Minimizing drug-drug interactions between dabigatran and levetiracetam through clinical management. a case report

Background Direct oral anticoagulants (DOACs) are useful for stroke prevention in atrial fibrillation (AF) patients. However, the concomitant administration of Levetiracetam limited their use in clinical practice, although some authors raise doubts about clinical relevance of the interaction. Case summary We report a case of a 54-year-old male with AF, cirrhosis and seizures, in which the assessment of Dabigatran plasma concentration was needed due to the concomitant use of Levetiracetam. In this case no relevant reduction of trough Dabigatran plasma concentration was found. An increased peak serum level of dabigatran may be obtained delaying levetiracetam administration. The patient was then followed in our clinic and during 32 months of follow up no ischemic or haemorrhagic events occurred. Discussion The evaluation of DOACs concentration could be helpful to start a tailored therapy in frailty patients

Efficacy of Spectral Signatures for the Automatic Classification of Abnormal Ventricular Potentials in Substrate-Guided Mapping Procedures

Several peculiar spectral signatures of post-ischaemic ventricular tachycardia (VT) electrograms (EGMs) have been recently published in the scientific literature. However, despite they were claimed as potentially useful for the automatic identification of arrhythmogenic targets for the VT treatment by trans-catheter ablation, their exploitation in machine learning (ML) applications has been not assessed yet. The aim of this work is to investigate the impact of the information retrieved from these frequency-domain signatures in modelling supervised ML tools for the identification of physiological and abnormal ventricular potentials (AVPs). As such, 1504 bipolar intracardiac EGMs from nine electroanatomic mapping procedures of post-ischaemic VT patients were retrospectively labelled as AVPs or physiological by an expert electrophysiologist. In order to assess the efficacy of the proposed spectral features for AVPs recognition, two different classifiers were adopted in a 10-time 10-fold cross-validation scheme. In both classifiers, the adoption of spectral signatures led to recognition accuracy values above 81%, suggesting that the use of the frequency-domain characteristics of these signals can be successfully considered for the computer-aided recognition of AVPs in substrate-guided mapping procedures

automatic detection of complete and measurable cardiac cycles in antenatal pulsed wave doppler signals

Abstract Background and objective Pulsed-wave Doppler (PWD) echocardiography is the primary tool for antenatal cardiological diagnosis. Based on it, different measurements and validated reference parameters can be extracted. The automatic detection of complete and measurable cardiac cycles would represent a useful tool for the quality assessment of the PWD trace and the automated analysis of long traces. Methods This work proposes and compares three different algorithms for this purpose, based on the preliminary extraction of the PWD velocity spectrum envelopes: template matching, supervised classification over a reduced set of relevant waveshape features, and supervised classification over the whole waveshape potentially representing a cardiac cycle. A custom dataset comprising 43 fetal cardiac PWD traces (174,319 signal segments) acquired on an apical five-chamber window was developed and used for the assessment of the different algorithms. Results The adoption of a supervised classifier trained with the samples representing the upper and lower envelopes of the PWD, with additional features extracted from the image, achieved significantly better results (p Conclusions The results reveal excellent detection performance, suggesting that the proposed approach can be adopted for the automatic analysis of long PWD traces or embedded in ultrasound machines as a first step for the extraction of measurements and reference clinical parameters

An FPGA platform for real-time simulation of spiking neuronal networks

In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments

Spectral characterisation of ventricular intracardiac potentials in human post-ischaemic bipolar electrograms

Abnormal ventricular potentials (AVPs) are frequently referred to as high-frequency defections in intracardiac electrograms (EGMs). However, no scientifc study performed a deep spectral characterisation of AVPs and physiological potentials in real bipolar intracardiac recordings across the entire frequency range imposed by their sampling frequency. In this work, the power contributions of post-ischaemic physiological potentials and AVPs, along with some spectral features, were evaluated in the frequency domain and then statistically compared to highlight specific spectral signatures for these signals. To this end, 450 bipolar EGMs from seven patients affected by post-ischaemic ventricular tachycardia were retrospectively annotated by an experienced cardiologist. Given the high variability of the morphologies observed, three different sub-classes of AVPs and two subcategories of post-ischaemic physiological potentials were considered. All signals were acquired by the CARTO\uae 3 system during substrate-guided catheter ablation procedures. Our findings indicated that the main frequency contributions of physiological and pathological post-ischaemic EGMs are found below 320 Hz. Statistical analyses showed that, when biases due to the signal amplitude influence are eliminated, not only physiological potentials show greater contributions below 20 Hz whereas AVPs demonstrate higher spectral contributions above~ 40 Hz, but several finer differences may be observed between the different AVP types

