The management of acute venous thromboembolism in clinical practice. Results from the European PREFER in VTE Registry

Venous thromboembolism (VTE) is a significant cause of morbidity and mortality in Europe. Data from real-world registries are necessary, as clinical trials do not represent the full spectrum of VTE patients seen in clinical practice. We aimed to document the epidemiology, management and outcomes of VTE using data from a large, observational database. PREFER in VTE was an international, non-interventional disease registry conducted between January 2013 and July 2015 in primary and secondary care across seven European countries. Consecutive patients with acute VTE were documented and followed up over 12 months. PREFER in VTE included 3,455 patients with a mean age of 60.8 ± 17.0 years. Overall, 53.0 % were male. The majority of patients were assessed in the hospital setting as inpatients or outpatients (78.5 %). The diagnosis was deep-vein thrombosis (DVT) in 59.5 % and pulmonary embolism (PE) in 40.5 %. The most common comorbidities were the various types of cardiovascular disease (excluding hypertension; 45.5 %), hypertension (42.3 %) and dyslipidaemia (21.1 %). Following the index VTE, a large proportion of patients received initial therapy with heparin (73.2 %), almost half received a vitamin K antagonist (48.7 %) and nearly a quarter received a DOAC (24.5 %). Almost a quarter of all presentations were for recurrent VTE, with >80 % of previous episodes having occurred more than 12 months prior to baseline. In conclusion, PREFER in VTE has provided contemporary insights into VTE patients and their real-world management, including their baseline characteristics, risk factors, disease history, symptoms and signs, initial therapy and outcomes

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Amazon tree dominance across forest strata

The forests of Amazonia are among the most biodiverse plant communities on Earth. Given the immediate threats posed by climate and land-use change, an improved understanding of how this extraordinary biodiversity is spatially organized is urgently required to develop effective conservation strategies. Most Amazonian tree species are extremely rare but a few are common across the region. Indeed, just 227 ‘hyperdominant’ species account for >50% of all individuals >10 cm diameter at 1.3 m in height. Yet, the degree to which the phenomenon of hyperdominance is sensitive to tree size, the extent to which the composition of dominant species changes with size class and how evolutionary history constrains tree hyperdominance, all remain unknown. Here, we use a large floristic dataset to show that, while hyperdominance is a universal phenomenon across forest strata, different species dominate the forest understory, midstory and canopy. We further find that, although species belonging to a range of phylogenetically dispersed lineages have become hyperdominant in small size classes, hyperdominants in large size classes are restricted to a few lineages. Our results demonstrate that it is essential to consider all forest strata to understand regional patterns of dominance and composition in Amazonia. More generally, through the lens of 654 hyperdominant species, we outline a tractable pathway for understanding the functioning of half of Amazonian forests across vertical strata and geographical locations

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Immunoglobulin, glucocorticoid, or combination therapy for multisystem inflammatory syndrome in children: a propensity-weighted cohort study

Background Multisystem inflammatory syndrome in children (MIS-C), a hyperinflammatory condition associated with SARS-CoV-2 infection, has emerged as a serious illness in children worldwide. Immunoglobulin or glucocorticoids, or both, are currently recommended treatments. Methods The Best Available Treatment Study evaluated immunomodulatory treatments for MIS-C in an international observational cohort. Analysis of the first 614 patients was previously reported. In this propensity-weighted cohort study, clinical and outcome data from children with suspected or proven MIS-C were collected onto a web-based Research Electronic Data Capture database. After excluding neonates and incomplete or duplicate records, inverse probability weighting was used to compare primary treatments with intravenous immunoglobulin, intravenous immunoglobulin plus glucocorticoids, or glucocorticoids alone, using intravenous immunoglobulin as the reference treatment. Primary outcomes were a composite of inotropic or ventilator support from the second day after treatment initiation, or death, and time to improvement on an ordinal clinical severity scale. Secondary outcomes included treatment escalation, clinical deterioration, fever, and coronary artery aneurysm occurrence and resolution. This study is registered with the ISRCTN registry, ISRCTN69546370. Findings We enrolled 2101 children (aged 0 months to 19 years) with clinically diagnosed MIS-C from 39 countries between June 14, 2020, and April 25, 2022, and, following exclusions, 2009 patients were included for analysis (median age 8·0 years [IQR 4·2–11·4], 1191 [59·3%] male and 818 [40·7%] female, and 825 [41·1%] White). 680 (33·8%) patients received primary treatment with intravenous immunoglobulin, 698 (34·7%) with intravenous immunoglobulin plus glucocorticoids, 487 (24·2%) with glucocorticoids alone; 59 (2·9%) patients received other combinations, including biologicals, and 85 (4·2%) patients received no immunomodulators. There were no significant differences between treatments for primary outcomes for the 1586 patients with complete baseline and outcome data that were considered for primary analysis. Adjusted odds ratios for ventilation, inotropic support, or death were 1·09 (95% CI 0·75–1·58; corrected p value=1·00) for intravenous immunoglobulin plus glucocorticoids and 0·93 (0·58–1·47; corrected p value=1·00) for glucocorticoids alone, versus intravenous immunoglobulin alone. Adjusted average hazard ratios for time to improvement were 1·04 (95% CI 0·91–1·20; corrected p value=1·00) for intravenous immunoglobulin plus glucocorticoids, and 0·84 (0·70–1·00; corrected p value=0·22) for glucocorticoids alone, versus intravenous immunoglobulin alone. Treatment escalation was less frequent for intravenous immunoglobulin plus glucocorticoids (OR 0·15 [95% CI 0·11–0·20]; p<0·0001) and glucocorticoids alone (0·68 [0·50–0·93]; p=0·014) versus intravenous immunoglobulin alone. Persistent fever (from day 2 onward) was less common with intravenous immunoglobulin plus glucocorticoids compared with either intravenous immunoglobulin alone (OR 0·50 [95% CI 0·38–0·67]; p<0·0001) or glucocorticoids alone (0·63 [0·45–0·88]; p=0·0058). Coronary artery aneurysm occurrence and resolution did not differ significantly between treatment groups. Interpretation Recovery rates, including occurrence and resolution of coronary artery aneurysms, were similar for primary treatment with intravenous immunoglobulin when compared to glucocorticoids or intravenous immunoglobulin plus glucocorticoids. Initial treatment with glucocorticoids appears to be a safe alternative to immunoglobulin or combined therapy, and might be advantageous in view of the cost and limited availability of intravenous immunoglobulin in many countries. Funding Imperial College London, the European Union's Horizon 2020, Wellcome Trust, the Medical Research Foundation, UK National Institute for Health and Care Research, and National Institutes of Health

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation