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2,408 results for “Atrial fibrillation”
Evaluation of PWI Assisted by Marshall Ethanolization in Ablation of Persistent Atrial Fibrillation
ClinicalTrials.gov study NCT06363604. IPD Sharing: UNDECIDED. Countries: 1. Publications: 19.
International Registry on Cardioversion of Atrial Fibrillation (MK-6621-051)
ClinicalTrials.gov study NCT01119716. IPD Sharing: Not stated. Countries: 0. Publications: 2.
Effect of Prophylaxy of Amiodarone and Propranolol and Amiodarone With Propranolol in Prevention of Atrial Fibrillation Post Coronary Artery Bypass Graft
ClinicalTrials.gov study NCT00654290. IPD Sharing: Not stated. Countries: 1. Publications: 1.
PulseSelect Based Pulmonary Vein Isolation and Ablation in Patients With Atrial Fibrillation
ClinicalTrials.gov study NCT07035288. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
High Power vs Standard Power RF Ablation of Atrial Fibrillation in Conscious Patients
ClinicalTrials.gov study NCT04250181. IPD Sharing: UNDECIDED. Countries: 1. Publications: 6.
STAR-AF:Substrate Versus Trigger Ablation for Reduction of Atrial Fibrillation Trial
ClinicalTrials.gov study NCT00367757. IPD Sharing: Not stated. Countries: 4. Publications: 1.
Dapagliflozin to Prevent Atrial Fibrillation Recurrence After Transcatheter Pulmonary Venous Isolation.
ClinicalTrials.gov study NCT04780438. IPD Sharing: UNDECIDED. Countries: 1. Publications: 17.
Left Atrium Reservoir Function Modulation in Patients With Atrial Fibrillation: Digoxin Versus Beta Blocker
ClinicalTrials.gov study NCT05540600. IPD Sharing: NO. Countries: 1. Publications: 5.
Phase III Tolerance and Efficacy Study of RSD1235 in Patients With Atrial Fibrillation
ClinicalTrials.gov study NCT00468767. IPD Sharing: Not stated. Countries: 4. Publications: 2.
Prospective Validation Study of AI-based Prediction Algorithm for the Prediction of Paroxysmal Atrial Fibrillation
ClinicalTrials.gov study NCT05725187. IPD Sharing: NO. Countries: 1. Publications: 5.
Hybrid Ablation of Atrial Fibrillation in Heart Failure
ClinicalTrials.gov study NCT05411614. IPD Sharing: NO. Countries: 1. Publications: 0.
Prevalence of Primary Aldosteronism in Hypertensive Patients Presenting With Atrial Flutter or Fibrillation
ClinicalTrials.gov study NCT01267747. IPD Sharing: Not stated. Countries: 1. Publications: 13.
Data from: Impact of microRNA expression in human atrial tissue in patients with atrial fibrillation undergoing cardiac surgery
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Direct oral anticoagulants in atrial fibrillation patients with concomitant hyperthyroidism
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Data from: Development and validation of a score to detect paroxysmal atrial fibrillation after stroke
Objective: Prolonged monitoring times (72h) are recommended to detect paroxysmal atrial fibrillation (pAF) after ischemic stroke, but not yet clinical practice; therefore, an individual patient selection for prolonged ECG monitoring might increase the diagnostic yield of pAF in a resource-saving manner. Methods: We used individual patient data from three prospective studies (ntotal=1556) performing prolonged Holter ECG monitoring (at least 72h) and centralized data evaluation after TIA or stroke in patients with sinus rhythm. Based on the TRIPOD guideline, a clinical score was developed on one cohort, internally validated by bootstrapping and externally validated on two other studies. Results: pAF was detected in 77 (4.9%) of 1556 patients during 72h-Holter monitoring. After logistic regression analysis with variable selection, age and the qualifying stroke event (categorised as stroke severity with NIH-SS≤5 (OR 2.4 vs. TIA; 95%CI0.8-6.9,p=0.112) or stroke with NIH-SS>5 (OR 7.2 vs. TIA; 95%CI 2.4-21.8,p<0.001)) were found to be predictive for the detection of pAF within 72h-Holter monitoring and included in the final score (Age: 0.76 points/year, Stroke Severity NIH-SS≤5 = 9 points, NIH-SS>5 = 21 points; to Find AF, AS5F). The high risk group defined by AS5F is characterized by a predicted risk between 5.2% and 40.8% for detection of pAF with a number needed to screen of 3 for the highest observed AS5F points within the study population. Regarding the low number of outcomes before generalization of AS5F the results need replication. Conclusion: The AS5F score can select patients for prolonged ECG monitoring after ischemic stroke to detect pAF.
