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Bicuspid aortic valve disease (BAVD) is present in up to half of all patients referred for surgical aortic valve replacement (SAVR) yet was an exclusion criterion for all randomized controlled trials (RCTs) comparing transcatheter aortic valve replacement (TAVR) to SAVR. Nonetheless, approximately 10% of patients currently treated with TAVR have BAVD and available observational data for performing TAVR in these patients are limited by selection bias. Many in the cardiovascular community have advocated for RCTs in this population, but none have been performed. The Heart Valve Collaboratory (HVC) is a multidisciplinary community of stakeholders with the aim of creating significant advances in valvular heart disease by stimulating clinical research, engaging in educational activities, and advancing regulatory science. In December 2020, the HVC hosted a Global Multidisciplinary workshop involving over 100 international experts in the field. Following this 2-day symposium, working groups with varied expertise were convened to discuss BAVD, including the need for and design of RCTs. This review, conducted under the auspices of the HVC, summarizes available data and knowledge gaps regarding procedural therapy for BAVD, outlining specific challenges for trials in this population. We also propose several potential studies that could be performed and discuss respective strengths and weaknesses of each approach. Finally, we present a roadmap for future directions in clinical research in TAVR for BAVD with an emphasis both on RCTs and also prospective registries focused on disease phenotyping to develop parameters and risk scores that could ultimately be applied to patients to inform clinical decision-making.

BACKGROUND: Anemia is associated with increased mortality in patients undergoing transcatheter aortic valve replacement (TAVR); however, data on the effect of the severity of and recovery from anemia on clinical outcomes are limited. This study examined the impact of the severity of and recovery from anemia after TAVR. METHODS: Patients with symptomatic, severe aortic stenosis across all surgical risk groups from the Placement of Aortic Transcatheter Valves (PARTNER) I, II, and III trials and registries who underwent TAVR were analyzed. Baseline anemia was defined as mild (hemoglobin [Hb] level ≥11.0 g/dL and

Background The neutrophil-to-lymphocyte ratio (NLR) as a marker of systemic inflammation has been associated with worse prognosis in several chronic disease states, including heart failure. However, few data exist on the prognostic impact of elevated baseline NLR or change in NLR levels during follow-up in patients undergoing transcatheter or surgical aortic valve replacement (TAVR or SAVR) for aortic stenosis. Methods and Results NLR was available in 5881 patients with severe aortic stenosis receiving TAVR or SAVR in PARTNER (Placement of Aortic Transcatheter Valves) I, II, and S3 trials/registries (median [Q1, Q3] NLR, 3.30 [2.40, 4.90]); mean NLR, 4.10; range, 0.5-24.9) and was evaluated as continuous variable and categorical tertiles (low: NLR ≤2.70, n=1963; intermediate: NLR 2.70-4.20, n=1958; high: NLR ≥4.20, n=1960). No patients had known baseline infection. High baseline NLR was associated with increased risk of death or rehospitalization at 3 years (58.4% versus 41.0%; adjusted hazard ratio [aHR], 1.39; 95% CI, 1.18-1.63; P

