The MutAnts Are Here.

The development of CRISPR/Cas9-mediated gene knockout in two ant species opens a new window into exploring how social insects use olfactory cues to organize their collective behavior.

Thermophotovoltaic efficiency of 40.

Thermophotovoltaics (TPVs) convert predominantly infrared wavelength light to electricity via the photovoltaic effect, and can enable approaches to energy storage1,2 and conversion3-9 that use higher temperature heat sources than the turbines that are ubiquitous in electricity production today. Since the first demonstration of 29% efficient TPVs (Fig. 1a) using an integrated back surface reflector and a tungsten emitter at 2,000 °C (ref. 10), TPV fabrication and performance have improved11,12. However, despite predictions that TPV efficiencies can exceed 50% (refs. 11,13,14), the demonstrated efficiencies are still only as high as 32%, albeit at much lower temperatures below 1,300 °C (refs. 13-15). Here we report the fabrication and measurement of TPV cells with efficiencies of more than 40% and experimentally demonstrate the efficiency of high-bandgap tandem TPV cells. The TPV cells are two-junction devices comprising III-V materials with bandgaps between 1.0 and 1.4 eV that are optimized for emitter temperatures of 1,900-2,400 °C. The cells exploit the concept of band-edge spectral filtering to obtain high efficiency, using highly reflective back surface reflectors to reject unusable sub-bandgap radiation back to the emitter. A 1.4/1.2 eV device reached a maximum efficiency of (41.1 ± 1)% operating at a power density of 2.39 W cm-2 and an emitter temperature of 2,400 °C. A 1.2/1.0 eV device reached a maximum efficiency of (39.3 ± 1)% operating at a power density of 1.8 W cm-2 and an emitter temperature of 2,127 °C. These cells can be integrated into a TPV system for thermal energy grid storage to enable dispatchable renewable energy. This creates a pathway for thermal energy grid storage to reach sufficiently high efficiency and sufficiently low cost to enable decarbonization of the electricity grid.

Distributed feedforward and feedback cortical processing supports human speech production.

Speech production is a complex human function requiring continuous feedforward commands together with reafferent feedback processing. These processes are carried out by distinct frontal and temporal cortical networks, but the degree and timing of their recruitment and dynamics remain poorly understood. We present a deep learning architecture that translates neural signals recorded directly from the cortex to an interpretable representational space that can reconstruct speech. We leverage learned decoding networks to disentangle feedforward vs. feedback processing. Unlike prevailing models, we find a mixed cortical architecture in which frontal and temporal networks each process both feedforward and feedback information in tandem. We elucidate the timing of feedforward and feedback-related processing by quantifying the derived receptive fields. Our approach provides evidence for a surprisingly mixed cortical architecture of speech circuitry together with decoding advances that have important implications for neural prosthetics.

Temporal dynamics of short-term neural adaptation across human visual cortex.

Neural responses in visual cortex adapt to prolonged and repeated stimuli. While adaptation occurs across the visual cortex, it is unclear how adaptation patterns and computational mechanisms differ across the visual hierarchy. Here we characterize two signatures of short-term neural adaptation in time-varying intracranial electroencephalography (iEEG) data collected while participants viewed naturalistic image categories varying in duration and repetition interval. Ventral- and lateral-occipitotemporal cortex exhibit slower and prolonged adaptation to single stimuli and slower recovery from adaptation to repeated stimuli compared to V1-V3. For category-selective electrodes, recovery from adaptation is slower for preferred than non-preferred stimuli. To model neural adaptation we augment our delayed divisive normalization (DN) model by scaling the input strength as a function of stimulus category, enabling the model to accurately predict neural responses across multiple image categories. The model fits suggest that differences in adaptation patterns arise from slower normalization dynamics in higher visual areas interacting with differences in input strength resulting from category selectivity. Our results reveal systematic differences in temporal adaptation of neural population responses between lower and higher visual brain areas and show that a single computational model of history-dependent normalization dynamics, fit with area-specific parameters, accounts for these differences.

Severe mental illness: cardiovascular risk assessment and management.

