Atrial fibrillation incidence after coronary artery bypass graft surgery and percutaneous coronary intervention: the prospective AFAF cohort study.

Objectives. Atrial fibrillation is a common arrhythmia in patients with ischemic heart disease. This study aimed to determine the cumulative incidence of new-onset atrial fibrillation after percutaneous coronary intervention or coronary artery bypass grafting surgery during 30 days of follow-up. Design. This was a prospective multi-center cohort study on atrial fibrillation incidence following percutaneous coronary intervention or coronary artery bypass grafting for stable angina or non-ST-elevation acute coronary syndrome. Heart rhythm was monitored for 30 days postoperatively by in-hospital telemetry and handheld thumb ECG recordings after discharge were performed. The primary endpoint was the cumulative incidence of atrial fibrillation 30 days after the index procedure. Results. In-hospital atrial fibrillation occurred in 60/123 (49%) coronary artery bypass graft and 0/123 percutaneous coronary intervention patients (p < .001). The cumulative incidence of atrial fibrillation after 30 days was 56% (69/123) of patients undergoing coronary artery bypass grafting and 2% (3/123) of patients undergoing percutaneous coronary intervention (p < .001). CABG was a strong predictor for atrial fibrillation compared to PCI (OR 80.2, 95% CI 18.1-354.9, p < .001). Thromboembolic stroke occurred in-hospital in one coronary artery bypass graft patient unrelated to atrial fibrillation, and at 30 days in two additional patients, one in each group. There was no mortality. Conclusion. New-onset atrial fibrillation during 30 days of follow-up was rare after percutaneous coronary intervention but common after coronary artery bypass grafting. A prolonged uninterrupted heart rhythm monitoring strategy identified additional patients in both groups with new-onset atrial fibrillation after discharge.

Seasonal occurrence and individual variability of bull sharks, Carcharhinus leucas, in a marine reserve of the southwestern Gulf of California.

Background: Studying how the bull sharks aggregate and how they can be driven by life history traits such as reproduction, prey availability, predator avoidance and social interaction in a National Park such as Cabo Pulmo, is key to understand and protect the species. Methods: The occurrence variability of 32 bull sharks tracked with passive acoustic telemetry were investigated via a hierarchical logistic regression model, with inference conducted in a Bayesian framework, comparing sex, and their response to temperature and chlorophyll. Results: Based on the fitted model, occurrence probability varied by sex and length. Juvenile females had the highest values, whereas adult males the lowest. A strong seasonality or day of the year was recorded, where sharks were generally absent during September-November. However, some sharks did not show the common pattern, being detected just for a short period. This is one of the first studies where the Bayesian framework is used to study passive acoustic telemetry proving the potential to be used in further studies.

Novel predictive approaches for drug-induced convulsions in non-human primates using machine learning and heart rate variability analysis.

Drug-induced convulsions are a major challenge to drug development because of the lack of reliable biomarkers. Using machine learning, our previous research indicated the potential use of an index derived from heart rate variability (HRV) analysis in non-human primates as a biomarker for convulsions induced by GABAA receptor antagonists. The present study aimed to explore the application of this methodology to other convulsants and evaluate its specificity by testing non-convulsants that affect the autonomic nervous system. Telemetry-implanted males were administered various convulsants (4-aminopyridine, bupropion, kainic acid, and ranolazine) at different doses. Electrocardiogram data gathered during the pre-dose period were employed as training data, and the convulsive potential was evaluated using HRV and multivariate statistical process control. Our findings show that the Q-statistic-derived convulsive index for 4-aminopyridine increased at doses lower than that of the convulsive dose. Increases were also observed for kainic acid and ranolazine at convulsive doses, whereas bupropion did not change the index up to the highest dose (1/3 of the convulsive dose). When the same analysis was applied to non-convulsants (atropine, atenolol, and clonidine), an increase in the index was noted. Thus, the index elevation appeared to correlate with or even predict alterations in autonomic nerve activity indices, implying that this method might be regarded as a sensitive index to fluctuations within the autonomic nervous system. Despite potential false positives, this methodology offers valuable insights into predicting drug-induced convulsions when the pharmacological profile is used to carefully choose a compound.

Attention 3D central difference convolutional dense network for hyperspectral image classification.

