Predictors of Prolonged Length of Stay after Elective Carotid Revascularization.

OBJECTIVE: Postoperative day-one discharge is used as a quality-of-care indicator after carotid revascularization. This study identifies predictors of prolonged length of stay (pLOS), defined as a postprocedural LOS of > 1 day, after elective carotid revascularization. METHODS: Patients undergoing carotid endarterectomy (CEA), Transcarotid artery revascularization (TCAR) and Transfemoral carotid artery stenting (TFCAS) in the Vascular Quality Initiative between 2016 and 2022 were included in this analysis. Multivariable logistic regression analysis was used to identify predictors of pLOS, defined as a postprocedural LOS of > 1 day, after each procedure. RESULTS: A total of 118,625 elective cases were included. pLOS was observed in nearly 23.2% of patients undergoing carotid revascularization. Major adverse events, including neurological, cardiac, infectious, and bleeding complications, occurred in 5.2% of patients and were the most significant contributor to pLOS after the 3 procedures. Age, female sex, nonwhite race, insurance status, high comorbidity index, prior ipsilateral CEA, non-ambulatory status, symptomatic presentation, surgeries occurring on Friday and postoperative hypo- or hypertension were significantly associated with pLOS across all 3 procedures. For CEA, additional predictors included contralateral carotid artery occlusion, preoperative use of dual antiplatelets and anticoagulation, low physician volume (< 11 cases/year) and drain use. For TCAR, preoperative anticoagulation use, low physician case volume (<6 cases/year), no protamine use, and post-stent dilatation intraoperatively were associated with pLOS. One-year analysis showed a significant association between pLOS and increased mortality for all 3 procedures; CEA (HR,1.64; 95%CI, 1.49-1.82), TCAR (HR,1.56; 95%CI, 1.35-1.80), and TFCAS (HR,1.33; 95%CI,1.08-1.64) (all P<0.05). CONCLUSIONS: A postoperative LOS of more than 1 day is not uncommon after carotid revascularization. Procedure-related complications are the most common drivers of pLOS. Identifying patients are risk for pLOS highlight quality improvement strategies that can optimize short and 1-year outcomes of patients undergoing carotid revascularization.

Global monitoring for biodiversity: Uncertainty, risk, and power analyses to support trend change detection.

Global targets aim to reverse biodiversity declines by 2050 but require knowledge of current trends and future projections under policy intervention. First, given uncertainty in measurement of current trends, we propose a risk framework, considering probability and magnitude of decline. While only 11 of 198 systems analyzed (taxonomic groups by country from the Living Planet Database) showed declining abundance with high certainty, 20% of systems had a 70% chance of strong declines. Society needs to decide acceptable risks of biodiversity loss. Second, we calculated statistical power to detect trend change using ~12,000 populations from 62 systems currently showing strong declines. Current trend uncertainty hinders our ability to assess improvements. Trend change is detectable with high certainty in only 14 systems, even if thousands of populations are sampled, and conservation action reduces net declines to zero immediately, on average. We provide potential solutions to improve monitoring of progress toward biodiversity targets.

Human coronavirus OC43-elicited CD4+ T cells protect against SARS-CoV-2 in HLA transgenic mice.

SARS-CoV-2-reactive T cells are detected in some healthy unexposed individuals. Human studies indicate these T cells could be elicited by the common cold coronavirus OC43. To directly test this assumption and define the role of OC43-elicited T cells that are cross-reactive with SARS-CoV-2, we develop a model of sequential infections with OC43 followed by SARS-CoV-2 in HLA-B*0702 and HLA-DRB1*0101 Ifnar1-/- transgenic mice. We find that OC43 infection can elicit polyfunctional CD8+ and CD4+ effector T cells that cross-react with SARS-CoV-2 peptides. Furthermore, pre-exposure to OC43 reduces subsequent SARS-CoV-2 infection and disease in the lung for a short-term in HLA-DRB1*0101 Ifnar1-/- transgenic mice, and a longer-term in HLA-B*0702 Ifnar1-/- transgenic mice. Depletion of CD4+ T cells in HLA-DRB1*0101 Ifnar1-/- transgenic mice with prior OC43 exposure results in increased viral burden in the lung but no change in virus-induced lung damage following infection with SARS-CoV-2 (versus CD4+ T cell-sufficient mice), demonstrating that the OC43-elicited SARS-CoV-2 cross-reactive T cell-mediated cross-protection against SARS-CoV-2 is partially dependent on CD4+ T cells. These findings contribute to our understanding of the origin of pre-existing SARS-CoV-2-reactive T cells and their effects on SARS-CoV-2 clinical outcomes, and also carry implications for development of broadly protective betacoronavirus vaccines.

