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NCT07603765
This prospective observational clinical study aims to evaluate the clinical utility of Pressure Recording Analytical Method (PRAM)-based minimally invasive hemodynamic monitoring in patients undergoing cardiac ablation procedures. The study will be conducted in the cardiac catheterization laboratory of Istanbul University-Cerrahpaşa Cardiology Institute and will include 27 adult patients scheduled for catheter ablation. Written informed consent will be obtained from all participants, and the study will adhere to the principles of the Declaration of Helsinki.
NCT02741180
The primary purpose of this study is to improve the quality of Magnetic Resonance Imaging in patients with heart arrhythmia. Investigators will recruit 105 patients with arrhythmia and 30 control volunteers over 3 years and will use two arrhythmia-tolerant imaging methods for diagnosis.
NCT03319160
This post-market study is a prospective observational study evaluating the efficacy and safety of the LifeVest in real-life settings.
NCT03444259
The objective of CAREBANK study is to establish definitive relationships with human cardiac samples and clinical phenotypes in patients undergoing cardiac procedures. Specifically, the investigators aim at comparing atrial phenotypes from atrial fibrillation patients and controls. The work consists of three broad categories: A) role of atrial cardiomyopathy in atrial fibrillation; B) genetic defects predisposing to atrial fibrillation; and C) the role of inflammation in atrial fibrillation.
NCT03614377
This prospective multicenter registry study aims to determine whether device-detected sleep-disordered breathing events are associated increased risk of cardiac arrhythmias or other cardiovascular outcomes.
NCT03716076
Relationship between carbetocin dose on transmural dispersion of repolarization (TDR).
NCT03662802
Identifying the correct arrhythmia at the time of a clinic event including cardiac arrest is of high priority to patients, healthcare organizations, and to public health. Recent developments in artificial intelligence and machine learning are providing new opportunities to rapidly and accurately diagnose cardiac arrhythmias and for how new mobile health and cardiac telemetry devices are used in patient care. The current investigation aims to validate a new artificial intelligence statistical approach called 'convolution neural network classifier' and its performance to different arrhythmias diagnosed on 12-lead ECGs and single-lead Holter/event monitoring. These arrhythmias include; atrial fibrillation, supraventricular tachycardia, AV-block, asystole, ventricular tachycardia and ventricular fibrillation, and will be benchmarked to the American Heart Association performance criteria (95% one-sided confidence interval of 67-92% based on arrhythmia type). In order to do so, the study approach is to create a large ECG database of de-identified raw ECG data, and to train the neural network on the ECG data in order to improve the diagnostic accuracy.
NCT03720639
This study will compare the reliability and timeliness in data transmission of the Abbott Confirm Rx™ loop recorder with the Medtronic Reveal LINQ™ loop recorder.