Incidence of predatory journals in computer science literature

Purpose One of the main tasks of a researcher is to properly communicate the results he obtained. The choice of the journal in which to publish the work is therefore very important. However, not all journals have suitable characteristics for a correct dissemination of scientific knowledge. Some publishers turn out to be unreliable and, against a payment, they publish whatever researchers propose. The authors call "predatory journals" these untrustworthy journals. The purpose of this paper is to analyse the incidence of predatory journals in computer science literature and present a tool that was developed for this purpose. Design/methodology/approach The authors focused their attention on editors, universities and publishers that are involved in this kind of publishing process. The starting point of their research is the list of scholarly open-access publishers and open-access stand-alone journals created by Jeffrey Beall. Specifically, they analysed the presence of predatory journals in the search results obtained from Google Scholar in the engineering and computer science fields. They also studied the change over time of such incidence in the articles published between 2011 and 2015. Findings The analysis shows that the phenomenon of predatory journals somehow decreased in 2015, probably due to a greater awareness of the risks related to the reputation of the authors. Originality/value We focused on computer science field, using a specific sample of queries. We developed a software to automatically make queries to the search engine, and to detect predatory journals, using Beall's list

A Periodic Transmission Line Model for Body Channel Communication

Body channel communication (BCC) is a technique for data transmission exploiting the human body as communication channel. Even though it was pioneered about 25 years ago, the identification of a good electrical model behind its functioning is still an open research question. The proposed distributed model can then serve as a supporting tool for the design, allowing to enhance the performances of any BCC system. A novel finite periodic transmission line model was developed to describe the human body as transmission medium. According to this model, for the first time, the parasitic capacitance between the transmitter and the receiver is assumed to depend on their distance. The parameters related to the body and electrodes are acquired experimentally by fitting the bio-impedentiometric measurements, in the range of frequencies from 1 kHz to 1 MHz, obtaining a mean absolute error lower than 4° and 30Ω for the phase angle and impedance modulus, respectively. The proposed mathematical framework has been successfully validated by describing a ground-referred and low-complexity system called Live Wire, suitable as supporting tool for visually impaired people, and finding good agreement between the measured and the calculated data, marking a ±3% error for communication distances ranging from 20 to 150 cm. In this work we introduced a new circuital approach, for capacitive-coupling systems, based on finite periodic transmission line, capable to describe and model BCC systems allowing to optimize the performances of similar systems

Exploring Transfer Learning for Ventricular Tachycardia Electrophysiology Studies

Arrhythmogenic sites in post-ischemic ventricular tachycardia (VT) are usually identified by looking for abnormal ventricular potentials (AVPs) in intracardiac electrograms (EGMs). Unfortunately, the accurate recognition of AVPs is a challenging problem for different reasons, including the intrinsic variability in the A VP waveform. Given the high performance of deep neural networks in several scenarios, in this work, we explored the use of transfer learning (TL) for AVPs detection in intracardiac electrophysiology. A balanced set of 1504 bipolar intracardiac EGMs was collected from nine post-ischemic VT patients. The time-frequency representation was generated for each EGM by computing the synchrosqueezed wavelet transform to be used in the re-training of the convolutional neural network. The proposed approach allows obtaining high recognition results, above 90% for all the investigated performance indexes, demonstrating the effectiveness of deep learning in the recognition of AVPs in post-ischemic VT EGMs and paving the way for its use in supporting clinicians in targeting arrhythmogenic sites. In addition, this study further confirms the efficacy of the TL approach even in case of limited dataset sizes

The history and challenges of SCP-ECG: the standard communication protocol for computer-assisted electrocardiography

Ever since the first publication of the standard communication protocol for computer-assisted electrocardiography (SCP-ECG), prENV 1064, in 1993, by the European Committee for Standardization (CEN), SCP-ECG has become a leading example in health informatics, enabling open, secure, and well-documented digital data exchange at a low cost, for quick and efficient cardiovascular disease detection and management. Based on the experiences gained, since the 1970s, in computerized electrocardiology, and on the results achieved by the pioneering, international cooperative research on common standards for quantitative electrocardiography (CSE), SCP-ECG was designed, from the beginning, to empower personalized medicine, thanks to serial ECG analysis. The fundamental concept behind SCP-ECG is to convey the necessary information for ECG re-analysis, serial comparison, and interpretation, and to structure the ECG data and metadata in sections that are mostly optional in order to fit all use cases. SCP-ECG is open to the storage of the ECG signal and ECG measurement data, whatever the ECG recording modality or computation method, and can store the over-reading trails and ECG annotations, as well as any computerized or medical interpretation reports. Only the encoding syntax and the semantics of the ECG descriptors and of the diagnosis codes are standardized. We present all of the landmarks in the development and publication of SCP-ECG, from the early 1990s to the 2009 International Organization for Standardization (ISO) SCP-ECG standards, including the latest version published by CEN in 2020, which now encompasses rest and stress ECGs, Holter recordings, and protocol-based trials