Patients with severe mental illness (SMI) including schizophrenia and bipolar disorder die on average 15-20 years earlier than the general population often due to sudden death that, in most cases, is caused by cardiovascular disease. This state-of-the-art review aims to address the complex association between SMI and cardiovascular risk, explore disparities in cardiovascular care pathways, describe how to adequately predict cardiovascular outcomes, and propose targeted interventions to improve cardiovascular health in patients with SMI. These patients have an adverse cardiovascular risk factor profile due to an interplay between biological factors such as chronic inflammation, patient factors such as excessive smoking, and healthcare system factors such as stigma and discrimination. Several disparities in cardiovascular care pathways have been demonstrated in patients with SMI, resulting in a 47% lower likelihood of undergoing invasive coronary procedures and substantially lower rates of prescribed standard secondary prevention medications compared with the general population. Although early cardiovascular risk prediction is important, conventional risk prediction models do not accurately predict long-term cardiovascular outcomes as cardiovascular disease and mortality are only partly driven by traditional risk factors in this patient group. As such, SMI-specific risk prediction models and clinical tools such as the electrocardiogram and echocardiogram are necessary when assessing and managing cardiovascular risk associated with SMI. In conclusion, there is a necessity for differentiated cardiovascular care in patients with SMI. By addressing factors involved in the excess cardiovascular risk, reconsidering risk stratification approaches, and implementing multidisciplinary care models, clinicians can take steps towards improving cardiovascular health and long-term outcomes in patients with SMI.

Cardiac Resynchronization Therapy Improves Outcomes in Patients With Intraventricular Conduction Delay But Not Right Bundle Branch Block: A Patient-Level Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Benefit from cardiac resynchronization therapy (CRT) varies by QRS characteristics; individual randomized trials are underpowered to assess benefit for relatively small subgroups. METHODS: The authors analyzed patient-level data from pivotal CRT trials (MIRACLE [Multicenter InSync Randomized Clinical Evaluation], MIRACLE-ICD [Multicenter InSync ICD Randomized Clinical Evaluation], MIRACLE-ICD II [Multicenter InSync ICD Randomized Clinical Evaluation II], REVERSE [Resynchronization Reverses Remodeling in Systolic Left Ventricular Dysfunction], RAFT [Resynchronization-Defibrillation for Ambulatory Heart Failure], BLOCK-HF [Biventricular Versus Right Ventricular Pacing in Heart Failure Patients with Atrioventricular Block], COMPANION [Comparison of Medical Therapy, Pacing and Defibrillation in Heart Failure], and MADIT-CRT [Multicenter Automatic Defibrillator Implantation Trial - Cardiac Resynchronization Therapy]) using Bayesian Hierarchical Weibull survival regression models to assess CRT benefit by QRS morphology (left bundle branch block [LBBB], n=4549; right bundle branch block [RBBB], n=691; and intraventricular conduction delay [IVCD], n=1024) and duration (with 150-ms partition). The continuous relationship between QRS duration and CRT benefit was also examined within subgroups defined by QRS morphology. The primary end point was time to heart failure hospitalization (HFH) or death; a secondary end point was time to all-cause death. RESULTS: Of 6264 patients included, 25% were women, the median age was 66 [interquartile range, 58 to 73] years, and 61% received CRT (with or without an implantable cardioverter defibrillator). CRT was associated with an overall lower risk of HFH or death (hazard ratio [HR], 0.73 [credible interval (CrI), 0.65 to 0.84]), and in subgroups of patients with QRS ≥150 ms and either LBBB (HR, 0.56 [CrI, 0.48 to 0.66]) or IVCD (HR, 0.59 [CrI, 0.39 to 0.89]), but not RBBB (HR 0.97 [CrI, 0.68 to 1.34]; Pinteraction <0.001). No significant association for CRT with HFH or death was observed when QRS was <150 ms (regardless of QRS morphology) or in the presence of RBBB. Similar relationships were observed for all-cause death. CONCLUSIONS: CRT is associated with reduced HFH or death in patients with QRS ≥150 ms and LBBB or IVCD, but not for those with RBBB. Aggregating RBBB and IVCD into a single "non-LBBB" category when selecting patients for CRT should be reconsidered. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifiers: NCT00271154, NCT00251251, NCT00267098, and NCT00180271.

