Active clinical trials for "Atrial Fibrillation"

Atrial Fibrillation (AF) is the most common disorder of the rhythm disturbance, especially in older adults. The incidence and prevalence of AF increases significantly with age: less than one new case per 1000/year before age 40 to 20/1000 per year after the age of eighty. AF represents 1% of emergency department (ED) visits a third of which are inaugural or recurrent. The causes are varied from cardiac (ischemic cardiac disease, valvular, high blood pressure, heart failure, pericarditis, myocarditis) to extra cardiac etiologies (pulmonary embolism, thyroid disorders, thyrotoxicosis, alcohol, shock, chest trauma, electrolyte disorders, dehydration). While the diagnosis is given quickly by reading the electrocardiogram (ECG), its management both in terms of therapeutic strategy that of choice of care pathway is complex as evidenced by the diversity of possibilities and the difference in practice. Specific recommendations have been published by the French Society of Emergency Medicine in 2015. Our study aims to investigate guidelines implementation in French ED, especially the contribution of diagnostic tests and initiated treatments. Therapeutic strategies are evaluated with a follow up at 3 months, 6 months and 1 year, reporting cardiovascular events and long-term treatment.

Mental disorders have been shown to be associated with a number of general medical conditions (also referred to as somatic or physical conditions). The investigators aim to undertake a comprehensive study of comorbidity among those with treated mental disorders, by using high-quality Danish registers to provide age- and sex-specific pairwise estimates between the ten groups of mental disorders and nine groups of general medical conditions. The investigators will examine the association between all 90 possible pairs of prior mental disorders and later GMC categories using the Danish national registers. Depending on whether individuals are diagnosed with a specific mental disorder, the investigators will estimate the risk of receiving a later diagnosis within a specific GMC category, between the start of follow-up (January 1, 2000) or at the earliest age at which a person might develop the mental disorder, whichever comes later. Follow-up will be terminated at onset of the GMC, death, emigration from Denmark, or December 31, 2016, whichever came first. Additionally for dyslipidemia, follow-up will be ended if a diagnosis of ischemic heart disease was received. A "wash-out" period will be employed in the five years before follow-up started (1995-1999), to identify and exclude prevalent cases from the analysis. Individuals with the GMC of interest before the observation period will be considered prevalent cases and excluded from the analyses (i.e. prevalent cases were "washed-out"). When estimating the risk of a specific GMC, the investigators will consider all individuals to be exposed or unexposed to the each mental disorder depending on whether a diagnosis is received before the end of follow-up. Persons will be considered unexposed to a mental disorder until the date of the first diagnosis, and exposed thereafter.

This study was designed to screen high risk patients in nursing homes for atrial fibrillation with intermittent electrocardiogram (ECG) recordings using a portable, smartphone-based, mobile ECG recording device (Kardia Mobile, AliveCor, Inc.). The investigators hypothesized that screening patients with 2 or more risk factors for atrial fibrillation would yield a higher incidence of atrial fibrillation compared to prior studies.

The study results will be used to check the hypothesis that CareLink Express remote monitoring system increases the detection rate of asymptomatic AF and allows to change timely the treatment strategy in patients at high risk of thromboembolic events, e.g. anticoagulation therapy onset, electrical cardioversion or/and PVI.

The proposed clinical study aims to validate the diagnostic performance, compared to a reference ECG, of the ECG-SW1 software and the PPG-SW1 software integrated into the HWA09 watch developed by Withings for the automatic identification of atrial fibrillation (AF).

Observational study of elderly individuals diagnosed with Non-Valvular Atrial Fibrillation and Heart Failure who are beginning oral blood thinners

Atrial fibrillation is the most frequent heart rhythm disorder. Its symptomatic forms, resistant to drug therapy, require invasive management (catheter ablation), which exposes to potentially serious complications including thromboembolic complications. Despite anticoagulant treatment, intra-atrial thrombus, which is a contraindication to catheter ablation, is detected in nearly 2 % of cases. Its diagnosis requires prior transoesophageal echocardiography, an unpleasant examination. A previous study (NCT02199080) showed that a zero ATE score, defined by no heart failure, no hypertension, no history of stroke, d-dimer < 270 ng/mL, has a negative predictive value of 100 % for the exclusion of intra-atrial thrombus. The objective of the study is to confirm the negative predictive value, sensitivity and specificity of the ATE score for the exclusion of intra-atrial thrombus.

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Although the condition itself is not life-threatening, the complications result in increased morbidity and mortality. AF is often asymptomatic and a considerable number of people suffering from AF are not aware of their condition. Unfortunately, a cerebral infarction is often the first clinical manifestation. The idea to screen subjects opportunistically for Asymptomatic Atrial Fibrillation (AAF) was infeasible until recently. However, with a recently-developed smartphone connected Mobile ECG Device (MED), this seems to be feasible after all. The main objectives are: To examine the feasibility of screening subjects of ≥65 years old for AAF. To validate the smartphone connected MED as an AAF screening instrument for application in transmural care in the Netherlands.

This observational prospective clinical investigation will evaluate the performance on an Artificial Intelligence (AI) solution interpreting ECG (electrocardiogram) collected from an Apple Watch (AI-AW) in the detection of Atrial Fibrillation (AF)

Comparison of COVID-19 disease course in hospitalized patients infected by SARS-CoV-2 in first and second waves of the novel coronavirus infection