BackgroundWe aimed to assess the efficacy and safety of two neutralising monoclonal antibody therapies (sotrovimab [Vir Biotechnology and GlaxoSmithKline] and BRII-196 plus BRII-198 [Brii Biosciences]) for adults admitted to hospital for COVID-19 (hereafter referred to as hospitalised) with COVID-19.MethodsIn this multinational, double-blind, randomised, placebo-controlled, clinical trial (Therapeutics for Inpatients with COVID-19 [TICO]), adults (aged ≥18 years) hospitalised with COVID-19 at 43 hospitals in the USA, Denmark, Switzerland, and Poland were recruited. Patients were eligible if they had laboratory-confirmed SARS-CoV-2 infection and COVID-19 symptoms for up to 12 days. Using a web-based application, participants were randomly assigned (2:1:2:1), stratified by trial site pharmacy, to sotrovimab 500 mg, matching placebo for sotrovimab, BRII-196 1000 mg plus BRII-198 1000 mg, or matching placebo for BRII-196 plus BRII-198, in addition to standard of care. Each study product was administered as a single dose given intravenously over 60 min. The concurrent placebo groups were pooled for analyses. The primary outcome was time to sustained clinical recovery, defined as discharge from the hospital to home and remaining at home for 14 consecutive days, up to day 90 after randomisation. Interim futility analyses were based on two seven-category ordinal outcome scales on day 5 that measured pulmonary status and extrapulmonary complications of COVID-19. The safety outcome was a composite of death, serious adverse events, incident organ failure, and serious coinfection up to day 90 after randomisation. Efficacy and safety outcomes were assessed in the modified intention-to-treat population, defined as all patients randomly assigned to treatment who started the study infusion. This study is registered with ClinicalTrials.gov, NCT04501978.FindingsBetween Dec 16, 2020, and March 1, 2021, 546 patients were enrolled and randomly assigned to sotrovimab (n=184), BRII-196 plus BRII-198 (n=183), or placebo (n=179), of whom 536 received part or all of their assigned study drug (sotrovimab n=182, BRII-196 plus BRII-198 n=176, or placebo n=178; median age of 60 years [IQR 50-72], 228 [43%] patients were female and 308 [57%] were male). At this point, enrolment was halted on the basis of the interim futility analysis. At day 5, neither the sotrovimab group nor the BRII-196 plus BRII-198 group had significantly higher odds of more favourable outcomes than the placebo group on either the pulmonary scale (adjusted odds ratio sotrovimab 1·07 [95% CI 0·74-1·56]; BRII-196 plus BRII-198 0·98 [95% CI 0·67-1·43]) or the pulmonary-plus complications scale (sotrovimab 1·08 [0·74-1·58]; BRII-196 plus BRII-198 1·00 [0·68-1·46]). By day 90, sustained clinical recovery was seen in 151 (85%) patients in the placebo group compared with 160 (88%) in the sotrovimab group (adjusted rate ratio 1·12 [95% CI 0·91-1·37]) and 155 (88%) in the BRII-196 plus BRII-198 group (1·08 [0·88-1·32]). The composite safety outcome up to day 90 was met by 48 (27%) patients in the placebo group, 42 (23%) in the sotrovimab group, and 45 (26%) in the BRII-196 plus BRII-198 group. 13 (7%) patients in the placebo group, 14 (8%) in the sotrovimab group, and 15 (9%) in the BRII-196 plus BRII-198 group died up to day 90.InterpretationNeither sotrovimab nor BRII-196 plus BRII-198 showed efficacy for improving clinical outcomes among adults hospitalised with COVID-19.FundingUS National Institutes of Health and Operation Warp Speed.

BACKGROUND: Guidelines provide class I recommendations for aortic valve intervention for patients with symptomatic severe aortic stenosis (AS) or reduced ejection fraction, but the cornerstone of management for asymptomatic patients has been watchful waiting. This is based on historical nonrandomized data, but randomized controlled trials (RCTs) have now been performed of early surgical aortic valve replacement (SAVR) for asymptomatic severe AS. We performed a meta-analysis of RCTs comparing early SAVR to watchful waiting for asymptomatic severe AS, focusing on individual end points of death and heart failure (HF) hospitalization. METHODS: We systematically identified all RCTs comparing early SAVR to watchful waiting in patients with asymptomatic severe AS and synthesized the data in a random-effects meta-analysis. The prespecified primary end point was all-cause mortality. RESULTS: Two trials randomizing 302 patients were included. Early SAVR lead to a 55% reduction in all-cause mortality (hazard ratio, 0.45; 95% confidence interval, 0.24-0.85; P = .014). There was no heterogeneity (I2 = 0.0%). Early SAVR also lead to a 79% reduction in HF hospitalization (hazard ratio, 0.21; 95% confidence interval, 0.05-0.96; P = .044). CONCLUSIONS: In patients with severe asymptomatic AS and normal ejection fraction, early SAVR reduces death and HF hospitalization compared to initial conservative management. This challenges current treatment standards and has implications for the clinical care of these patients and for guidelines.