Benefit of cardiac resynchronization therapy among older patients: A patient-level meta-analysis.

BACKGROUND: Cardiac resynchronization therapy (CRT) reduces heart failure hospitalizations (HFH) and mortality for guideline-indicated patients with heart failure (HF). Most patients with HF are aged ≥70 years but such patients are often under-represented in randomized trials. METHODS: Patient-level data were combined from 8 randomized trials published 2002-2013 comparing CRT to no CRT (n = 6,369). The effect of CRT was estimated using an adjusted Bayesian survival model. Using age as a categorical (<70 vs ≥70 years) or continuous variable, the interaction between age and CRT on the composite end point of HFH or all-cause mortality or all-cause mortality alone was assessed. RESULTS: The median age was 67 years with 2436 (38%) being 70+; 1,554 (24%) were women; 2,586 (41%) had nonischemic cardiomyopathy and median QRS duration was 160 ms. Overall, CRT was associated with a delay in time to the composite end point (adjusted hazard ratio [aHR] 0.75, 95% credible interval [CI] 0.66-0.85, P = .002) and all-cause mortality alone (aHR of 0.80, 95% CI 0.69-0.96, P = .017). When age was treated as a categorical variable, there was no interaction between age and the effect of CRT for either end point (P > .1). When age was treated as a continuous variable, older patients appeared to obtain greater benefit with CRT for the composite end point (P for interaction = .027) with a similar but nonsignificant trend for mortality (P for interaction = .35). CONCLUSION: Reductions in HFH and mortality with CRT are as great or greater in appropriately indicated older patients. Age should not be a limiting factor for the provision of CRT.

Peak frequency mapping of atypical atrial flutter.

INTRODUCTION: Peak frequency (PF) mapping is a novel method that may identify critical portions of myocardial substrate supporting reentry. The aim of this study was to describe and evaluate PF mapping combined with omnipolar voltage mapping in the identification of critical isthmuses of left atrial (LA) atypical flutters. METHODS AND RESULTS: LA omnipolar voltage and PF maps were generated in flutter using the Advisor HD-Grid catheter (Abbott) and EnSite Precision Mapping System (Abbott) in 12 patients. Normal voltage was defined as ≥0.5 mV, low-voltage as 0.1-0.5 mV, and scar as <0.1 mV. PF distributions were compared with ANOVA and post hoc Tukey analyses. The 1 cm radius from arrhythmia termination was compared to global myocardium with unpaired t-testing. The mean age was 65.8 ± 9.7 years and 50% of patients were female. Overall, 34 312 points were analyzed. Atypical flutters most frequently involved the mitral isthmus (58%) or anterior wall (25%). Mean PF varied significantly by myocardial voltage: normal (335.5 ± 115.0 Hz), low (274.6 ± 144.0 Hz), and scar (71.6 ± 140.5 Hz) (p < .0001 for all pairwise comparisons). All termination sites resided in low-voltage regions containing intermediate or high PF. Overall, mean voltage in the 1 cm radius from termination was significantly lower than the remaining myocardium (0.58 vs. 0.95 mV, p < .0001) and PF was significantly higher (326.4 vs. 245.1 Hz, p < .0001). CONCLUSION: Low-voltage, high-PF areas may be critical targets during catheter ablation of atypical atrial flutter.

Racial disparities in the utilization of invasive neuromodulation devices for the treatment of drug-resistant focal epilepsy.

Racial disparities affect multiple dimensions of epilepsy care including epilepsy surgery. This study aims to further explore these disparities by determining the utilization of invasive neuromodulation devices according to race and ethnicity in a multicenter study of patients living with focal drug-resistant epilepsy (DRE). We performed a post hoc analysis of the Human Epilepsy Project 2 (HEP2) data. HEP2 is a prospective study of patients living with focal DRE involving 10 sites distributed across the United States. There were no statistical differences in the racial distribution of the study population compared to the US population using census data except for patients reporting more than one race. Of 154 patients enrolled in HEP2, 55 (36%) underwent invasive neuromodulation for DRE management at some point in the course of their epilepsy. Of those, 36 (71%) were patients who identified as White. Patients were significantly less likely to have a device if they identified solely as Black/African American than if they did not (odds ratio = .21, 95% confidence interval = .05-.96, p = .03). Invasive neuromodulation for management of DRE is underutilized in the Black/African American population, indicating a new facet of racial disparities in epilepsy care.

