A Patch Wearable Cardioverter-Defibrillator for Patients at Risk of Sudden Cardiac Arrest.

BACKGROUND: For many patients, sudden cardiac arrest (SCA) risk is elevated temporarily. Wearable cardioverter-defibrillators (WCDs) can monitor and treat SCA during these temporary periods. Traditional WCDs can be uncomfortable, require frequent maintenance, and cannot be used when showering, resulting in poor compliance and avoidable SCA deaths. The Jewel is a novel, water-resistant patch-wearable cardioverter-defibrillator (P-WCD) with a machine learning detection algorithm designed to improve compliance and protection against SCA. OBJECTIVES: This study aims to demonstrate the safety and clinical effectiveness of a novel P-WCD. METHODS: The Jewel IDE Study, a prospective, single-arm study conducted at 30 U.S. sites, enrolled patients at SCA risk due to ventricular tachycardia/ventricular fibrillation who were not candidates for or refused an implantable defibrillator. The primary safety endpoint was <15% patients with clinically significant cutaneous adverse device effects and the primary effectiveness endpoint was <2 inappropriate shocks/100 patient-months. Secondary endpoints were ≥1 successful ventricular tachycardia/ventricular fibrillation conversion and wear time compliance of >14.1 h/d. RESULTS: A total of 305 patients (mean age: 57.9 years; 30.2% female, 27.9% non-White) were enrolled, of which 290 had available device data. The clinically significant cutaneous adverse device effect rate was 2.30% (upper 1-sided 98% CI: 4.80); none were severe. No device-related deaths or serious adverse events were reported. The inappropriate shock rate was 0.36/100 patient-months (upper 1-sided 98% CI: 1.53). Of 11 shocks in 9 patients, 9 shocks were adjudicated to be appropriate. Eight of 9 shocks were successful with a single shock. Median wear time compliance was 23.5 (20.7-23.9) h/d. CONCLUSIONS: The novel P-WCD is a safe and effective WCD with high patient compliance. There were no deaths due to noncompliance and a high number of successful conversions (Jewel IDE study [A Clinical Evaluation of the Jewel P-WCD in Subjects at High Risk for Sudden Cardiac Arrest]; NCT05201495).

Incidence and temporal evolution of delayed peridevice leak after left atrial appendage closure.

BACKGROUND: Peridevice leak (PDL) after left atrial appendage closure (LAAC) portends adverse outcomes. OBJECTIVE: The purpose of this study was to assess the incidence, predictors, clinical implications, and temporal evolution of PDL after LAAC. METHODS: This single-center retrospective study included all patients who underwent LAAC with Watchman FLX and had no PDL detected at the time of implantation. The primary end point was the incidence of new PDL at initial imaging. The composite secondary end point included continued oral anticoagulation after initial imaging, device-related thrombus, stroke or transient ischemic attack, major bleeding, and need for PDL closure at longest follow-up. Temporal evolution of PDL was assessed in patients with available surveillance imaging. RESULTS: Of the 355 patients who completed imaging at 47 days (interquartile range [IQR] 44-50 days), 139 (39%) had new PDL with a mean leak size of 3.2 ± 1.4 mm (median 3.0 mm; IQR 2.0-4.0 mm; range 1.0-9.0 mm). Multiple deployment attempts and larger device size were positive predictors of PDL, while increased contrast volume administration was a negative predictor of PDL. The composite secondary end point occurred in 42 (30%) patients with PDL and 33 (15%) patients without PDL (P < .001). Of the 139 patients with PDL, 43 (31%) had surveillance imaging where the leak size regressed from 3.7 ± 1.8 mm at 46 days (IQR 44-51 days) to 1.7 ± 2.0 mm at 189 days (IQR 158-285 days) (P < .001). The leak size regressed in 33 (77%), remained stable in 4 (9%), and progressed in 6 (14%) cases. CONCLUSION: Despite design improvements, LAAC with Watchman FLX demonstrates a significant incidence of PDL with meaningful clinical implications. Regardless of initial size, most leaks regressed over time.

Dual-energy lattice-tip ablation system for persistent atrial fibrillation: a randomized trial.

