one of the most popular minimally invasive procedures for patients with coronary artery disease or valvular diseases. Studies have shown that, as compared to conventional sternotomy, patients underwent robot-assisted bypass grafting or valvuloplasty had less post-operation pain, blood transfusion volume during operation, re-operation rate, post-operation stroke rate and length of hospitalization. However, most studies focused on the comparison of complications of different procedures, and the investigation of cardiopulmonary function recovery is still lacking. Thus our study is to compare the functional outcomes between patients that undergo different surgical procedures.
NCT07125469
This study aims to understand why there may be differences between the measurements of the aortic valve taken before and during surgery. Specifically, it will compare the valve size suggested by a CT scan (Computed Tomography) with the size measured during the operation using surgical tools. This will help determine which method is more accurate for selecting the right valve size in patients undergoing SAVR (Surgical Aortic Valve Replacement ).
NCT07099417
It is a prospective, controlled, single-center, observational, non-randomized study. The study is planned to include at least 1000 patients over 18 years old in the training sample and 200 patients over 18 years old in the test sample (the total number of patients is at least 1200 people). All patients will undergo an echocardiography examination with a comprehensive analysis of the function of the valves and other structures of the heart according to current recommendations by two independent experts. Registration of electrocardiogram will be performed immediately after echocardiography using a single lead ECG monitor (in I standard lead) for 1 minutes. The obtained data will be stored in the remote monitoring center of Sechenov University without being linked to the personal data of patients. A spectral analysis of the electrocardiogram will be performed using a continuous wavelet transform. The result of this study will be the identification of ECG parameters that will correlate with valvular heart disease.
NCT04618718
The PROTEMBO C Trial is an international, multi-center, single arm, non-inferiority study of the safety and performance of using the ProtEmbo System for cerebral embolic protection in subjects with severe native aortic valve stenosis indicated for TAVR.
NCT05654272
Cardiovascular disease is the leading cause of death worldwide. Advanced cardiovascular imaging using Magnetic Resonance Imaging (MRI) has proven to be effective in providing gold standard myocardial tissue characterization. Moreover, the intrinsic advantage of MRI's lack of exposure to ionizing radiation is particularly beneficial. At the same time, blood work can be very useful in early detection of certain cardiomyopathy, such as amyloid. However, there is a lack of agreement of on which markers are the most sensitive. This multi-study will allow us the unique opportunity to form a more comprehensive understanding for various cardiovascular diseases. Our team has developed novel cardiac MRI techniques that leverages endogenous tissue properties to reveal a milieu of deep tissue phenotypes including myocardial inflammation, fibrosis, metabolism, and microstructural defects. Among these phenotypes, myocardial microstructure has proven to be most sensitive to early myocardial tissue damage and is predictive of myocardial regeneration. In this study, the investigators aim to further study the importance of cardiac microstructure revealed by MRI in patient and healthy population and compare this novel technology with conventional clinical biomarkers.
NCT03488420
The objective of this registry is the characterization of patients with atrial fibrillation (AF) and/ or atrial flutter (AFL) with confirmed VHD who are prescribed edoxaban in a real life clinical setting.
NCT06634121
To investigate potential differences in procedural outcomes of both commercially available transcatheter edge-to-edge mitral valve repair devices in a non-selected clinical setting.
NCT06475157
This is a retrospective study to establish models for the prediction of future valvular heart diseases with artificial intelligence-enhanced electrocardiogram (ECG).
NCT06060171
An observational cohort study of patients recruited presenting with valvular heart disease. The specialized investigations will focus on myocardial remodelling and scar formation/regression and extracardiac micro- and macro-vascular sequelae of valvular heart disease (VHD). The aim is to investigate the natural history of VHD and its ensuing cardiac and extracardiac end organ effects, the impact of existing interventions and the long-term outcome. We hope to establish the underlying causative aetiology of known associated conditions (e.g. vascular dementia) and to determine if extracardiac changes may serve as early biomarkers of prognosis in VHD. Participants will attend for two visits at Barts Heart Centre or Chenies Mews Imaging Centre and will undergo a panel of tests including cross-sectional cardiac imaging, point-of-care microvascular assessment and blood tests. Patient outcome will be assessed by data linkage to hospital episode statistic (HES) data and ONS data (via NHS spine). We aim to identify determinants that will help to improve patient selection and timing of valve intervention based on advanced clinical, blood and/or imaging biomarkers.
NCT05325723
This pilot study is to investigate the feasibility of obtaining medical grade audio phonocardiogram (PCG) recordings using a smartphone-based auscultation device in the first step. The ability to determine Valvular Heart Disease (VHD) (i.e., presence or absence of cardiac murmurs) using novel handheld CAA-devices shall be analyzed and first data on a smartphone-based auscultation in a hospital setting shall be collected. In further studies, the data provided from this study can be used to investigate the potential diagnostic use of such devices in the ambulatory and stationary care scenarios.