Outcomes in solid organ transplant recipients receiving organs from a donor with Fusarium solani species complex meningitis.

BACKGROUND: Five organs (heart, right lung, liver, right, and left kidneys) from a deceased patient were transplanted into five recipients in four US states; the deceased patient was identified as part of a healthcare-associated fungal meningitis outbreak among patients who underwent epidural anesthesia in Matamoros, Mexico. METHODS: After transplant surgeries occurred, Fusarium solani species complex, a fungal pathogen with a high case-mortality rate, was identified in cerebrospinal fluid from the organ donor by metagenomic next-generation sequencing (mNGS) and fungal-specific polymerase chain reaction and in plasma by mNGS. RESULTS: Four of five transplant recipients received recommended voriconazole prophylaxis; four were monitored weekly by serum (1-3)-ß-d-glucan testing. All five were monitored for signs of infection for at least 3 months following transplantation. The liver recipient had graft failure, which was attributed to an etiology unrelated to fungal infection. No fungal DNA was identified in sections of the explanted liver, suggesting that F. solani species complex did not contribute to graft failure. The remaining recipients experienced no signs or symptoms suggestive of fusariosis. CONCLUSION: Antifungal prophylaxis may be useful in preventing donor-derived infections in recipients of organs from donors that are found to have Fusarium meningitis.

Artificial intelligence/machine learning for epilepsy and seizure diagnosis.

Accurate seizure and epilepsy diagnosis remains a challenging task due to the complexity and variability of manifestations, which can lead to delayed or missed diagnosis. Machine learning (ML) and artificial intelligence (AI) is a rapidly developing field, with growing interest in integrating and applying these tools to aid clinicians facing diagnostic uncertainties. ML algorithms, particularly deep neural networks, are increasingly employed in interpreting electroencephalograms (EEG), neuroimaging, wearable data, and seizure videos. This review discusses the development and testing phases of AI/ML tools, emphasizing the importance of generalizability and interpretability in medical applications, and highlights recent publications that demonstrate the current and potential utility of AI to aid clinicians in diagnosing epilepsy. Current barriers of AI integration in patient care include dataset availability and heterogeneity, which limit studies' quality, interpretability, comparability, and generalizability. ML and AI offer substantial promise in improving the accuracy and efficiency of epilepsy diagnosis. The growing availability of diverse datasets, enhanced processing speed, and ongoing efforts to standardize reporting contribute to the evolving landscape of AI applications in clinical care.

The influence of risk factors, biomarkers and care settings on SUDEP counseling.

Although sudden unexpected death in epilepsy (SUDEP) is the most feared epilepsy outcome, there is a dearth of SUDEP counseling provided by neurologists. This may reflect limited time, as well as the lack of guidance on the timing and structure for counseling. We evaluated records from SUDEP cases to examine frequency of inpatient and outpatient SUDEP counseling, and whether counseling practices were influenced by risk factors and biomarkers, such as post-ictal generalized EEG suppression (PGES). We found a striking lack of SUDEP counseling despite modifiable SUDEP risk factors; counseling was limited to outpatients despite many patients having inpatient visits within a year of SUDEP. PGES was inconsistently documented and was never included in counseling. There is an opportunity to greatly improve SUDEP counseling by utilizing inpatient settings and prompting algorithms incorporating risk factors and biomarkers.

Mortality and mortality disparities among people with epilepsy in the United States, 2011-2021.