Data from: The association between alcohol consumption, cardiac biomarkers, left atrial size and re-ablation in patients with atrial fibrillation referred for catheter ablation
Background: Information on alcohol consumption in patients undergoing radiofrequency ablation (RFA) of atrial fibrillation (AF) is often limited by the reliance on self-reports. The aim of this study was to describe the long-term alcohol consumption, measured as ethyl glucuronide in hair (hEtG), in patients undergoing RFA due to AF, and to examine potential associations with cardiac biomarkers, left atrial size and re-ablation within one year after the initial RFA. Methods: The amount of hEtG was measured in patients referred for RFA, and a cut-off of 7 pg/mg was used. N-terminal pro B-type natriuretic peptide (NT-proBNP) and the mid-regional fragment of pro atrial natriuretic peptide (MR-proANP) were examined and maximum left atrium volume index (LAVI) was measured. The number of re-ablations was examined up to one year after the initial RFA. Analyses were stratified by gender, and adjusted for age, systolic blood pressure, body mass index, presence of heart failure and heart rhythm for analyses regarding NT-proBNP, MR-proANP and LAVI and heart rhythm being replaced by type of AF for analyses regarding re-ablation. Results: In total, 192 patients were included in the study. Median (25th – 75th percentile) NT-proBNP in men with hEtG ≥ 7 vs. < 7 pg/mg was 250 (96-695) vs. 130 (49-346) pg/ml (p = 0.010), and in women it was 230 (125-480) vs. 230 (125-910) pg/ml (p = 0.810). Median MR-proANP in men with hEtG ≥ 7 vs. < 7 pg/mg was 142 (100-224) vs. 117 (83-179) pmol/l (p=0.120) and in women it was 139 (112-206) vs. 153 (93-249) pmol/l (p = 0.965). The median of maximum LAVI was 30.1 (26.7-33.9) vs. 25.8 (21.4-32.0) ml/m2 (p = 0.017) in men, and 25.0 (18.9-29.6) vs. 25.7 (21.7-34.6) ml/m2 (p =0.438) in women, with hEtG ≥ 7 vs. < 7 pg/ml, respectively. Adjusted analyses showed similar results, except for MR-proANP turning out significant in men with hEtG ≥ 7 vs. < 7 pg/mg (p=0.047). The odds ratio of having a re-ablation was 3.5 (95% CI 1.3-9.6, p = 0.017) in men with hEtG ≥ 7 vs. < 7 pg/mg, while there was no significant difference in women. Conclusions: In male patients with AF and hEtG ≥ 7 pg/mg, NT-proBNP and MR-proANP were higher, LA volumes larger, and there was a higher rate of re-ablations, as compared to men with hEtG < 7 pg/mg. This implies that men with an alcohol consumption corresponding to an hEtG-value ≥ 7, have a higher risk for LA remodelling that could potentially lead to a deterioration of the AF situation.