Including socioeconomic status reduces readmission penalties to safety-net hospitals.

OBJECTIVE: Medicare's Hospital Readmissions Reduction Program (HRRP) financially penalizes "excessive" postoperative readmissions. Concerned with creating a double standard for institutions treating a high percentage of economically vulnerable patients, Medicare elected to exclude socioeconomic status (SES) from its risk-adjustment model. However, recent evidence suggests that safety-net hospitals (SNHs) caring for many low-SES patients are disproportionately penalized under the HRRP. We sought to simulate the impact of including SES-sensitive models on HRRP penalties for hospitals performing lower extremity revascularization (LER). METHODS: This is a retrospective, cross-sectional analysis of national data on Medicare patients undergoing open or endovascular LER procedures between 2007 and 2009. We used hierarchical logistic regression to generate hospital risk-standardized 30-day readmission rates under Medicare's current model (adjusting for age, sex, comorbidities, and procedure type) compared with models that also adjust for SES. We estimated the likelihood of a penalty and penalty size for SNHs compared with non-SNHs under the current Medicare model and these SES-sensitive models. RESULTS: Our study population comprised 1708 hospitals performing 284,724 LER operations with an overall unadjusted readmission rate of 14.4% (standard deviation: 5.3%). Compared with the Centers for Medicare and Medicaid Services model, adjusting for SES would not change the proportion of SNHs penalized for excess readmissions (55.1% vs 53.4%, P = .101) but would reduce penalty amounts for 38% of SNHs compared with only 17% of non-SNHs, P < .001. CONCLUSIONS: For LER, changing national Medicare policy to including SES in readmission risk-adjustment models would reduce penalty amounts to SNHs, especially for those that are also teaching institutions. Making further strides toward reducing the national disparity between SNHs and non-SHNs on readmissions, performance measures require strategies beyond simply altering the risk-adjustment model to include SES.

Rapid monitoring of ecological persistence.

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of an ecological community is supported by its underlying network of species interactions. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, only small subsets of these networks can be monitored. There is therefore an urgent need to establish links between the small snapshots of data conservationists can collect, and the "big picture" conclusions about ecosystem health demanded by policymakers, scientists, and societies. Here, we show that the persistence of small subnetworks (motifs) in isolation-that is, their persistence when considered separately from the larger network of which they are a part-is a reliable probabilistic indicator of the persistence of the network as a whole. Our methods show that it is easier to detect if an ecological community is not persistent than if it is persistent, allowing for rapid detection of extinction risk in endangered systems. Our results also justify the common practice of predicting ecological persistence from incomplete surveys by simulating the population dynamics of sampled subnetworks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies.

A framework for the detection and attribution of biodiversity change.

The causes of biodiversity change are of great scientific interest and central to policy efforts aimed at meeting biodiversity targets. Changes in species diversity and high rates of compositional turnover have been reported worldwide. In many cases, trends in biodiversity are detected, but these trends are rarely causally attributed to possible drivers. A formal framework and guidelines for the detection and attribution of biodiversity change is needed. We propose an inferential framework to guide detection and attribution analyses, which identifies five steps-causal modelling, observation, estimation, detection and attribution-for robust attribution. This workflow provides evidence of biodiversity change in relation to hypothesized impacts of multiple potential drivers and can eliminate putative drivers from contention. The framework encourages a formal and reproducible statement of confidence about the role of drivers after robust methods for trend detection and attribution have been deployed. Confidence in trend attribution requires that data and analyses used in all steps of the framework follow best practices reducing uncertainty at each step. We illustrate these steps with examples. This framework could strengthen the bridge between biodiversity science and policy and support effective actions to halt biodiversity loss and the impacts this has on ecosystems. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Detecting and attributing the causes of biodiversity change: needs, gaps and solutions.