Studies on epilepsy mortality in the United States are limited. We used the National Vital Statistics System Multiple Cause of Death data to investigate mortality rates and trends during 2011-2021 for epilepsy (defined by the International Classification of Diseases, 10th Revision, codes G40.0-G40.9) as an underlying, contributing, or any cause of death (i.e., either an underlying or contributing cause) for U.S. residents. We also examined epilepsy as an underlying or contributing cause of death by selected sociodemographic characteristics to assess mortality rate changes and disparities in subpopulations. During 2011-2021, the overall age-standardized mortality rates for epilepsy as an underlying (39 % of all deaths) or contributing (61 % of all deaths) cause of death increased 83.6 % (from 2.9 per million to 6.4 per million population) as underlying cause and 144.1 % (from 3.3 per million to 11.0 per million population) as contributing cause (P < 0.001 for both based on annual percent changes). Compared to 2011-2015, in 2016-2020 mortality rates with epilepsy as an underlying or contributing cause of death were higher overall and in nearly all subgroups. Overall, mortality rates with epilepsy as an underlying or contributing cause of death were higher in older age groups, among males than females, among non-Hispanic Black or non-Hispanic American Indian/Alaska Native persons than non-Hispanic White persons, among those living in the West and Midwest than those living in the Northeast, and in nonmetro counties compared to urban regions. Results identify priority subgroups for intervention to reduce mortality in people with epilepsy and eliminate mortality disparity.

Shared Protentions in Multi-Agent Active Inference.

In this paper, we unite concepts from Husserlian phenomenology, the active inference framework in theoretical biology, and category theory in mathematics to develop a comprehensive framework for understanding social action premised on shared goals. We begin with an overview of Husserlian phenomenology, focusing on aspects of inner time-consciousness, namely, retention, primal impression, and protention. We then review active inference as a formal approach to modeling agent behavior based on variational (approximate Bayesian) inference. Expanding upon Husserl's model of time consciousness, we consider collective goal-directed behavior, emphasizing shared protentions among agents and their connection to the shared generative models of active inference. This integrated framework aims to formalize shared goals in terms of shared protentions, and thereby shed light on the emergence of group intentionality. Building on this foundation, we incorporate mathematical tools from category theory, in particular, sheaf and topos theory, to furnish a mathematical image of individual and group interactions within a stochastic environment. Specifically, we employ morphisms between polynomial representations of individual agent models, allowing predictions not only of their own behaviors but also those of other agents and environmental responses. Sheaf and topos theory facilitates the construction of coherent agent worldviews and provides a way of representing consensus or shared understanding. We explore the emergence of shared protentions, bridging the phenomenology of temporal structure, multi-agent active inference systems, and category theory. Shared protentions are highlighted as pivotal for coordination and achieving common objectives. We conclude by acknowledging the intricacies stemming from stochastic systems and uncertainties in realizing shared goals.

Temporal Dynamics of Neural Responses in Human Visual Cortex.

Neural responses to visual stimuli exhibit complex temporal dynamics, including subadditive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low contrast. These phenomena are often studied independently. Here, we demonstrate these phenomena within the same experiment and model the underlying neural computations with a single computational model. We extracted time-varying responses from electrocorticographic recordings from patients presented with stimuli that varied in duration, interstimulus interval (ISI) and contrast. Aggregating data across patients from both sexes yielded 98 electrodes with robust visual responses, covering both earlier (V1-V3) and higher-order (V3a/b, LO, TO, IPS) retinotopic maps. In all regions, the temporal dynamics of neural responses exhibit several nonlinear features. Peak response amplitude saturates with high contrast and longer stimulus durations, the response to a second stimulus is suppressed for short ISIs and recovers for longer ISIs, and response latency decreases with increasing contrast. These features are accurately captured by a computational model composed of a small set of canonical neuronal operations, that is, linear filtering, rectification, exponentiation, and a delayed divisive normalization. We find that an increased normalization term captures both contrast- and adaptation-related response reductions, suggesting potentially shared underlying mechanisms. We additionally demonstrate both changes and invariance in temporal response dynamics between earlier and higher-order visual areas. Together, our results reveal the presence of a wide range of temporal and contrast-dependent neuronal dynamics in the human visual cortex and demonstrate that a simple model captures these dynamics at millisecond resolution.SIGNIFICANCE STATEMENT Sensory inputs and neural responses change continuously over time. It is especially challenging to understand a system that has both dynamic inputs and outputs. Here, we use a computational modeling approach that specifies computations to convert a time-varying input stimulus to a neural response time course, and we use this to predict neural activity measured in the human visual cortex. We show that this computational model predicts a wide variety of complex neural response shapes, which we induced experimentally by manipulating the duration, repetition, and contrast of visual stimuli. By comparing data and model predictions, we uncover systematic properties of temporal dynamics of neural signals, allowing us to better understand how the brain processes dynamic sensory information.