Hyperspectral Images (HSI) classification is a challenging task due to a large number of spatial-spectral bands of images with high inter-similarity, extra variability classes, and complex region relationships, including overlapping and nested regions. Classification becomes a complex problem in remote sensing images like HSIs. Convolutional Neural Networks (CNNs) have gained popularity in addressing this challenge by focusing on HSI data classification. However, the performance of 2D-CNN methods heavily relies on spatial information, while 3D-CNN methods offer an alternative approach by considering both spectral and spatial information. Nonetheless, the computational complexity of 3D-CNN methods increases significantly due to the large capacity size and spectral dimensions. These methods also face difficulties in manipulating information from local intrinsic detailed patterns of feature maps and low-rank frequency feature tuning. To overcome these challenges and improve HSI classification performance, we propose an innovative approach called the Attention 3D Central Difference Convolutional Dense Network (3D-CDC Attention DenseNet). Our 3D-CDC method leverages the manipulation of local intrinsic detailed patterns in the spatial-spectral features maps, utilizing pixel-wise concatenation and spatial attention mechanism within a dense strategy to incorporate low-rank frequency features and guide the feature tuning. Experimental results on benchmark datasets such as Pavia University, Houston 2018, and Indian Pines demonstrate the superiority of our method compared to other HSI classification methods, including state-of-the-art techniques. The proposed method achieved 97.93% overall accuracy on the Houston-2018, 99.89% on Pavia University, and 99.38% on the Indian Pines dataset with the 25 × 25 window size.

Improving Telemetry use in the Acute Assessment Unit.

BACKGROUND AND AIMS: Despite published guidelines, telemetry use is inappropriate in 25-43% of cases. This impacts patient safety and telemetry effectiveness. QI methodology was used to review telemetry in a hospital acute medical unit with the aim of reducing inappropriate use and addressing alarm fatigue. METHODS: A 'Telemetry Indication Form' was created. Eight weeks of baseline data was collated before introducing the 'Indication Form'. Four plan-do-study-act cycles were conducted. At each cycle, data was analysed using statistical process control charts. RESULTS: Inappropriate telemetry use significantly reduced from 32% to 4%. Total telemetry use also fell. Unfortunately, interventions to address alarm rates did not result in significant reduction in false alarms. CONCLUSIONS: A 'Telemetry Indication Form' has significant potential to improve patient safety through reducing inappropriate use.

Paper towel shredding as a novel, affordable, noninvasive method for detecting arousals in hibernating rodents.

Many research groups explore the regulation of hibernation or compare the physiology of heterothermic mammals between the torpid and aroused, euthermic states. Current methods for monitoring torpor (for example, infrared cameras, body temperature or heart-rate telemetry, and motion sensing) are costly, require specialized techniques, and can be invasive. Here we present an alternate method for determining torpor-bout duration that is cost-effective, noninvasive and accurate: paper towel shredding. In the winter, euthermic thirteen-lined ground squirrels will shred paper towels placed in the cage, but torpid animals will not. The presence of a shredded paper towel, indicating an arousal from torpor, is easily evaluated during routine daily monitoring. In 12 animals over 52 days, this simple technique detected 59 arousals with 100% accuracy when compared with the body temperature telemetry of the same animals. Moreover, this novel method avoids some of the drawbacks of other cheap monitoring systems such as the sawdust technique.

Analysis of Electrocardiograms and Behavior in Mice from Pregnancy to Lactation Period.

Changes in the mother-offspring relationship are presumably accompanied by dynamic changes in the autonomic nervous system. Although temporal measurements of autonomic activity have been performed in human mothers and infants, the analysis of long-term changes remains unexplored. Mouse mothers can form social bonds with their pups and have a short period of pregnancy and lactation, which makes them useful for the examination of physiological changes from pregnancy to pup-rearing. Therefore, a telemetry system was used for several weeks to measure the changes in the autonomic nervous system and the behavior of mouse mothers. The current results showed that an electrocardiogram (ECG) could be stably recorded regardless of the movements of mothers and parturition. ECG analysis showed that the heart rate gradually decreased from pregnancy to lactation, and sympathetic activity sharply increased as the pups developed. Furthermore, the simultaneous recording of behavior and ECG in the home cage enabled us to understand the behavior-dependent influences on the ECG, thereby revealing the characteristics of autonomic nervous activity during each behavior. Thus, the present experimental method helps to understand how the physiological characteristics of mothers change from pregnancy through pup rearing, supporting the healthy development of pups.

Evaluation of a Clinical Decision Support Tool to Guide Adoption of the American Heart Association Telemetry Monitoring Practice Standards.