Category learning is our ability to generalize across experiences and apply existing knowledge to new situations. Many real-world categories adhere to a “rule-plus-exceptions” structure, wherein most items are rule-followers, but a subset of “exceptions” violate category rules. Rule-plus-exception learning seems tightly coupled with hippocampal function. Though past work has demonstrated that prediction error drives hippocampus to form distinct representations of exceptions, limited work has investigated how this process impacts existing rule-follower representations. Here we use a neural network model of hippocampus to quantify how rule- follower representations are altered by the introduction of exceptions. By recording model representations of rule- followers before and after exceptions are introduced, we computed the shift in rule-follower representation elicited by exceptions. A rule-follower’s similarity to exceptions along category-relevant, but not irrelevant, dimensions predicted its degree of representational shift. This work furthers our understanding of how hippocampus supports the integration of surprising information in dynamic environments.

Paradigms using the free recall of word lists have furthered our understanding of the organizational structure of memory by elucidating the role of contextual associations on memory search. We adapted the traditional word list-learning paradigm to investigate whether emphasizing contextual associations between items influences subsequent retrieval. Specifically, we introduced a review period between encoding and recall of word lists where items were repeated to highlight either the temporal or semantic associations at encoding. We found that temporal review led to stronger temporal clustering compared to a semantic or control review, and semantic review led to stronger semantic clustering compared to a temporal or control review. Moreover, participants recalled more list items when semantic associations were emphasized, with the degree of semantic clustering at recall predicting memory performance. These results demonstrate that emphasizing contextual associations during a repeated viewing after initial encoding can affect subsequent memory organization and recall.

Ways in which ovarian hormones affect cognition have been long overlooked in psychology and neuroscience research despite strong evidence of their effects on the brain. In order to address this gap, we study performance on a rule-plus-exception category learning task, a complex task that requires careful coordination of core cognitive mechanisms, across the menstrual cycle. Results show that the menstrual cycle distinctly affects learning of exceptions in a manner that matches the typical estradiol cycle. Furthermore, participants in their high estradiol phase outperform participants in their low estradiol phase, and show steeper learning slopes than men in exception-learning. These results provide novel evidence of the role of estradiol in category learning, underscore the importance of recruiting diverse samples in cognitive neuroscience research, and highlight the ways in which cognition varies throughout the fundamental biological cycles of the human experience.

The learning of rule-plus-exception categories relies on pattern integration and differentiation, but how the representations of rule-followers and exceptions develop through these two operations remains obscure. Here, we inspected the representational shifts in rule-plus-exception category learning by fitting a computational model to behavioral categorization data. We found that exceptions were differentiated from rule-followers within and between categories through learning. The distanced rule-follower and exception representations in each category formed distinct clusters that together constituted a hierarchically structured categorical representation. Moreover, exception learning increased the representational overlap between rule-followers of opposite categories, thereby blurring the category boundary. Our findings illuminate the representational dynamic underlying the acquisition of rule-plus-exception categories and highlight the roles of pattern integration and differentiation in category learning.

Hippocampus (HPC) is a key structure in category learning, forming organized concepts from individual episodes to adaptively represent shared and distinct elements. Most of the evidence for the role of HPC in concept formation, however, relies on neural coding measured at the end of learning. Thus, it remains unclear how neural mechanisms early in learning support the formation of flexible knowledge. We explored this by combining human functional MRI with a computational model of learning, SUSTAIN. Participants learned to categorize complex visual objects with multiple features. A multidimensional rule linked features to categories with exception items in each category. We observed distinct HPC engagement along its primary axis for exception learning that also predicted learning outcomes. The model predicted that better learners use exceptions to update their knowledge, which was reflected in HPC activation. These findings suggest that HPC discriminates initial informative experiences during learning to support flexible knowledge formation.