Risk Factors and Outcomes of Invasive Aspergillosis in Kidney Transplant Recipients: A Case-Control Study of United States Renal Data System Data.

BACKGROUND: Kidney transplant recipients are at increased risk for invasive aspergillosis (IA), a disease with poor outcomes and substantial economic burden. We aimed to determine risk factors for posttransplant IA by using a national database and to assess the association of IA with mortality and allograft failure. METHODS: Using the United States Renal Data System database, we performed a retrospective case-control study of patients who underwent kidney transplant from 1998 through 2017. To evaluate risk factors for IA, we performed conditional logistic regression analysis by comparing characteristics between IA-infected patients and their matched uninfected controls. We performed Cox regression analysis to evaluate the effects of IA on mortality and death-censored allograft failure. RESULTS: We matched 359 patients with IA to 1436 uninfected controls (1:4). IA was diagnosed at a median of 22.5 months (interquartile range, 5.4-85.2 months) after kidney transplant. Risk factors for IA were Black/African American race, duration of pretransplant hemodialysis, higher Elixhauser Comorbidity Index score, weight loss, chronic pulmonary disease, need for early posttransplant hemodialysis, and a history of cytomegalovirus infection. Receiving an allograft from a living donor was protective against IA. IA was a strong independent predictor of 1-year mortality (adjusted hazard ratio [aHR], 5.02 [95% confidence interval {CI}, 3.58-7.04], P < .001). Additionally, IA was associated with 1-year allograft failure (aHR, 3.37 [95% CI, 1.96-5.77], P < .001). CONCLUSIONS: Our findings emphasize the importance of timely transplant to mitigate the risk of posttransplant IA. An individualized approach to disease prevention is essential to decrease mortality and allograft failure.

Natural killer cell immune synapse formation and cytotoxicity are controlled by tension of the target interface.

Natural killer (NK) cells can kill infected or transformed cells via a lytic immune synapse. Diseased cells may exhibit altered mechanical properties but how this impacts NK cell responsiveness is unknown. We report that human NK cells were stimulated more effectively to secrete granzymes A and B, FasL (also known as FasLG), granulysin and IFNγ, by stiff (142 kPa) compared to soft (1 kPa) planar substrates. To create surrogate spherical targets of defined stiffness, sodium alginate was used to synthesise soft (9 kPa), medium (34 kPa) or stiff (254 kPa) cell-sized beads, coated with antibodies against activating receptor NKp30 (also known as NCR3) and the integrin LFA-1 (also known as ITGAL). Against stiff beads, NK cells showed increased degranulation. Polarisation of the microtubule-organising centre and lytic granules were impaired against soft targets, which instead resulted in the formation of unstable kinapses. Thus, by varying target stiffness to characterise the mechanosensitivity of immune synapses, we identify soft targets as a blind spot in NK cell recognition. This article has an associated First Person interview with the co-first authors of the paper.

Rates and predictors of hospital and emergency department care after catheter ablation of atrial fibrillation.

INTRODUCTION: Although atrial fibrillation (AF) ablation has become increasingly safer, rehospitalization and emergency department (ED) evaluations can occur in the postablation period. Better understanding of the frequency, causes, and predictors for hospitalization and ED evaluation after ablation are needed, particularly as same-day discharge programs expand. METHODS: The Optum Clinformatics database was used to define rates, causes, and predictors of hospital and ED care after AF ablation performed between January 2016 and May 2019. Primary outcomes were all-cause hospital and ED care within 30 days of discharge. Independent predictors of all-cause ED and hospital admissions care were determined via logistic regression. RESULTS: Of the 18 848 patients in this study, the mean age was 67.5 ± 10 years, 37.9% were female, and the mean CHA2 DS2 -VASc score was 3.27 ± 1.84. Within 30 days of AF ablation, 1440 of 18 848 patients (7.6%) required hospital care of which 15% had >1 admission; 7.9% required ED care of which 28.6% had >1 ED visit. The most common reasons for hospital admission (which occurred on average 12.3 days after discharge) were supraventricular tachycardia (SVT) or AF (33.2%), heart failure (12.7%), and infection (12.2%). The most common reasons for ED care were SVT/AF (15.0%), noncardiac chest pain (13.3%), and noninfectious respiratory illness (12.2%). Age, female sex, ablation in an inpatient setting, and co-morbidities were associated with increased risk of rehospitalization. Age, female sex, patient comorbidities, and non-use of direct oral anticoagulation were associated with increased risk of ED visit. CONCLUSION: Approximately 7%-8% of patients require unplanned hospitalization or ED care after AF ablation, most commonly due to SVT/AF. Predictors of unscheduled care include patient age, sex, and several patient comorbidities. This study can inform quality improvement initiatives by identifying common causes for unscheduled care.