BACKGROUND: The objectives of this study were to (1) evaluate telemetry use pre- and postimplementation of clinical decision support tools to support American Heart Association practice standards for telemetry monitoring and (2) understand the factors that may contribute to variation of telemetry monitoring in practice. METHODS AND RESULTS: First, we captured overall variability in telemetry use pre- and postimplementation of the clinical decision support intervention. We then conducted semistructured interviews with telemetry-ordering providers to identify key barriers and facilitators to adoption. During the study period, 399 physicians met criteria for inclusion and were divided into excessive and nonexcessive orderers. Distribution of telemetry use was bimodal. Among nonexcessive users, 24.4% of patient days were with telemetry compared with 51.6% among excessive users. On average, both excessive (6.1% reduction) and nonexcessive users (2.8% reduction) decreased telemetry use postimplementation, and these reductions were sustained over a 16-month period. Sixteen interviews were conducted. Physicians believed that the tool was successful because it caused them to more closely consider if telemetry was indicated for each patient. Physicians also voiced frustration with interruptions to their workflow, and some noted that they commonly use telemetry outside of practice standards to monitor patients who were acutely but not critically ill. CONCLUSIONS: Embedding telemetry practice standards into the electronic health record in the form of clinical decision support is effective at reducing excess telemetry use. Although the intervention was well received, there are persistent barriers, such as preexisting views on telemetry and existing workflow habits, that may inhibit higher adoption of standards.

STIRUnet: SwinTransformer and inverted residual convolution embedding in unet for Sea-Land segmentation.

Extraction of coastline from optical remote sensing images is of paramount importance for coastal zone management, erosion monitoring, and intelligent ocean construction. However, nearshore marine environment complexity presents a challenge when capturing small-scale and detailed information regarding coastlines. Furthermore, the presence of numerous tidal flats, suspended sediments, and coastal biological communities exacerbates the reduction in segmentation accuracy, which is particularly noticeable in medium-high-resolution remote sensing image segmentation tasks. Most previous related studies, based primarily on convolutional neural networks (CNNs) or traditional feature extraction methods, faced challenges in detailed pixel-level refinement and lacked comprehensive understanding of the studied images. Therefore, we proposed a new U-shaped deep learning model (STIRUnet) that combines the excellent global modeling ability of SwinTransformer with an improved CNN using an inverted residual module. The proposed method has the capability of global supervised feature learning and layer-by-layer feature extraction, and we conducted sea-land segmentation experiments using GF-HNCD and BSD remote sensing image datasets to validate the performance of the proposed model. The results indicate the following: 1) suspended sediments and coastal biological communities are major contributors to coastline blurring, and 2) the recovery of minute features (e.g., narrow watercourses and microscale artificial structures) effectively enhances edge details and leads to more realistic segmentation outcomes. The findings of this study are highly important in relation of accurate extraction of sea-land information in complex marine environments, and they offer novel insights regarding mixed-pixel identification.

Repeated Syncope Following COVID-19 Infection.

A 74-year-old woman presented to our hospital with syncope after a coronavirus disease 2019 (COVID-19) infection. Upon admission, she passed out, and an 8 second sinus arrest was detected during telemetry monitoring. During the next syncope episode, telemetry monitoring showed that her heart rate decreased from 80 to 36 bpm, accompanied by a 2.4 second pause. A permanent pacemaker was implanted; however, the patient still experienced syncope. The head-up tilt test revealed a vasodepressor reflex syncope. The need for permanent pacemakers in patients with syncope following COVID-19 therefore remains controversial.

A systematic review of the use of in-vehicle telematics in monitoring driving behaviours.

BACKGROUND: Road traffic deaths are increasing globally, and preventable driving behaviours are a significant cause of these deaths. In-vehicle telematics has been seen as technology that can improve driving behaviour. The technology has been adopted by many insurance companies to track the behaviours of their consumers. This systematic review presents a summary of the ways that in-vehicle telematics has been modelled and analysed. METHODOLOGY: Electronic searches were conducted on Scopus and Web of Science. Studies were only included if they had a sample size of 10 or more participants, collected their data over at least multiple days, and were published during or after 2010. 45 relevant papers were included in the review. 27 of these articles received a rating of "good" in the quality assessment. RESULTS: We found a divide in the literature regarding the use of in-vehicle telematics. Some articles were interested in the utility of in-vehicle telematics for insurance purposes, while others were interested in determining the influence that in-vehicle telematics has on driving behaviour. Machine learning analyses were the most common forms of analysis seen throughout the review, being especially common in articles with insurance-based outcomes. Acceleration, braking, and speed were the most common variables identified in the review. CONCLUSION: We recommend that future studies provide the demographical information of their sample so that the influence of in-vehicle telematics on the driving behaviours of different groups can be understood. It is also recommended that future studies use multi-level models to account for the hierarchical structure of the telematics data. This hierarchical structure refers to the individual trips for each driver.