This issue addresses the multifaceted problems of understanding biodiversity change to meet emerging international development and conservation goals, national economic accounting and diverse community needs. Recent international agreements highlight the need to establish monitoring and assessment programmes at national and regional levels. We identify an opportunity for the research community to develop the methods for robust detection and attribution of biodiversity change that will contribute to national assessments and guide conservation action. The 16 contributions of this issue address six major aspects of biodiversity assessment: connecting policy to science, establishing observation, improving statistical estimation, detecting change, attributing causes and projecting the future. These studies are led by experts in Indigenous studies, economics, ecology, conservation, statistics, and computer science, with representations from Asia, Africa, South America, North America and Europe. The results place biodiversity science in the context of policy needs and provide an updated roadmap for how to observe biodiversity change in a way that supports conservation action via robust detection and attribution science. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Spread of networked populations is determined by the interplay between dispersal behavior and habitat configuration.

Predicting the spread of populations across fragmented habitats is vital if we are to manage their persistence in the long term. We applied network theory with a model and an experiment to show that spread rate is jointly defined by the configuration of habitat networks (i.e., the arrangement and length of connections between habitat fragments) and the movement behavior of individuals. We found that population spread rate in the model was well predicted by algebraic connectivity of the habitat network. A multigeneration experiment with the microarthropod Folsomia candida validated this model prediction. The realized habitat connectivity and spread rate were determined by the interaction between dispersal behavior and habitat configuration, such that the network configurations that facilitated the fastest spread changed depending on the shape of the species' dispersal kernel. Predicting the spread rate of populations in fragmented landscapes requires combining knowledge of species-specific dispersal kernels and the spatial configuration of habitat networks. This information can be used to design landscapes to manage the spread and persistence of species in fragmented habitats.

Validating administratively derived frailty scores for use in Veterans Health Administration emergency departments.

OBJECTIVES: Frailty is a clinical syndrome characterized by decreased physiologic reserve that diminishes the ability to respond to stressors such as acute illness. Veterans Health Administration (VA) emergency departments (ED) are the primary venue of care for Veterans with acute illness and represent key sites for frailty recognition. As questionnaire-based frailty instruments can be cumbersome to implement in the ED, we examined two administratively derived frailty scores for use among VA ED patients. METHODS: This national retrospective cohort study included all VA ED visits (2017-2020). We evaluated two administratively derived scores: the Care Assessment Needs (CAN) score and the VA Frailty Index (VA-FI). We categorized all ED visits across four frailty groups and examined associations with outcomes of 30-day and 90-day hospitalization and 30-day, 90-day, and 1-year mortality. We used logistic regression to assess the model performance of the CAN score and the VA-FI. RESULTS: The cohort included 9,213,571 ED visits. With the CAN score, 28.7% of the cohort were classified as severely frail; by VA-FI, 13.2% were severely frail. All outcome rates increased with progressive frailty (p-values for all comparisons < 0.001). For example, for 1-year mortality based on the CAN score frailty was determined as: robust, 1.4%; prefrail, 3.4%; moderately frail, 7.0%; and severely frail, 20.2%. Similarly, for 90-day hospitalization based on VA-FI, frailty was determined as prefrail, 8.3%; mildly frail, 15.3%; moderately frail, 29.5%; and severely frail, 55.4%. The c-statistics for CAN score models were higher than for VA-FI models across all outcomes (e.g., 1-year mortality, 0.721 vs. 0.659). CONCLUSIONS: Frailty was common among VA ED patients. Increased frailty, whether measured by CAN score or VA-FI, was strongly associated with hospitalization and mortality and both can be used in the ED to identify Veterans at high risk for adverse outcomes. Having an effective automatic score in VA EDs to identify frail Veterans may allow for better targeting of scarce resources.

Metapopulation persistence can be inferred from incomplete surveys.

Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation-populations inhabiting habitat patches connected by dispersal-can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape: often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a portion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub-samples of habitat patches. Full-factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds (Amazilia boucardi). On the basis of our statistical framework, we provide some sampling suggestion for monitoring metapopulation persistence. Our approach allows for rapid and effective inference of metapopulation persistence from incomplete patch surveys.