Watchman device migration and embolization: A report from the NCDR LAAO Registry.

INTRODUCTION: Incomplete anchoring of the Watchman left atrial appendage closure (LAAO) device can result in substantial device migration or device embolization (DME) requiring percutaneous or surgical retrieval. METHODS: We performed a retrospective analysis of Watchman procedures (January 2016 through March 2021) reported to the National Cardiovascular Data Registry LAAO Registry. We excluded patients with prior LAAO interventions, no device released, and missing device information. In-hospital events were assessed among all patients and postdischarge events were assessed among patients with 45-day follow-up. RESULTS: Of 120 278 Watchman procedures, the in-hospital DME rate was 0.07% (n = 84) and surgery was commonly performed (n = 39). In-hospital mortality rate was 14% among patients with DME and 20.5% among patients who underwent surgery. In-hospital DME was more common: at hospitals with a lower median annual procedure volume (24 vs. 41 procedures, p < .0001), with Watchman 2.5 versus Watchman FLX devices (0.08% vs. 0.04%, p = .0048), with larger LAA ostia (median 23 vs. 21 mm, p = .004), and with a smaller difference between device and LAA ostial size (median difference 4 vs. 5 mm, p = .04). Of 98 147 patients with 45-day follow-up, postdischarge DME occurred in 0.06% (n = 54) patients and cardiac surgery was performed in 7.4% (n = 4) of cases. The 45-day mortality rate was 3.7% (n = 2) among patients with postdischarge DME. Postdischarge DME was more common among men (79.7% of events but 58.9% of all procedures, p = .0019), taller patients (177.9 vs. 172 cm, p = .0005), and those with greater body mass (99.9 vs. 85.5 kg, p = .0055). The rhythm at implant was less frequently AF among patients with DME compared to those without (38.9% vs. 46.9%, p = .0098). CONCLUSION: While Watchman DME is rare, it is associated with high mortality and frequently requires surgical retrieval, and a substantial proportion of events occur after discharge. Due to the severity of DME events, risk mitigation strategies and on-site cardiac surgical back-up are of paramount importance.

Voltage gradients in transvenous and subcutaneous defibrillation and their risk of myocardial damage.

INTRODUCTION: Transvenous implantable cardioverter-defibrillator (ICD) shocks have been associated with cardiac biomarker elevations and are thought in some cases to contribute to adverse clinical outcomes and mortality, possibly from myocardium exposed to excessive shock voltage gradients. Currently, there are only limited data for comparison with subcutaneous ICDs. We sought to compare ventricular myocardium voltage gradients resulting from transvenous (TV) and subcutaneous defibrillator (S-ICD) shocks to assess their risk of myocardial damage. METHODS: A finite element model was derived from thoracic magnetic resonance imaging (MRI). Voltage gradients were modeled for an S-ICD with a left-sided parasternal coil and a left-sided TV-ICD with a mid-cavity, a septal right ventricle (RV) coil, or a dual coil lead (TV mid, TV septal, TV septal + superior vena cava [SVC]). High gradients were defined as > 100 V/cm. RESULTS: The volumes of ventricular myocardium with high gradients > 100 V/cm were 0.02, 2.4, 7.7, and 0 cc for TV mid, TV septal, TV septal + SVC, and S-ICD, respectively. CONCLUSION: Our models suggest that S-ICD shocks produce more uniform gradients in the myocardium, with less exposure to potentially damaging electrical fields, compared to TV-ICDs. Dual coil TV leads yield higher gradients, as does closer proximity of the shock coil to the myocardium.