Troubleshooting Cochlear Implant Malfunction Using Neural Response Telemetry and Normal Saline.

Cochlear implantation has become a standard of care for a child diagnosed with bilateral profound sensorineural hearing loss with a structured surgical standard operating procedure. A 3-year-old boy with bilateral profound prelingual sensorineural deafness underwent a Med-EL Sonata Ti100 implant. We faced a peculiar situation intraoperatively after inserting the electrodes and closing the wound. The impedance recording indicated high ground path impedance with short-circuiting of few electrodes. As a bionic implant, its electronic components may at times malfunction both intraoperatively and/or postoperatively; therefore, neural response telemetry (NRT) was invented to check it. By using NRT and a few milliliters of normal saline, we were able to diagnose as well as rectify the malfunctioning of the implant.

Variación de la impedancia eléctrica a lo largo de cinco años postimplantación y relación con el umbral de confort máximo (MCL) en adultos portadores de implante coclear / Variation of electrical impedance over 5 years post-implantation and relationship with the maximum comfort level (MCL) in adults with cochlear implants

Introducción El umbral de confort máximo o maximum comfort level (MCL), umbral eléctrico o threshold level (THR) e impedancia eléctrica cambian en el postoperatorio del implante coclear durante meses hasta estabilizarse. El objetivo de este artículo es establecer la variación durante cinco años posquirúrgicos de la impedancia, y su relación con MCL en adultos implantados unilateralmente. Métodos Estudio retrospectivo a cinco años, con 78 pacientes adultos implantados con MED-EL en un hospital terciario desde el año 2000 hasta 2015. Se analizó la variación de impedancia, MCL y relación entre ellos, en electrodos basales (9-12), medios (5-8) y apicales (1-4), realizando análisis inferencial ANOVA de medidas repetidas con comparaciones entre tiempos consecutivos, corregidas con criterio Bonferroni. Resultados Treinta y tres hombres (42,3%) y 45 mujeres (57,7%), con edad media 52,7 ± 14,6 años. Se consideró «estabilidad» el momento del seguimiento sin diferencias estadísticamente significativas entre una visita y la siguiente. Los cambios en la impedancia en electrodos medios dejaron de ser estadísticamente significativos a los tres meses, y en apicales a los seis meses, con valores medios de 5,84 y 6,43 kohms. MCL se estabilizó a los dos años en electrodos basales y apicales, y a los tres años en medios, con valores medios de 24,9, 22,7 y 25,6 qu. Hubo correlación entre MCL e impedancia en electrodos medios hasta 3 meses y en apicales hasta un año. Conclusiones La impedancia eléctrica desciende significativamente en electrodos medios y apicales hasta tres y seis meses. El MCL aumenta significativamente hasta dos años. La impedancia se relaciona con MCL hasta seis meses. (AU)

Introduction The maximum comfort level (MCL), threshold level (THR) and electrical impedance change in the postoperative period of the cochlear implant for months until they stabilize. The objective of this article is to establish the variation during 5 post-surgical years of impedance, and its relationship with MCL in unilaterally implanted adults. Methods Retrospective study over 5 years, with 78 adult patients implanted with MED-EL in a tertiary hospital from the year 2000 to 2015. The variation in impedance, MCL and the relationship between them were analyzed in basal (9-12), medial (5-8) and apical electrodes (1-4), performing an inferential ANOVA analysis of repeated measures with comparisons between consecutive times, corrected with Bonferroni criteria. Results 33 men (42.3%) and 45 women (57.7%), with a mean age of 52.7 ± 14.6 years. “Stability” was considered the time of follow-up without statistically significant differences between one visit and the next. Changes in impedance in medial electrodes ceased to be statistically significant at 3 months, and in apicals at 6 months, with mean values of 5.84 and 6.43 kohms. MCL stabilized at 2 years in basal and apical electrodes, and at 3 years in medial, with mean values of 24.9, 22.7, and 25.6 qu. There was a correlation between MCL and impedance in medium electrodes up to 3 months and in apical ones up to one year. Conclusions Electrical impedance drops significantly in medial and apical electrodes up to 3 and 6 months. MCL increases significantly up to two years. Impedance is related to MCL up to 6 months. (AU)

[Options for home telemonitoring in heart failure patients]. / Opties voor thuismonitoring bij patiënten met hartfalen.