Monitor biodiversity for action.

This week, Montreal, Canada, is at the epicenter of international negotiations for biodiversity. Thousands of people from around the world are attending the 15th Conference of the Parties to the United Nations Convention on Biological Diversity (COP15) to witness the negotiation of a new Global Biodiversity Framework. Its goals and targets replace the previous framework-the Aichi Biodiversity Targets-that failed to bring about the transformative change needed to reverse the alarming trends in biodiversity loss.

Highly efficient and durable antimicrobial nanocomposite textiles.

Healthcare associated infections cause millions of hospitalizations and cost billions of dollars every year. A potential solution to address this problem is to develop antimicrobial textile for healthcare fabrics (hospital bedding, gowns, lab coats, etc.). Metal nanoparticle-coated textile has been proven to possess antimicrobial properties but have not been adopted by healthcare facilities due to risks of leaching and subsequent loss of function, toxicity, and environmental pollution. This work presents the development and testing of antimicrobial zinc nanocomposite textiles, fabricated using a novel Crescoating process. In this process, zinc nanoparticles are grown in situ within the bulk of different natural and synthetic fabrics to form safe and durable nanocomposites. The zinc nanocomposite textiles show unprecedented microbial reduction of 99.99% (4 log10) to 99.9999% (6 log10) within 24 h on the most common Gram-positive and Gram-negative bacteria, and fungal pathogens. Furthermore, the antimicrobial activity remains intact even after 100 laundry cycles, demonstrating the high longevity and durability of the textile. Independent dermatological evaluation confirmed that the novel textile is non-irritating and hypoallergenic.

Generalism drives abundance: A computational causal discovery approach.

A ubiquitous pattern in ecological systems is that more abundant species tend to be more generalist; that is, they interact with more species or can occur in wider range of habitats. However, there is no consensus on whether generalism drives abundance (a selection process) or abundance drives generalism (a drift process). As it is difficult to conduct direct experiments to solve this chicken-and-egg dilemma, previous studies have used a causal discovery method based on formal logic and have found that abundance drives generalism. Here, we refine this method by correcting its bias regarding skewed distributions, and employ two other independent causal discovery methods based on nonparametric regression and on information theory, respectively. Contrary to previous work, all three independent methods strongly indicate that generalism drives abundance when applied to datasets on plant-hummingbird communities and reef fishes. Furthermore, we find that selection processes are more important than drift processes in structuring multispecies systems when the environment is variable. Our results showcase the power of the computational causal discovery approach to aid ecological research.

Virtual Reality Based Active Shooter Training Drill Increases Salivary and Subjective Markers of Stress.

Law enforcement personnel are required to respond to a variety of dangerous, potentially life-threatening high stress scenarios. Virtual reality (VR)-based training has been shown to attenuate stress responses; however, little is known about the acute stress response from VR exposure. This study examined the impact of participating in a VR-based active shooter training drill (ASD) on markers of physiological stress as well as potential differences in men and women. To examine the impact of participation in a ~50 sec VR-based ASD, 29 subjects (n = 29; 17 males, 12 females) participated in a quasi-experimental single group design. Saliva samples were collected and analyzed from 27 of the 29 subjects a total of four times 1) 30-min prior to, 2) 5-min prior to, 3) 5-min after, and 4) 30-min after the ASD and analyzed for α-amylase (AA) activity and concentrations of secretory immunoglobulin-A (SIgA), cortisol (CORT), and uric acid (UA). Participation in the ASD resulted in a significant (p < 0.05) increase in salivary stress markers AA and SIgA. In addition, lower concentrations of CORT and UA were found in women compared to men. These findings have implications for law enforcement and/or military personnel that may seek to implement a VR-based training into their training regimen. Future studies should investigate the impact of longitudinal participation in ASD interventions to determine if this is an effective training method to reduce stress responses to real life active shooter training drills.

A Zika virus mutation enhances transmission potential and confers escape from protective dengue virus immunity.