Clinical outcomes of catheter ablation for atrial fibrillation (AF) are suboptimal due, in part, to challenges in achieving durable lesions. Although focal point-by-point ablation allows for the creation of any required lesion set, this strategy necessitates the generation of contiguous lesions without gaps. A large-tip catheter, capable of creating wide-footprint ablation lesions, may increase ablation effectiveness and efficiency. In a randomized, single-blind, non-inferiority trial, 420 patients with persistent AF underwent ablation using a large-tip catheter with dual pulsed field and radiofrequency energies versus ablation using a conventional radiofrequency ablation system. The primary composite effectiveness endpoint was evaluated through 1 year and included freedom from acute procedural failure and repeat ablation at any time, plus arrhythmia recurrence, drug initiation or escalation or cardioversion after a 3-month blanking period. The primary safety endpoint was freedom from a composite of serious procedure-related or device-related adverse events. The primary effectiveness endpoint was observed for 73.8% and 65.8% of patients in the investigational and control arms, respectively (P < 0.0001 for non-inferiority). Major procedural or device-related complications occurred in three patients in the investigational arm and in two patients in the control arm (P < 0.0001 for non-inferiority). In a secondary analysis, procedural times were shorter in the investigational arm as compared to the control arm (P < 0.0001). These results demonstrate non-inferior safety and effectiveness of the dual-energy catheter for the treatment of persistent AF. Future large-scale studies are needed to gather real-world evidence on the impact of the focal dual-energy lattice catheter on the broader population of patients with AF. ClinicalTrials.gov identifier: NCT05120193 .

EsophAguS Deviation During RadiofrequencY Ablation of Atrial Fibrillation: The EASY AF Trial.

BACKGROUND: Injury to the esophagus has been reported in a high percentage of patients undergoing ablation of atrial fibrillation (AF). OBJECTIVES: This study assessed the incidence of esophageal injury in patients undergoing ablation of AF with and without an esophageal deviating device. METHODS: This prospective, randomized, multicenter, double-blinded, controlled Food and Drug Administration investigational device exemption trial compared the incidence of ablation-related esophageal lesions, as assessed by endoscopy, in patients undergoing AF ablation assigned to a control group (luminal esophageal temperature [LET] monitoring alone) compared with patients randomized to a deviation group (esophagus deviation device + LET). This novel deviating device uses vacuum suction and mechanical deflection to deviate a segment of the esophagus, including the trailing edge. RESULTS: The data safety and monitoring board recommended stopping the study early after randomizing 120 patients due to deviating device efficacy. The primary study endpoint, ablation injury to the esophageal mucosa, was significantly less in the deviation group (5.7%) in comparison to the control group (35.4%; P < 0.0001). Control patients had a significantly higher severity and greater number of ablation lesions per patient. There was no adverse event assigned to the device. By multivariable analysis, the only feature associated with reduced esophageal lesions was randomization to deviating device (OR: 0.13; 95% CI: 0.04-0.46; P = 0.001). Among control subjects, there was no difference in esophageal lesions with high power/short duration (31.8%) vs other radiofrequency techniques (37.2%; P = 0.79). CONCLUSIONS: The use of an esophageal deviating device resulted in a significant reduction in ablation-related esophageal lesions without any adverse events.

Agent-based simulation and child protection systems: Rationale, implementation, and verification.

BACKGROUND AND OBJECTIVE: Simulation models are an important tool used in health care and other disciplines to support operational research and decision-making. In the child protection literature, simulation models are an under-utilized source of research evidence. PARTICIPANTS AND SETTING: In this paper, we describe the rationale for and the development of an agent-based simulation of a child protection system in the US. Using the investigation, prevention service, and placement histories of 600,000 children served in an urban child welfare system, we walk the reader through the development of a prototype known as OSPEDALE. METHODS: The governing equations built into OSPEDALE probabilistically simulate the onset of investigations. Then, drawing from empirical survival distributions, the governing equations trace the probability of subsequent interactions with the system (recurrence of maltreatment, service referrals, and placement) conditional on the characteristics of children, their assessed risk level, and prior child protection system involvement. RESULTS: As an initial test of OSPEDALE's utility, we compare empirical admission counts with counts generated from OSPEDALE. Though the verification step is admittedly simple, the comparison shows that OSPEDALE replicates the empirical count of new admissions closely enough to justify further investment in OSPEDALE. CONCLUSIONS: Management of public child protection systems is increasingly research evidence-dependent. The emphasis on research evidence as a decision-support tool has elevated evidence acquired through randomized clinical trials. Though important, the evidence from clinical trials represents only one type of research evidence. Properly specified, simulation models are another source of evidence with real-world relevance.

Clarifying status of DNNs as models of human vision.

On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN-human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in the literature. In our view, these latter issues are contributing to many unjustified claims regarding DNN-human correspondences in vision and other domains of cognition. We explore all these issues in this response.

Human shape representations are not an emergent property of learning to classify objects.