OBJECTIVE: To provide an overview of the effectiveness of various forms of home telemonitoring systems for heart failure and the potential role these systems may have in decreasing the burden on healthcare through reduction in heart failure hospitalizations. DESIGN: Meta-analysis of randomized and observational studies. METHODS: A meta-analysis of randomized and observational studies was carried out to assess the effect on mortality and heart failure-related hospitalizations, comparing standard heart failure care with the use of home monitoring systems. RESULTS: The pooled results from 92 studies demonstrate a reduction in the risk of both mortality and heart failure admissions. CONCLUSION: The results of this meta-analysis support the use of home telemonitoring systems. Determining which form of home telemonitoring is most suitable for which patient requires further research.

Deeply Implanted Conformal Antenna for Real-Time Bio-Telemetry Applications.

The design and experimental verification of a deeply implanted conformal printed antenna is presented. The hip implant acts as the ground plane for a coaxial-cable-fed trapezoidal radiator designed to transmit biological signals collected within the body by proper biosensors. The arrangement, consisting of a metallic (or equivalent) hip implant, bio-compatible gypsum-based dielectric, and conformal radiator, was tested when the hosting 3D-printed plastic bone was immersed in tissue-like liquid contained in a plastic bucket. The dimensions of the set-up are similar to a human leg. Matching and radiation characteristics are presented in the industrial, scientific, and medical (ISM) frequency band (2.4-2.5 GHz), showing the feasibility of the proposed arrangement.

Road extraction through Yangwang-1 nighttime light data: A case study in Wenzhou, China.

The extraction of roadways from remote sensing imagery constitutes a pivotal task, with far-reaching implications across diverse domains such as urban planning, management of transportation systems, emergency response initiatives, and environmental monitoring endeavors. Satellite images captured during daytime have customarily served as the primary resource for this extraction process. However, the emergence of Nighttime Light (NTL) remote sensing data introduces an innovative dimension to this arena. The exploration of NTL data for road extraction remains in its nascent stage, and this study seeks to bridge this gap. We present a refined U-Net model (CA U-Net) integrated with Cross-Attention Mechanisms, meticulously designed to extract roads from Yangwang-1 NTL images. This model incorporates several enhancements, thereby improving its proficiency in identifying and delineating road networks. Through extensive experimentation conducted in the urban landscape of Wenzhou City, the model delivers highly accurate results, achieving an F1 score of 84.46%. These outcomes significantly surpass the performance benchmarks set by Support Vector Machines (SVM) and the Optimal Threshold (OT) method. This promising development paves the way towards maximizing the utility of NTL data for comprehensive mapping and analysis of road networks. Furthermore, the findings underscore the potential of utilizing Yangwang-1 data as a reliable source for road extraction and reaffirm the viability of deploying deep learning frameworks for road extraction tasks utilizing NTL data.

Remote Multi-Person Heart Rate Monitoring with Smart Speakers: Overcoming Separation Constraint.

Heart rate is a key vital sign that can be used to understand an individual's health condition. Recently, remote sensing techniques, especially acoustic-based sensing, have received increasing attention for their ability to non-invasively detect heart rate via commercial mobile devices such as smartphones and smart speakers. However, due to signal interference, existing methods have primarily focused on monitoring a single user and required a large separation between them when monitoring multiple people. These limitations hinder many common use cases such as couples sharing the same bed or two or more people located in close proximity. In this paper, we present an approach that can minimize interference and thereby enable simultaneous heart rate monitoring of multiple individuals in close proximity using a commonly available smart speaker prototype. Our user study, conducted under various real-life scenarios, demonstrates the system's accuracy in sensing two users' heart rates when they are seated next to each other with a median error of 0.66 beats per minute (bpm). Moreover, the system can successfully monitor up to four people in close proximity.

Telemetry-Based Haptic Rendering for Racing Game Experience Improvement.

Many recent games, such as racing and flight games, open their game telemetry data to users by storing them in the local memory. Such telemetry data can provide useful information for haptic rendering, and this advantage has been exploited by the industry. This approach applies to any applications that export telemetry data in run time. The haptic rendering module operates as a separate process that accesses the telemetry data in parallel with the application. It is simple, efficient, and modular while retaining the application intact. We examine the approach's viability for user experience improvement by developing three telemetry-based haptic rendering algorithms for car racing games. They express the car engine response, collisions with external objects, and the road surface texture, respectively. Building a haptics-enabled driving platform, we conducted a user study comparing gaming experiences between our telemetry-based algorithms and conventional sound-to-tactile conversion algorithms. The results showed that the telemetry-based effects elicited better experiences than the sound-based effects.