Clinical and electrophysiological predictors of device-detected new-onset atrial fibrillation during 3 years after cardiac surgery

Postoperative atrial fibrillation (POAF) after cardiac surgery is an independent predictor of stroke and mortality late after discharge. We aimed to determine the burden and predictors of early (up to 5th postoperative day) and late (after 5th postoperative day) new-onset atrial fibrillation (AF) using implantable loop recorders (ILRs) in patients undergoing open chest cardiac surgery Seventy-nine patients without a history of AF undergoing cardiac surgery underwent peri-operative high-resolution mapping of electrically induced AF and were followed 36 months after surgery using an ILR (Reveal XTTM). Clinical and electrophysiological predictors of late POAF were assessed. POAF occurred in 46 patients (58%), with early POAF detected in 27 (34%) and late POAF in 37 patients (47%). Late POAF episodes were short-lasting (mostly between 2 min and 6 h) and showed a circadian rhythm pattern with a peak of episode initiation during daytime. In POAF patients, electrically induced AF showed more complex propagation patterns than in patients without POAF. Early POAF, right atrial (RA) volume, prolonged PR time, and advanced age were independent predictors of late POAF

Hybrid cosmic ray measurements using the IceAct telescopes in coincidence with the IceCube and IceTop detectors

IceAct is a proposed surface array of compact (50 cm diameter) and cost-effective Imaging Air Cherenkov Telescopes installed at the site of the IceCube Neutrino Observatory at the geographic South Pole. Since January 2019, two IceAct telescope demonstrators, featuring 61 silicon photomultiplier (SiPM) pixels have been taking data in the center of the IceTop surface array during the austral winter. We present the first analysis of hybrid cosmic ray events detected by the IceAct imaging air-Cherenkov telescopes in coincidence with the IceCube Neutrino Observatory, including the IceTop surface array and the IceCube in-ice array. By featuring an energy threshold of about 10 TeV and a wide field-of-view, the IceAct telescopes show promising capabilities of improving current cosmic ray composition studies: measuring the Cherenkov light emissions in the atmosphere adds new information about the shower development not accessible with the current detectors, enabling significantly better primary particle type discrimination on a statistical basis. The hybrid measurement also allows for detailed feasibility studies of detector cross-calibration and of cosmic ray veto capabilities for neutrino analyses. We present the performance of the telescopes, the results from the analysis of two years of data, and an outlook of a hybrid simulation for a future telescope array

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Collins and Sivers asymmetries in muonproduction of pions and kaons off transversely polarised protons

Measurements of the Collins and Sivers asymmetries for charged pions and charged and neutral kaons produced in semi-inclusive deep-inelastic scattering of high energy muons off transversely polarised protons are presented. The results were obtained using all the available COMPASS proton data, which were taken in the years 2007 and 2010. The Collins asymmetries exhibit in the valence region a non-zero signal for pions and there are hints of non-zero signal also for kaons. The Sivers asymmetries are found to be positive for positive pions and kaons and compatible with zero otherwise. © 2015

Antikoagulation bei linksatrialer Katheterablation

Left atrial catheter ablation is an established treatment for rhythm maintenance in patients with atrial fibrillation and other supraventricular arrhythmias. There is growing evidence that rhythm-preserving therapy, in addition to improving quality of life and relieving atrial fibrillation-related symptoms, may prevent cardiovascular events such as ischemic stroke and help to preserve cognitive function. However, clinically silent acute cerebral ischemia is found in about a quarter of patients after left atrial fibrillation ablation by MRI and an estimated 0.2-0.3 % of all ablated patients experience cerebral ischemia with manifest neurological deficits peri-intervention. Optimal anticoagulation to prevent thromboembolic events during left atrial catheter ablation is therefore a central element in a holistic therapy concept. In this article, the current evidence and the results of the AFNET-coordinated AXAFA-AFNET 5 study will be discussed

Automated Signal Quality Assessment of Single-Lead ECG Recordings for Early Detection of Silent Atrial Fibrillation

