View clinical trials related to Arrhythmias, Cardiac.
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Atrial fibrillation is a serious public health issue that affects over 5 million Americans (Miyazaka, Circulation 2006) in whom it may cause skipped beats, dizziness, stroke and even death. Therapy for AF is currently suboptimal, in part because AF represents several disease states of which few have been delineated or used to successfully guide management. This study seeks to clarify this delineation of AF types using machine learning (ML).
Atrial fibrillation (AF) is an enormous public health problem in the United States, affecting 2-5 million Americans and causing rapid heart beats, stroke, heart failure or death. In this project, the applicant will develop a novel framework to better understand human AF that builds on agreement between several concepts for the disease. The applicant will develop strategies to identify AF patients who will best respond to each of several therapies, to guide personalized therapy.
Patient-centered novel e-health technology and services will lay the foundation for future healthcare systems and services to support health and welfare promotion. Yet, there is a lack of ways to incorporate novel technological innovations into easy-to-use, cost-effective and low workload treatment. The detection of atrial fibrillation (AF) paroxysms and its permanent form as well as the prevention of AF-related strokes are major challenges in cardiology today. AF is often silent or asymptomatic, but the risk of ischemic stroke seems to be similar regardless of the presence or absence of symptoms. CARE-DETECT algorithm development part I will investigate following topics: 1. The usefulness and validity of bed sensor and mobile phone application in rhythm disorder capture compared to gold standard ECG-holter monitoring (Faros ECG) 2. Accuracy of AF detection from PDL data 3. Technical development of algorithms to detect arrhythmia from data collected with these novel devices 4. Development of a pre-processing tool that will evaluate the collected data and generate a preliminary filtered report of the raw data to ease clinician's workload in data handling and rhythm evaluation. CARE-DETECT clinical trial (part II) proposal provides a new concept for low workload for healthcare personnel, high diagnostic yield in silent AF detection and AF burden evaluation. CARE-DETECT protocol proposal seeks to address following issues: 1. Can a combination of actively used smartphone application and passive monitoring with bed sensor (with upstream ECG) - compared to routine care - enhance the detection of AF in patients who are at increased risk of stroke and have undergone a cardiac procedure? 2. What is the actual AF burden in paroxysmal AF patients after the detection of new-onset AF? 3. Can a direct-to-consumer telehealth with integrated cloud-based telecardiology service for medical professionals improve the efficacy of silent AF detection and what is the AF burden in patients suffering of (asymptomatic) paroxysmal AF and secondarily what is the cost-effectiveness of these new screening methods? 4. Additionally, during the hospitalization phase of the study part II PDL data will be collected in the intervention group. PDL data will be analyzed offline with the purpose to develop new methods and will not be used to monitor treatment or for diagnosis.
Temporary cardiac pacing with active-fixation leads (TPAFL) using a reusable permanent pacemaker generator has been shown to be safer than lead systems without fixation. However, TPAFL requires the off-label (non-certificated) use of Pacemaker leads and generators. It is designed a fastening system to ensure the safety and efficacy of the procedure: the KronoSafe System®. The aim of this study is to demonstrate the safety and effectiveness of the KronoSafe System® for temporary pacing in a series of patients receiving TPAFL.
The purpose of the study is to determine if the Electrocardiograms (ECGs) and symptoms data obtained from an Apple Watch and transmitted to Mayo Clinic are of sufficient quality to guide a person's care.
The CMR/CT WG of the Italian pediatric cardiology society set up a multi-center observational clinical database of repaired-TOF evaluated. This registry will enroll prospectively patients evaluated by CMR for clinical indication in most of the CHD Italian centers. Data collection will include surgical history, clinical data, imaging data, and also adverse cardiac events for a period of 6 years.
In patients expressing the SCN5A-E1784K mutation (Glu1784Lys), cardiovascular risk is difficult to define as the stratification of these patients is challenging. From our experience, major cardiovascular events (MCE) tend to occur more frequently in patients expressing overlap syndrome phenotype (Brugada syndrome and Long QT syndrome type 3)than in patients expressing a single phenotype (whether Brugada syndrome or Long QT syndrome type 3). This trials is led on the impact on Risk Stratification of Overlap Syndrome Phenotype in Patients With E1784K Mutation in SCN5A ( RISKOVER )
The project is a direct response to the identified lack of ECG diagnostic solutions dedicated to children. There are several tools for automatic ECG signal analysis in adults, but these cannot be used in the diagnosis of heart disorders among children. A digital ECG analysis technology developer, Cardiomatics, and the Medical University of Warsaw team have taken the challenge of developing an internationally innovative tool for automatic assessment, analysis, and interpretation of electrocardiographic signals in pediatric patients. The developed tool will allow cardiac arrhythmias in children to be assessed more effectively and minimize the time needed for cardiologists to evaluate data received from the Holter monitor due to the use of algorithms, which are based on artificial intelligence.
Ablation of consecutive atrial tachycardia (AT) after ablation of atrial fibrillation (AF) or cardiac surgery can be challenging due to complex substrate and AT mechanisms. A substantial portion of patients is known to show various tachycardias and recurrences occur in a noticeable number of cases. With the availability of novel ultra-high-density mapping techniques characterization and understanding of AT mechanisms and underlying substrate can be improved. Aim of this prospective, multi-center, randomized study is to compare a standard AT ablation approach versus minimalized ablation of the clinical AT in regards to arrhythmia free survival.