Zika virus (ZIKV) and dengue virus (DENV) are arthropod-borne pathogenic flaviviruses that co-circulate in many countries. To understand some of the pressures that influence ZIKV evolution, we mimic the natural transmission cycle by repeating serial passaging of ZIKV through cultured mosquito cells and either DENV-naive or DENV-immune mice. Compared with wild-type ZIKV, the strains passaged under both conditions exhibit increased pathogenesis in DENV-immune mice. Application of reverse genetics identifies an isoleucine-to-valine mutation (I39V) in the NS2B proteins of both passaged strains that confers enhanced fitness and escape from pre-existing DENV immunity. Introduction of I39V or I39T, a naturally occurring homologous mutation detected in recent ZIKV isolates, increases the replication of wild-type ZIKV in human neuronal precursor cells and laboratory-raised mosquitoes. Our data indicate that ZIKV strains with enhanced transmissibility and pathogenicity can emerge in DENV-naive or -immune settings, and that NS2B-I39 mutants may represent ZIKV variants of interest.

A Glyphosate-Based Herbicide Cross-Selects for Antibiotic Resistance Genes in Bacterioplankton Communities.

Agrochemicals often contaminate freshwater bodies, affecting microbial communities that underlie aquatic food webs. For example, the herbicide glyphosate has the potential to indirectly select for antibiotic-resistant bacteria. Such cross-selection could occur if the same genes (encoding efflux pumps, for example) confer resistance to both glyphosate and antibiotics. To test for cross-resistance in natural aquatic bacterial communities, we added a glyphosate-based herbicide (GBH) to 1,000-liter mesocosms filled with water from a pristine lake. Over 57 days, we tracked changes in bacterial communities with shotgun metagenomic sequencing and annotated metagenome-assembled genomes (MAGs) for the presence of known antibiotic resistance genes (ARGs), plasmids, and resistance mutations in the enzyme targeted by glyphosate (enolpyruvyl-shikimate-3-phosphate synthase; EPSPS). We found that high doses of GBH significantly increased ARG frequency and selected for multidrug efflux pumps in particular. The relative abundance of MAGs after a high dose of GBH was predictable based on the number of ARGs in their genomes (17% of variation explained) and, to a lesser extent, by resistance mutations in EPSPS. Together, these results indicate that GBHs can cross-select for antibiotic resistance in natural freshwater bacteria. IMPORTANCE Glyphosate-based herbicides (GBHs) such as Roundup formulations may have the unintended consequence of selecting for antibiotic resistance genes (ARGs), as demonstrated in previous experiments. However, the effects of GBHs on ARGs remain unknown in natural aquatic communities, which are often contaminated with pesticides from agricultural runoff. Moreover, the resistance provided by ARGs compared to canonical mutations in the glyphosate target enzyme, EPSPS, remains unclear. Here, we performed a freshwater mesocosm experiment showing that a GBH strongly selects for ARGs, particularly multidrug efflux pumps. These selective effects were evident after just a few days, and the ability of bacteria to survive and thrive after GBH stress was predictable by the number of ARGs in their genomes and, to a lesser extent, by mutations in EPSPS. Intensive GBH application may therefore have the unintended consequence of selecting for ARGs in natural freshwater communities.

Genotype diversity promotes the persistence of Daphnia populations exposed to severe copper stress.

When environmental stressors of high intensity are sustained for long periods of time, populations face high probabilities of being extirpated. However, depending on the intensity of the stressor, large populations with sufficient genetic diversity may persist. We report the results of an experiment that tracked the persistence of Daphnia populations exposed to copper contamination. We assessed whether genotypic diversity reduced the risk of extinction. We created monoclonal and multiclonal populations and monitored their population sizes during a 32-week experiment. Cu was applied at a sub-lethal concentration and then increased every week until the population sizes dropped to about 10% of the carrying capacity (Cu at 180 µg/L). The concentration was then increased up to 186 µg/L and held stable until the end of the experiment. A survival analysis showed that clonal diversity extended the persistence of Daphnia populations, but copper contamination caused a substantial genetic erosion followed by population extirpation. However, some Cu-treated populations, mostly multiclonal, showed U-shaped patterns of growth consistent with evolutionary rescue but these did not lead to lasting population recovery. These results highlight the importance of genetic variation for population persistence, but they also show how quickly it can be lost in contaminated environments.