A 2 × 2 factorial, randomised, open-label trial to determine the clinical and cost-effectiveness of hypertonic saline (HTS 6%) and carbocisteine for airway clearance versus usual care over 52 weeks in adults with bronchiectasis:a protocol for the CLEAR clinical trial

Background: Current guidelines for the management of bronchiectasis (BE) highlight the lack of evidence to recommend mucoactive agents, such as hypertonic saline (HTS) and carbocisteine, to aid sputum removal as part of standard care. We hypothesise that mucoactive agents (HTS or carbocisteine, or a combination) are effective in reducing exacerbations over a 52-week period, compared to usual care. Methods: This is a 52-week, 2 × 2 factorial, randomized, open-label trial to determine the clinical effectiveness and cost effectiveness of HTS 6% and carbocisteine for airway clearance versus usual care-the Clinical and cost-effectiveness of hypertonic saline (HTS 6%) and carbocisteine for airway clearance versus usual care (CLEAR) trial. Patients will be randomised to (1) standard care and twice-daily nebulised HTS (6%), (2) standard care and carbocisteine (750 mg three times per day until visit 3, reducing to 750 mg twice per day), (3) standard care and combination of twice-daily nebulised HTS and carbocisteine, or (4) standard care. The primary outcome is the mean number of exacerbations over 52 weeks. Key inclusion criteria are as follows: Adults with a diagnosis of BE on computed tomography, BE as the primary respiratory diagnosis, and two or more pulmonary exacerbations in the last year requiring antibiotics and production of daily sputum. Discussion: This trial's pragmatic research design avoids the significant costs associated with double-blind trials whilst optimising rigour in other areas of trial delivery. The CLEAR trial will provide evidence as to whether HTS, carbocisteine or both are effective and cost effective for patients with BE. Trial registration: EudraCT number: 2017-000664-14 (first entered in the database on 20 October 2017). ISRCTN.com, ISRCTN89040295. Registered on 6 July/2018. Funder: National Institute for Health Research, Health Technology Assessment Programme (15/100/01). Sponsor: Belfast Health and Social Care Trust. Ethics Reference Number: 17/NE/0339. Protocol version: V3.0 Final_14052018

Open X-Embodiment:Robotic learning datasets and RT-X models

Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, this has led to a consolidation of pretrained models, with general pretrained backbones serving as a starting point for many applications. Can such a consolidation happen in robotics? Conventionally, robotic learning methods train a separate model for every application, every robot, and even every environment. Can we instead train "generalist" X-robot policy that can be adapted efficiently to new robots, tasks, and environments? In this paper, we provide datasets in standardized data formats and models to make it possible to explore this possibility in the context of robotic manipulation, alongside experimental results that provide an example of effective X-robot policies. We assemble a dataset from 22 different robots collected through a collaboration between 21 institutions, demonstrating 527 skills (160266 tasks). We show that a high-capacity model trained on this data, which we call RT-X, exhibits positive transfer and improves the capabilities of multiple robots by leveraging experience from other platforms. The project website is robotics-transformer-x.github.io

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Change and continuity in peri-urban Australia, Peri-urban case study: Bendigo Corridor: Monograph 2

This monograph is the second in a series of four monographs on peri-urban issues funded by Land and Water Australia and the Commonwealth Department of Environment and Heritage. This publication is a case study of the Bendigo regional corridor in Victoria and has been produced by a team from RMIT University with assistance from researchers at Latrobe University (Bendigo). A companion case study of the Extended Western Corridor to the west of Brisbane has been prepared by the Griffith University School of Environment and Planning. Together these two case studies attempt to apply the scoping study of peri-urban areas published in monograph one of this project. They identify and analyse spatial, land use, environmental, natural resource, social and economic trends; identify governance, institutional, policy and management arrangements and evaluate their adequacy; and examine the implications of change for future land use and land management

Incidence and Susceptibility of Pathogenic Bacteria Vary between Intensive Care Units within a Single Hospital: Implications for Empiric Antibiotic Strategies

BACKGROUNDThe purpose of this study was to determine whether the incidence of recovery and patterns of antibiotic susceptibility of pathogenic bacteria vary between intensive care units (ICUs) in a single teaching hospital. METHODSCulture and susceptibility results were collected prospectively for a 3-month period (April through June 1999) in each of the surgical, trauma, and medical ICUs. The number of unique isolates and susceptibility patterns were determined. Susceptibility of isolates among ICUs was compared with χ. RESULTSStatistically significant differences between ICUs in susceptibility to various antibiotics were found for Staphylococcus aureus, Enterococcus sp, Acinetobacter sp, Enterobacter sp, Klebsiella sp, and Pseudomonas sp. Notably, vancomycin-resistant Enterococcus was not seen in the medical ICU, whereas it was seen in both the surgical and trauma ICUs. Klebsiella spp resistant to ceftazidime were seen only in the trauma ICU. The aminoglycosides and quinolones had attenuated activity against Pseudomonas sp in the surgical ICU, whereas they remained highly effective in the trauma ICU. Cefazolin had no activity against the Enterobacter sp in either of the surgical ICUs, but was highly effective in the medical ICU. CONCLUSIONAlthough the microbiologic results of this study should not be extrapolated to other institutions, the principle is of value. There is variability between ICUs in a single large teaching hospital in susceptibility of bacterial pathogens to various antibiotics. This may have implications in the design of empiric antibiotic strategies and the planning of the hospital formulary. Hospital wide or composite ICU antibiograms are inadequate for planning empiric therapy in the ICU

It's not that I don't care, I just don't care very much: confounding between attribute non-attendance and taste heterogeneity

With the growing interest in the topic of attribute non-attendance, there is now widespread use of latent class (LC) structures aimed at capturing such behaviour, across a number of different fields. Specifically, these studies rely on a confirmatory LC model, using two separate values for each coefficient, one of which is fixed to zero while the other is estimated, and then use the obtained class probabilities as an indication of the degree of attribute non-attendance. In the present paper, we argue that this approach is in fact misguided, and that the results are likely to be affected by confounding with regular taste heterogeneity. We contrast the confirmatory model with an exploratory LC structure in which the values in both classes are estimated. We also put forward a combined latent class mixed logit model (LC-MMNL) which allows jointly for attribute non-attendance and for continuous taste heterogeneity. Across three separate case studies, the exploratory LC model clearly rejects the confirmatory LC approach and suggests that rates of non-attendance may be much lower than what is suggested by the standard model, or even zero. The combined LC-MMNL model similarly produces significant improvements in model fit, along with substantial reductions in the implied rate of attribute non-attendance, in some cases even eliminating the phenomena across the sample population. Our results thus call for a reappraisal of the large body of recent work that has implied high rates of attribute non-attendance for some attributes. Finally, we also highlight a number of general issues with attribute non-attendance, in particular relating to the computation of willingness to pay measures

A question of taste: Recognising the role of latent preferences and attitudes in analysing food choices

There has long been substantial interest in understanding consumer food choices, where a key complexity in this context is the potentially large amount of heterogeneity in tastes across individual consumers, as well as the role of underlying attitudes towards food and cooking. The present paper underlines that both tastes and attitudes are unobserved, and makes the case for a latent variable treatment of these components. Using empirical data collected in Northern Ireland as part of a wider study to elicit intra-household trade-offs between home-cooked meal options, we show how these latent sensitivities and attitudes drive both the choice behaviour as well as the answers to supplementary questions. We find significant heterogeneity across respondents in these underlying factors and show how incorporating them in our models leads to important insights into preferences