Humans are particularly sensitive to relationships between parts of objects. It remains unclear why this is. One hypothesis is that relational features are highly diagnostic of object categories and emerge as a result of learning to classify objects. We tested this by analyzing the internal representations of supervised convolutional neural networks (CNNs) trained to classify large sets of objects. We found that CNNs do not show the same sensitivity to relational changes as previously observed for human participants. Furthermore, when we precisely controlled the deformations to objects, human behavior was best predicted by the number of relational changes while CNNs were equally sensitive to all changes. Even changing the statistics of the learning environment by making relations uniquely diagnostic did not make networks more sensitive to relations in general. Our results show that learning to classify objects is not sufficient for the emergence of human shape representations. Instead, these results suggest that humans are selectively sensitive to relational changes because they build representations of distal objects from their retinal images and interpret relational changes as changes to these distal objects. This inferential process makes human shape representations qualitatively different from those of artificial neural networks optimized to perform image classification. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

NIR-II Nanoprobes: A Review of Components-Based Approaches to Next-Generation Bioimaging Probes.

Fluorescence and photoacoustic imaging techniques offer valuable insights into cell- and tissue-level processes. However, these optical imaging modalities are limited by scattering and absorption in tissue, resulting in the low-depth penetration of imaging. Contrast-enhanced imaging in the near-infrared window improves imaging penetration by taking advantage of reduced autofluorescence and scattering effects. Current contrast agents for fluorescence and photoacoustic imaging face several limitations from photostability and targeting specificity, highlighting the need for a novel imaging probe development. This review covers a broad range of near-infrared fluorescent and photoacoustic contrast agents, including organic dyes, polymers, and metallic nanostructures, focusing on their optical properties and applications in cellular and animal imaging. Similarly, we explore encapsulation and functionalization technologies toward building targeted, nanoscale imaging probes. Bioimaging applications such as angiography, tumor imaging, and the tracking of specific cell types are discussed. This review sheds light on recent advancements in fluorescent and photoacoustic nanoprobes in the near-infrared window. It serves as a valuable resource for researchers working in fields of biomedical imaging and nanotechnology, facilitating the development of innovative nanoprobes for improved diagnostic approaches in preclinical healthcare.

Direct current cardioversion practices following percutaneous left atrial appendage closure.

INTRODUCTION: Among patients with non-valvular atrial fibrillation (AF) and percutaneous left atrial appendage closure (LAAC) undergoing direct current cardioversion (DCCV), the need for and use of LAA imaging and oral anticoagulation (OAC) is unclear. OBJECTIVE: The purpose of this study is to evaluate the real-world use of transesophageal echocardiography (TEE) or cardiac computed tomography angiography (CCTA) before DCCV and use of OAC pre- and post-DCCV in patients with AF status post percutaneous LAAC. METHODS: This retrospective single center study included all patients who underwent DCCV after percutaneous LAAC from 2016 to 2022. Key measures were completion of TEE or CCTA pre-DCCV, OAC use pre- and post-DCCV, incidence of left atrial thrombus (LAT) or device-related thrombus (DRT), incidence of peri-device leak (PDL), and DCCV-related complications (stroke, systemic embolism, device embolization, major bleeding, or death) within 30 days. RESULTS: A total of 76 patients with AF and LAAC underwent 122 cases of DCCV. LAAC consisted of 47 (62%), 28 (37%), and 1 (1%) case of Watchman 2.5, Watchman FLX, and Lariat, respectively. Among the 122 DCCV cases, 31 (25%) cases were identified as "non-guideline based" due to: (1) no OAC for 3 weeks and no LAA imaging within 48 h before DCCV in 12 (10%) cases, (2) no OAC for 4 weeks following DCCV in 16 (13%) cases, or (3) both in 3 (2%) cases. Among the 70 (57%) cases that underwent TEE or CCTA before DCCV, 16 (23%) cases had a PDL with a mean size of 3.0 ± 1.1 mm, and 4 (6%) cases had a LAT/DRT on TEE resulting in cancellation. There were no DCCV-related complications within 30 days. DISCUSSION: There is a widely varied practice pattern of TEE, CCTA, and OAC use with DCCV after LAAC, with a 6% rate of LAT/DRT. LAA imaging before DCCV appears prudent in all cases, especially within 1 year of LAAC, to assess for device position, PDL, and LAT/DRT.

An experimental and simulation study of the impact of emotional information on analogical reasoning.

We investigated whether and how emotional information would affect analogical reasoning. We hypothesized that task-irrelevant emotional information would impair performance whereas task-relevant emotional information would enhance it. In Study 1, 233 undergraduates completed a novel version of the People Pieces Task (Emotional Faces People Task), an analogical reasoning task in which the task characters displayed emotional or neutral facial expressions (within-participants). The emotional faces were relevant or irrelevant to the task (between-participants). We simulated the behavioral results using the Learning and Inference with Schemas and Analogies (LISA) model of relational reasoning. LISA is a neurally plausible, symbolic-connectionist computational model of analogical reasoning. In comparison to neutral trials, participants were slower but more accurate on emotion-relevant trials, and were faster but less accurate on emotion-irrelevant trials. Simulations using the LISA model demonstrated that it is possible to account for the effects of emotional information on reasoning in terms of how emotional stimuli attract attention during a reasoning task. In Study 2, 255 undergraduates completed the Emotional Faces People Task at either a high- or low-working memory load. The high working memory load condition of Study 2 replicated the findings of Study 1, showing that participants were more accurate on emotion-relevant trials than on emotion-irrelevant trials; in Study 2, this increased accuracy could not be accounted for by a speed-accuracy tradeoff. The working memory manipulation influenced the manner in which the congruence (with the correct answer) of emotion-irrelevant emotion influenced performance. Simulations using the LISA model showed that manipulating the salience of emotion, the error penalty, as well as vigilance (which determines the likelihood that LISA will notice it has attended to an irrelevant relation), could reasonably reproduce the behavioral results of both low and high working memory load conditions of Study 2.

Cardiac magnetic resonance imaging for left atrial appendage closure planning.

BACKGROUND: Transesophageal echocardiography (TEE) and cardiac computed tomography angiography (CCTA) are currently utilized for left atrial appendage closure (LAAC) planning. During the recent global iodine contrast media shortage in 2022, cardiac magnetic resonance imaging (CMR) was utilized for the first time for LAAC planning. This study sought to assess the utility of CMR versus TEE for LAAC planning. METHODS: This single center retrospective study consisted of all patients who underwent preoperative CMR for LAAC with Watchman FLX or Amplatzer Amulet. Key measures were accuracy of LAA thrombus exclusion, ostial diameter, depth, lobe count, morphology, accuracy of predicted device size, and devices deployed per case. Bland-Altman Analysis was used to compare CMR versus TEE measurements of LAA ostial diameter and depth. RESULTS: 25 patients underwent preoperative CMR for LAAC planning. A total of 24 (96%) cases were successfully completed with 1.2 ± 0.5 devices deployed per case. Among the 18 patients who underwent intraoperative TEE, there was no significant difference between CMR versus TEE in LAA thrombus exclusion (CMR 83% vs. TEE 100% cases, p = .229), lobe count (CMR 1.7 ± 0.8 vs. TEE 1.4 ± 0.6, p = .177), morphology (p = .422), and accuracy of predicted device size (CMR 67% vs. TEE 72% cases, p = 1.000). When comparing the difference between CMR and TEE measurements, Bland-Altman analysis demonstrated no significant difference in LAA ostial diameter (CMR-TEE bias 0.7 mm, 95% CI [-1.1, 2.4], p = .420), but LAA depth was significantly larger with CMR versus TEE (CMR-TEE bias 7.4 mm, 95% CI [1.6, 13.2], p = .015). CONCLUSIONS: CMR is a promising alternative for LAAC planning in cases where TEE or CCTA are contraindicated or unavailable.

Three-dimensional functional anatomy of the human sinoatrial node for epicardial and endocardial mapping and ablation.

The sinoatrial node (SAN) is the primary pacemaker of the human heart. It is a single, elongated, 3-dimensional (3D) intramural fibrotic structure located at the junction of the superior vena cava intercaval region bordering the crista terminalis (CT). SAN activation originates in the intranodal pacemakers and is conducted to the atria through 1 or more discrete sinoatrial conduction pathways. The complexity of the 3D SAN pacemaker structure and intramural conduction are underappreciated during clinical multielectrode mapping and ablation procedures of SAN and atrial arrhythmias. In fact, defining and targeting SAN is extremely challenging because, even during sinus rhythm, surface-only multielectrode mapping may not define the leading pacemaker sites in intramural SAN but instead misinterpret them as epicardial or endocardial exit sites through sinoatrial conduction pathways. These SAN exit sites may be distributed up to 50 mm along the CT beyond the ∼20-mm-long anatomic SAN structure. Moreover, because SAN reentrant tachycardia beats may exit through the same sinoatrial conduction pathway as during sinus rhythm, many SAN arrhythmias are underdiagnosed. Misinterpretation of arrhythmia sources and/or mechanisms (eg, enhanced automaticity, intranodal vs CT reentry) limits diagnosis and success of catheter ablation treatments for poorly understood SAN arrhythmias. The aim of this review is to provide a state-of-the-art overview of the 3D structure and function of the human SAN complex, mechanisms of SAN arrhythmias and available approaches for electrophysiological mapping, 3D structural imaging, pharmacologic interventions, and ablation to improve diagnosis and mechanistic treatment of SAN and atrial arrhythmias.

Deep problems with neural network models of human vision.

Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting brain signals in response to images taken from various brain datasets (e.g., single cell responses or fMRI data). However, these behavioral and brain datasets do not test hypotheses regarding what features are contributing to good predictions and we show that the predictions may be mediated by DNNs that share little overlap with biological vision. More problematically, we show that DNNs account for almost no results from psychological research. This contradicts the common claim that DNNs are good, let alone the best, models of human object recognition. We argue that theorists interested in developing biologically plausible models of human vision need to direct their attention to explaining psychological findings. More generally, theorists need to build models that explain the results of experiments that manipulate independent variables designed to test hypotheses rather than compete on making the best predictions. We conclude by briefly summarizing various promising modeling approaches that focus on psychological data.

Advances in Cardiac Electrophysiology.

Despite the global COVID-19 pandemic, during the past 2 years, there have been numerous advances in our understanding of arrhythmia mechanisms and diagnosis and in new therapies. We increased our understanding of risk factors and mechanisms of atrial arrhythmias, the prediction of atrial arrhythmias, response to treatment, and outcomes using machine learning and artificial intelligence. There have been new technologies and techniques for atrial fibrillation ablation, including pulsed field ablation. There have been new randomized trials in atrial fibrillation ablation, giving insight about rhythm control, and long-term outcomes. There have been advances in our understanding of treatment of inherited disorders such as catecholaminergic polymorphic ventricular tachycardia. We have gained new insights into the recurrence of ventricular arrhythmias in the setting of various conditions such as myocarditis and inherited cardiomyopathic disorders. Novel computational approaches may help predict occurrence of ventricular arrhythmias and localize arrhythmias to guide ablation. There are further advances in our understanding of noninvasive radiotherapy. We have increased our understanding of the role of His bundle pacing and left bundle branch area pacing to maintain synchronous ventricular activation. There have also been significant advances in the defibrillators, cardiac resynchronization therapy, remote monitoring, and infection prevention. There have been advances in our understanding of the pathways and mechanisms involved in atrial and ventricular arrhythmogenesis.

Feasibility of Assessing Cryoballoon Pulmonary Vein Occlusion With Saline Injection and a Novel Mapping System.

Thirty-eight patients had assessment of pulmonary vein occlusion with the dielectric mapping system and injection of saline as an alternative to contrast. Contrast injection was required to ascertain pulmonary vein occlusion in 31.6% (12 of 38) of subjects and 17.4% (27 of 155) of veins. No contrast was required in the last 13 subjects. In this single center study, a novel mapping-guided cryoablation approach appeared to minimize the use of contrast in pulmonary vein isolation for the treatment of atrial fibrillation.

A theory of relation learning and cross-domain generalization.

People readily generalize knowledge to novel domains and stimuli. We present a theory, instantiated in a computational model, based on the idea that cross-domain generalization in humans is a case of analogical inference over structured (i.e., symbolic) relational representations. The model is an extension of the Learning and Inference with Schemas and Analogy (LISA; Hummel & Holyoak, 1997, 2003) and Discovery of Relations by Analogy (DORA; Doumas et al., 2008) models of relational inference and learning. The resulting model learns both the content and format (i.e., structure) of relational representations from nonrelational inputs without supervision, when augmented with the capacity for reinforcement learning it leverages these representations to learn about individual domains, and then generalizes to new domains on the first exposure (i.e., zero-shot learning) via analogical inference. We demonstrate the capacity of the model to learn structured relational representations from a variety of simple visual stimuli, and to perform cross-domain generalization between video games (Breakout and Pong) and between several psychological tasks. We demonstrate that the model's trajectory closely mirrors the trajectory of children as they learn about relations, accounting for phenomena from the literature on the development of children's reasoning and analogy making. The model's ability to generalize between domains demonstrates the flexibility afforded by representing domains in terms of their underlying relational structure, rather than simply in terms of the statistical relations between their inputs and outputs. (PsycInfo Database Record (c) 2022 APA, all rights reserved).