DIRK Schemes with High Weak Stage Order

Runge-Kutta time-stepping methods in general suffer from order reduction: the observed order of convergence may be less than the formal order when applied to certain stiff problems. Order reduction can be avoided by using methods with high stage order. However, diagonally-implicit Runge-Kutta (DIRK) schemes are limited to low stage order. In this paper we explore a weak stage order criterion, which for initial boundary value problems also serves to avoid order reduction, and which is compatible with a DIRK structure. We provide specific DIRK schemes of weak stage order up to 3, and demonstrate their performance in various examples.Comment: 10 pages, 5 figure

Use of a sample-to-result shotgun metagenomics platform for the detection and quantification of viral pathogens in paediatric immunocompromised patients

Background: Infections by several DNA viruses can severely impact outcomes in paediatric immunocompromised patients. Current testing, which is generally limited to singleplex qPCR assays, can miss both common and rarer viruses if they are not targeted. Objectives: To evaluate the performance of the Galileo Viral Panel (Galileo), a sample-to-result shotgun metagenomics platform for the detection and quantification of 12 DNA viruses, compared to standard of care qPCR assays. Study design: A clinical performance evaluation was carried out using 43 prospectively collected EDTA plasma samples positive for one or more DNA viruses. Agreement between assays was assessed by overall, positive, and negative percent agreement, as well as quantitative agreement by linear regression and Bland-Altman analysis. Results: Overall positive percent agreement was 84% (95% CI: 76%-90%), and negative percent agreement was 95% (95% CI: 92%-97%). There was a high correlation between Galileo and qPCR for ADV, CMV, EBV, and VZV (R2 = 0.91) and a mean difference by Bland Altman of -0.43 log10 IU or cp/ml (95% limits of agreement, -1.37 to 0.51). In addition, there was a high correlation between Galileo Signal Score and qPCR for TTV (R2 = 0.85). Conclusion: We observed high qualitative and quantitative agreement between qPCR and Galileo. Galileo identified additional viruses that were not tested with routine qPCR and could impact clinical outcomes

Validation of methods for converting the original Disease Activity Score (DAS) to the DAS28

© The Author(s) 2018.The Disease Activity Score (DAS) is integral in tailoring the clinical management of rheumatoid arthritis (RA) patients and is an important measure in clinical research. Different versions have been developed over the years to improve reliability and ease of use. Combining the original DAS and the newer DAS28 data in both contemporary and historical studies is important for both primary and secondary data analyses. As such, a methodologically robust means of converting the old DAS to the new DAS28 measure would be invaluable. Using data from The Early RA Study (ERAS), a sub-sample of patients with both DAS and DAS28 data were used to develop new regression imputation formulas using the total DAS score (univariate), and using the separate components of the DAS score (multivariate). DAS were transformed to DAS28 using an existing formula quoted in the literature, and the newly developed formulas. Bland and Altman plots were used to compare the transformed DAS with the recorded DAS28 to ascertain levels of agreement. The current transformation formula tended to overestimate the true DAS28 score, particularly at the higher end of the scale. A formula which uses all separate components of the DAS was found to estimate the scores with a higher level of precision. A new formula is proposed that can be used by other early RA cohorts to convert the original DAS to DAS28.Peer reviewedFinal Published versio

Why are feasibility studies accessing routinely collected health data? A systematic review

BACKGROUND: Feasibility trials are often undertaken to determine whether a larger randomised controlled trial (RCT) is achievable. In a recent review, 15 feasibility trials accessed routinely collected health data (RCHD) from UK national databases and registries. This paper looks at attributes of these trials and the reasons why they accessed RCHD. METHODS: We extracted data from all publicly available sources for the 15 feasibility studies found in a previous review of trials successfully accessing RCHD in the UK between 2013–2018 for the purpose of informing or supplementing participant data. We extracted trial characteristics, the registry accessed, and the way the RCHD was used. RESULTS: The 15 feasibility RCTs were conducted in a variety of disease areas, and were generally small (median sample size 100, range 41–4061) and individually randomised (60%, 9/15). The primary trial outcome was predominantly administrative (non-clinical) (80%, 12/15) such as feasibility of patient recruitment. They were more likely to recruit from secondary care (67%, 10/15) settings than primary (33%, 5/15). NHS Digital was the most commonly accessed registry (33% (5/15)) with SAIL databank (20% (3/15)), electronic Data Research and Innovation Service (eDRIS) and Paediatric Intensive Care Audit Network (PICANET) (each 13% 2/15) also being accessed. Where the information was clear, the trials used RCHD for data collection during the trial (47%, 7/15), follow-up after the trial (27%, 4/15) and recruitment (13%, 2/15). CONCLUSIONS: Between 2013 and 2018, 15 feasibility trials successfully accessed UK RCHD. Feasibility trials would benefit, as with other trials, from guidance on reporting the use of RCHD in protocols and publications