Atrial fibrillation (AF) is an arrhythmic cardiac disorder with a high and increasing prevalence in aging societies, which is associated with a risk for stroke and heart failure. However, early detection of onset AF can become cumbersome since it often manifests in an asymptomatic and paroxysmal nature, also known as silent AF. Large-scale screenings can help identifying silent AF and allow for early treatment to prevent more severe implications. In this work, we present a machine learning-based algorithm for assessing signal quality of hand-held diagnostic ECG devices to prevent misclassification due to insufficient signal quality. A large-scale community pharmacy-based screening study was conducted on 7295 older subjects to investigate the performance of a single-lead ECG device to detect silent AF. Classification (normal sinus rhythm or AF) of the ECG recordings was initially performed automatically by an internal on-chip algorithm. The signal quality of each recording was assessed by clinical experts and used as a reference for the training process. Signal processing stages were explicitly adapted to the individual electrode characteristics of the ECG device since its recordings differ from conventional ECG tracings. With respect to the clinical expert ratings, the artificial intelligence-based signal quality assessment (AISQA) index yielded strong correlation of 0.75 during validation and high correlation of 0.60 during testing. Our results suggest that large-scale screenings of older subjects would greatly benefit from an automated signal quality assessment to repeat measurements if applicable, suggest additional human overread and reduce automated misclassifications

Beat-to-beat P-wave Variability Increases From Paroxysmal to Persistent Atrial Fibrillation

Atrial fibrillation (AF) is known to worsen over time. Beat-to-beat P-wave variability is used to evaluate the risk of developing AF, but it has not been used to monitor arrhythmia progression in a comprehensive model. The aim of this study is to create a method to measure beat-to-beat P-wave variability to evaluate AF types. ECG recordings of 5 minutes were measured on 159 AF patients. The first three principal components (PCs) of the ECG signal were added to the analysis. The temporal beat-to-beat P-wave variability was assessed through the normalized Euclidean Distance and the Similarity Index. The spatial P-wave similarity was measured as the percentage of variance explained by the first 2 PCs. A binomial logistic regression model was built for each lead and parameter, with AF type as dependent variable. To assess variability due exclusively to the P-waves, we considered, as confounding factors, other sources of ECG-variability, such as the noise level, the variability of the RR series and of the heart axis. Both temporal (e.g. 0.94±0.12 for paroxysmal AF and 0.85±0.28 for persistent AF in lead I, p=0.001) and spatial P-wave similarities (95.35±3.29% for paroxysmal AF vs 94.44±4.14% for persistent AF, p=0.001) were significantly higher in paroxysmal than in persistent AF, suggesting them as promising tools to evaluate AF types

Beat-to-beat P-wave Variability Increases From Paroxysmal to Persistent Atrial Fibrillation

Atrial fibrillation (AF) is known to worsen over time. Beat-to-beat P-wave variability is used to evaluate the risk of developing AF, but it has not been used to monitor arrhythmia progression in a comprehensive model. The aim of this study is to create a method to measure beat-to-beat P-wave variability to evaluate AF types. ECG recordings of 5 minutes were measured on 159 AF patients. The first three principal components (PCs) of the ECG signal were added to the analysis. The temporal beat-to-beat P-wave variability was assessed through the normalized Euclidean Distance and the Similarity Index. The spatial P-wave similarity was measured as the percentage of variance explained by the first 2 PCs. A binomial logistic regression model was built for each lead and parameter, with AF type as dependent variable. To assess variability due exclusively to the P-waves, we considered, as confounding factors, other sources of ECG-variability, such as the noise level, the variability of the RR series and of the heart axis. Both temporal (e.g. 0.94±0.12 for paroxysmal AF and 0.85±0.28 for persistent AF in lead I, p=0.001) and spatial P-wave similarities (95.35±3.29% for paroxysmal AF vs 94.44±4.14% for persistent AF, p=0.001) were significantly higher in paroxysmal than in persistent AF, suggesting them as promising tools to evaluate AF types