Background Concerns about discordance between echocardiographic and invasive mean gradients after transcatheter aortic valve replacement (TAVR) with balloon-expandable valves (BEVs) versus self-expanding valves (SEVs) exist. Methods and Results In a multicenter study, direct-invasive and echocardiography-derived transvalvular mean gradients obtained before and after TAVR were compared as well as post-TAVR and discharge echocardiographic mean gradients in BEVs versus SEVs in 808 patients. Pre-TAVR, there was good correlation (R=0.614; P

ObjectivesTo compare echocardiographic and invasive mean gradients obtained concomitantly in degenerated bioprosthetic surgical aortic valves (SAVRs).MethodsIn a multicenter study, we compared concomitant echocardiographic and invasive mean gradients of SAVR, obtained before valve-in-valve transcatheter aortic valve replacement in all patients, patients with primary stenosis (AS), primary aortic regurgitation (AR), and mixed aortic valve disease (MAVD), and in small versus large valves (≤ or >23 mm). Dimensionless index (DI) was calculated in all groups.ResultsIn total, 74 patients were included and data presented as median (interquartile range). Echocardiography-catheterization mean gradient discordance was observed in all patients (invasive = 22 mm Hg [11-34] vs echocardiographic = 32 mm Hg [21-42], P = .013), small valves (invasive = 15 mm Hg [8-34] vs echocardiographic = 28 mm Hg [21-41], P = .013), and large valves (invasive = 20 mm Hg [8.5-27.13] vs echocardiographic = 32 mm Hg [25.5 - 41.5], P

In addition to saliency and goal-based factors, a scene’s semantic content has been shown to guide attention in visual search tasks. Here, we ask if this rapidly available guidance signal can be leveraged to learn new attentional strategies. In a variant of the scene preview paradigm (Castelhano & Heaven, 2010), participants searched for targets embedded in real-world scenes with target locations linked to scene gist. We found that activating gist with scene previews significantly increased search efficiency over time in a manner consistent with formal theories of skill acquisition. We combine VGG16 and EBRW to provide a biologically inspired account of the gist preview advantage and its effects on learning in gist-guided attention. Preliminary model results suggest that, when preview information is useful, stimulus features may amplify the similarities and differences between exemplars.

We explore the impact of learning sequence on performance in a rule-plus-exception categorization task. Behavioural results indicate that exception categorization accuracy improves when exceptions are introduced later in learning, after exposure to rule-following stimuli. Simulations of this task using a neural network model of hippocampus and its subfields replicate these behavioural findings. Representational similarity analysis of the model’s hidden layers suggests that model representations are also impacted by trial sequence. These results provide novel computational evidence of hippocampus’s sensitivity to learning sequence and further support this region’s proposed role in category learning.

The novel coronavirus disease-2019 (COVID-19) pandemic has created uncertainty in the management of patients with severe aortic stenosis. This population experiences high mortality from delays in treatment of valve disease but is largely overlapping with the population of highest mortality from COVID-19. The authors present strategies for managing patients with severe aortic stenosis in the COVID-19 era. The authors suggest transitions to virtual assessments and consultation, careful pruning and planning of necessary testing, and fewer and shorter hospital admissions. These strategies center on minimizing patient exposure to COVID-19 and expenditure of human and health care resources without significant sacrifice to patient outcomes during this public health emergency. Areas of innovation to improve care during this time include increased use of wearable and remote devices to assess patient performance and vital signs, devices for facile cardiac assessment, and widespread use of clinical protocols for expedient discharge with virtual physical therapy and cardiac rehabilitation options.

Successful categorization requires a careful coordination ofattention, representation, and decision making. Comprehensivetheories that span levels of analysis are key to understandingthe computational and neural dynamics of categorization. Here,we build on recent work linking neural representations ofcategory learning to computational models to investigate howcategory decision making is driven by neural signals across thebrain. We combine functional magnetic resonance imagingwith hierarchical drift diffusion modelling to show that trial-by-trial fluctuations in neural activation from regions ofoccipital, cingulate, and lateral prefrontal cortices are linked tocategory decisions. Notably, lateral prefrontal cortex activationwas also associated with exemplar-based model predictions oftrial-by-trial category evidence. We propose that these brainregions underlie distinct functions that contribute to successfulcategory learning.