The changing nature of risk and risk management: the challenge of borders, uncertainty and resilience

No abstract available

Do Interventions Designed to Support Shared Decision-Making Reduce Health Inequalities? : A Systematic Review and Meta-Analysis

Copyright: © 2014 Durand et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: Increasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities. Objective: To evaluate the impact of SDM interventions on disadvantaged groups and health inequalities. Design: Systematic review and meta-analysis of randomised controlled trials and observational studies.Peer reviewe

Making Associativity Operational

The purpose of this paper is to propose an operational idea for developing algebraic thinking in the absence of alphanumeric symbols. The paper reports on a design experiment encouraging preschool children to use the associative property algebraically. We describe the theoretical basis of the design, the tasks used, and examples of algebraic thinking in 5–6-year-old children. Theoretically, the paper makes a critical distinction between operational and structural meanings of the notion of equality. We argue that mathematical thinking involving equality among young learners can comprise both an operational and a structural conception and that the operational conception has a side that is productively linked to the structural conception. Using carefully designed hands-on tasks, the crux of the paper is the realization of algebraic thinking (in verbal mathematics) as operationally experienced in the ability to transform one number structure, with a quantity that is subject to change, into another through equality-preserving transformations

Sensitivity Analysis for Not-at-Random Missing Data in Trial-Based Cost-Effectiveness Analysis : A Tutorial

Cost-effectiveness analyses (CEA) of randomised controlled trials are a key source of information for health care decision makers. Missing data are, however, a common issue that can seriously undermine their validity. A major concern is that the chance of data being missing may be directly linked to the unobserved value itself [missing not at random (MNAR)]. For example, patients with poorer health may be less likely to complete quality-of-life questionnaires. However, the extent to which this occurs cannot be ascertained from the data at hand. Guidelines recommend conducting sensitivity analyses to assess the robustness of conclusions to plausible MNAR assumptions, but this is rarely done in practice, possibly because of a lack of practical guidance. This tutorial aims to address this by presenting an accessible framework and practical guidance for conducting sensitivity analysis for MNAR data in trial-based CEA. We review some of the methods for conducting sensitivity analysis, but focus on one particularly accessible approach, where the data are multiply-imputed and then modified to reflect plausible MNAR scenarios. We illustrate the implementation of this approach on a weight-loss trial, providing the software code. We then explore further issues around its use in practice

Early Warning Signals for Critical Transitions: A Generalized Modeling Approach

Critical transitions are sudden, often irreversible, changes that can occur in a large variety of complex systems; signals that warn of critical transitions are therefore highly desirable. We propose a new method for early warning signals that integrates multiple sources of information and data about the system through the framework of a generalized model. We demonstrate our proposed approach through several examples, including a previously published fisheries model. We regard our method as complementary to existing early warning signals, taking an approach of intermediate complexity between model-free approaches and fully parameterized simulations. One potential advantage of our approach is that, under appropriate conditions, it may reduce the amount of time series data required for a robust early warning signal

Toward Human-Carnivore Coexistence: Understanding Tolerance for Tigers in Bangladesh

Fostering local community tolerance for endangered carnivores, such as tigers (Panthera tigris), is a core component of many conservation strategies. Identification of antecedents of tolerance will facilitate the development of effective tolerance-building conservation action and secure local community support for, and involvement in, conservation initiatives. We use a stated preference approach for measuring tolerance, based on the ‘Wildlife Stakeholder Acceptance Capacity’ concept, to explore villagers’ tolerance levels for tigers in the Bangladesh Sundarbans, an area where, at the time of the research, human-tiger conflict was severe. We apply structural equation modeling to test an a priori defined theoretical model of tolerance and identify the experiential and psychological basis of tolerance in this community. Our results indicate that beliefs about tigers and about the perceived current tiger population trend are predictors of tolerance for tigers. Positive beliefs about tigers and a belief that the tiger population is not currently increasing are both associated with greater stated tolerance for the species. Contrary to commonly-held notions, negative experiences with tigers do not directly affect tolerance levels; instead, their effect is mediated by villagers’ beliefs about tigers and risk perceptions concerning human-tiger conflict incidents. These findings highlight a need to explore and understand the socio-psychological factors that encourage tolerance towards endangered species. Our research also demonstrates the applicability of this approach to tolerance research to a wide range of socio-economic and cultural contexts and reveals its capacity to enhance carnivore conservation efforts worldwide