Left atrial polygenic scores for "Deep Learning of Left Atrial Structure and Function Provides Link to Atrial Fibrillation Risk"
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EARLY WARNING OF ATRIAL FIBRILLATION USING DEEP LEARNING
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Supplementary results for stroke, timing of atrial fibrillation diagnosis, and risk of death
<p><span><span><span><span><span><span><span><span><span><span><span><b>Objective:</b> To evaluate the prognosis of ischemic stroke patients according to the timing of an atrial fibrillation (AF) diagnosis, we created an inception cohort of incident stroke events and compared the risk of death between stroke patients with a) sinus rhythm; b) known atrial fibrillation (KAF); and c) AF diagnosed after stroke (AFDAS). </span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Methods:</b> We utilized the Penn AF Free study to create an inception cohort of patients with incident stroke. Mortality events were identified after linkage with the National Death Index through June 30, 2017. We also evaluated initiation of anticoagulants and antiplatelets across the study duration. Cox proportional hazards models evaluated associations between stroke subtypes and death.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span><b>Results</b>: We identified 1,489 individuals who developed an incident ischemic stroke event: 985 did not develop AF at any point during the study period, 215 had KAF before stroke, 160 had AF detected ≤6 months after stroke and 129 had AF detected >6 months after stroke. After a median follow-up of 4.9 [IQR 1.9, 6.8] years, 686 deaths occurred. The annualized mortality rate was 8.8% in the stroke, no AF group; 12.2% in the KAF group, 15.8% in the AFDAS ≤6 months; and 12.7% in the AFDAS > 6 months. Patients in the AFDAS ≤6 months had the highest independent risk of all-cause mortality even after multivariable adjustment for demographics, clinical risk factors and the use of antithrombotic therapies [HR 1.62 (1.22, 2.14)]. Compared to the stroke, no AF group, those with KAF had a higher mortality risk that was rendered non-significant after adjustment. </span></span></span></span></span></span></span></span></span></span></span></p> <p><span class="MsoHyperlink"><span><span><span><span><span><span><span><span><span><b>Conclusions</b></span></span></span></span></span></span></span></span></span></span><span class="MsoHyperlink"><span><span><span><span><span><span><span><span><span>: The AFDAS group had the highest risk of death, which was not explained by comorbidities or use of antithrombotic therapies. </span></span></span></span></span></span></span></span></span></span></p>
Predicting atrial fibrillation recurrence by combining population data and virtual cohorts of patient-specific left atrial models
<p><strong>Abstract</strong></p> <p><strong>Background: </strong>Current ablation therapy for atrial fibrillation is sub-optimal and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more inter-individual variability.</p> <p><strong>Methods: </strong>Patient-specific models were constructed for 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, 16 long-standing persistent), undergoing first ablation. Patients were followed for 1-year using ambulatory ECG monitoring. Each patient-specific biophysical model combined differing fibrosis patterns, fibre orientation maps, electrical properties and ablation patterns to capture uncertainty in atrial properties and to test the ability of the tissue to sustain fibrillation. These simulation stress tests of different model variants were post-processed to calculate atrial fibrillation simulation metrics. Machine learning classifiers were trained to predict atrial fibrillation recurrence using features from the patient history, imaging and atrial fibrillation simulation metrics.</p> <p><strong>Results: </strong>We performed 1100 atrial fibrillation ablation simulations across 100 patient-specific models. Models based on simulation stress tests alone showed a maximum accuracy of 0.63 for predicting long-term fibrillation recurrence. Classifiers trained to history, imaging and simulation stress tests (average ten-fold cross-validation area under the curve 0.85 ± 0.09, recall 0.80 ± 0.13, precision 0.74 ± 0.13) outperformed those trained to history and imaging (area under the curve 0.66 ± 0.17), or history alone (area under the curve 0.61 ± 0.14). </p> <p><strong>Conclusion: </strong>A novel computational pipeline accurately predicted long-term atrial fibrillation recurrence in individual patients by combining outcome data with patient-specific acute simulation response. This technique could help to personalise selection for atrial fibrillation ablation.</p> <p><strong>Dataset Description: </strong>We include surface meshes in vtk format, consisting of the nodes, triangular elements, the atrial coordinate fields defined on the nodes, and the endocardial and epicardial fibre fields defined on the elements. </p> <p>We also include universal atrial coordinate fields alpha and beta, which are a lateral-septal coordinate and posterior-anterior coordinate for the LA. More details on the coordinate construction are given in our manuscript and <a href="https://www.ncbi.nlm.nih.gov/pubmed/31026761">https://www.ncbi.nlm.nih.gov/pubmed/31026761</a>. These coordinates can be used for registering datasets. </p> <p><strong>Publication</strong>: https://pubmed.ncbi.nlm.nih.gov/35089057/</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.