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Heart Failure Prediction in Patients with Remotely Monitored Implanted Cardiac Devices: A Multiparametric Model
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Preliminary findings on left atrial appendage occlusion simulations applying different endocardial devices
Full text linkAtrial fibrillation (AF) is one of the most investigated arrhythmias since it is
associated with a five-fold increase in the risk of strokes. Left atrium dilation
and unbalanced and irregular contraction caused by AF favour blood stasis
and, consequently, stroke risk. The left atrial appendage (LAA) is the site of the
highest clots formation, increasing the incidence of stroke in AF population. For
many years oral anticoagulation therapy has been the most used AF treatment
option available to decrease stroke risk. Unfortunately, several contraindications
including bleeding risk increase, interference with other drugs and with multiorgan
functioning, might outweigh its remarkable benefits on thromboembolic events.
For these reasons, in recent years, other approaches have been designed, including
LAA percutaneous closure. Unfortunately, nowadays, LAA occlusion (LAAO) is
restricted to small subgroups of patients and require a certain level of expertise
and training to successfully complete the procedure without complications. The
most critical clinical problems associated with LAAO are represented by peridevice
leaks and device related thrombus (DRT). The anatomical variability of the
LAA plays a key role in the choice of the correct LAA occlusion device and in its
correct positioning with respect to the LAA ostium during the implant. In this
scenario, computational fluid dynamics (CFD) simulations could have a crucial
role in improving LAAO intervention. The aim of this study was to simulate the fluid
dynamics effects of LAAO in AF patients to predict hemodynamic changes due
to the occlusion. LAAO was simulated by applying two different types of closure
devices based on the plug and the pacifier principles on 3D LA anatomical models
derived from real clinical data in five AF patients. CFD simulations were performed
on the left atrium model before and after the LAAO intervention with each device.
Blood velocity, particle washout and endothelial damage were computed to
quantify flow pattern changes after the occlusion in relation to the thrombogenic
risk. Our preliminary results confirmed an improved blood washout after the
simulated implants and the capability of foreseeing thrombogenic risk based on
endothelial damage and maximum blood velocities in different scenarios. This
tool may help to identify effective device configurations in limiting stroke risk for
patient-specific LA morphologies
Left Atrial Appendage Contraction Analysis: A Preliminary Test on Atrial Fibrillation Patients
Full text linkComputational Fluid Dynamics Simulations to Deepen Understanding of the Hemodynamic Underlying Atrial Fibrillation and Improve Therapeutic Approaches
No full textThis chapter provides an overview of some possible applications of patient-specific computational fluid dynamics (CFD) simulations to gain insight into the fluid dynamic mechanism underlying the onset and maintenance of atrial fibrillation (AF), improve treatment planning, and control disease progression. CFD represents a valuable non-invasive approach to determine and evaluate significant parameters in a very complex fluid dynamic system such as the left atrium in AF. Different applications of our CFD model to derive parameters such as left atrial appendage ostium velocity, wall shear stress, and endothelial cell activation potential, which are shown to be promising indicators for a quantitative prognostic evaluation of AF, are presented and critically evaluated from the perspective of defining a quantitative approach for stroke risk prediction in the context of precision medicine
Applying a Digital Twin Framework for Stroke Risk Evaluation in Atrial Fibrillation Patients
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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