1,878 research outputs found

    A causal inference framework for comparative effectiveness and safety research using observational data, with application in type 2 diabetes

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    Randomized controlled trials are the gold standard to answer causal questions in health research as the process of randomization ensures balanced treatment groups and therefore makes it possible to compare average group outcomes directly. But they have many limitations with respect to costs, ethical considerations and practicability and therefore may not be suitable to answer all research questions. Evidence on cause and effect relationships from observational studies have the potential to overcome the limitations of trials and close important research gaps as they provide the possibility to study subpopulations of patients which are often excluded due to safety concerns, or can give insights into the risk profile of long-term endpoints. The quality of this real-world evidence depends on the quality of data, their suitability to answer a particular research question and the use of appropriate methods to estimate the treatment effect of interest. Of concern in observational research is bias in the treatment effect estimation due to confounding, as the treatment assignment is not controlled by the researcher and cannot be randomized. It is therefore possible that treatment groups are not balanced and confounding factors exist in the data which influence the treatment choice and the outcome of interest simultaneously. The benefits of observational studies make them attractive for studying the risk and benefit profiles of oral type 2 diabetes treatments, especially of newer agent classes such as Sodium-glucose Cotransporter-2 Inhibitors. Prescribing of this treatment class has increased in recent years and a large proportion of type 2 diabetes patients have become eligible to receive agents from this class after recent treatment guideline changes. More information about treatment effects of Sodium-glucose Cotransporter-2 Inhibitors are needed especially for the large patient population of older adults (e.g. 70 years or older), as possible adverse effects such as osmotic symptoms associated with this class could have severe consequences for these patients. The overall aim of this thesis is to develop a causal inference framework for the exploitation of observational data, needed to derive high quality evidence on the benefit and safety profile of oral type 2 diabetes treatments, with a focus on the widely prescribed treatment class of Sodium-glucose Cotransporter-2 Inhibitors and the patient population of older adults. Chapter 1 and 2 are introductions to causal inference theory including the description of all estimation methods employed in this thesis and an introduction to type 2 diabetes research encompassing important treatment decision considerations, and current research evidence on Sodium-glucose Cotransporter-2 Inhibitors. Chapter 3 presents a triangulation framework of assorted estimation methods to establish the consistency of estimation results from approaches utilizing different parts of the data and relying on different data structure assumptions. Furthermore, an Instrumental Variable approach is introduced which uses data from the period before treatment initiation to mitigate potential bias in case the exchangeability assumption is violated and a history of the outcome of interest previous to treatment initiation has an influence on the treatment decision. Chapter 4 describes a simulation study on the performance of established construction methods for a proxy Instrumental Variable of health care provider prescription preference. The methods are tested under different data conditions such as change in provider preference over time, missing data in baseline covariates and different sample sizes within each health care provider. Additionally, a construction method is introduced that aims to address changes in preference over time and non-ignorabile missingness in baseline characteristics. In Chapter 5 the developed conclusions about a robust Instrumental Variable estimation approach from previous chapters are applied for a causal analysis on the relative benefit and risk profile of Sodium-glucose Cotransporter-2 Inhibitors versus Dipeptidyl peptidase-4 Inhibitors in the patient population of older adults. Chapter 6 provides an overview of the main findings and implications of this thesis and discusses limitations and future research potential of each study.Operating Budget, Research Englan

    A Unifying Theory for Graph Transformation

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    The field of graph transformation studies the rule-based transformation of graphs. An important branch is the algebraic graph transformation tradition, in which approaches are defined and studied using the language of category theory. Most algebraic graph transformation approaches (such as DPO, SPO, SqPO, and AGREE) are opinionated about the local contexts that are allowed around matches for rules, and about how replacement in context should work exactly. The approaches also differ considerably in their underlying formal theories and their general expressiveness (e.g., not all frameworks allow duplication). This dissertation proposes an expressive algebraic graph transformation approach, called PBPO+, which is an adaptation of PBPO by Corradini et al. The central contribution is a proof that PBPO+ subsumes (under mild restrictions) DPO, SqPO, AGREE, and PBPO in the important categorical setting of quasitoposes. This result allows for a more unified study of graph transformation metatheory, methods, and tools. A concrete example of this is found in the second major contribution of this dissertation: a graph transformation termination method for PBPO+, based on decreasing interpretations, and defined for general categories. By applying the proposed encodings into PBPO+, this method can also be applied for DPO, SqPO, AGREE, and PBPO

    Symmetries of Riemann surfaces and magnetic monopoles

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    This thesis studies, broadly, the role of symmetry in elucidating structure. In particular, I investigate the role that automorphisms of algebraic curves play in three specific contexts; determining the orbits of theta characteristics, influencing the geometry of the highly-symmetric Bring’s curve, and in constructing magnetic monopole solutions. On theta characteristics, I show how to turn questions on the existence of invariant characteristics into questions of group cohomology, compute comprehensive tables of orbit decompositions for curves of genus 9 or less, and prove results on the existence of infinite families of curves with invariant characteristics. On Bring’s curve, I identify key points with geometric significance on the curve, completely determine the structure of the quotients by subgroups of automorphisms, finding new elliptic curves in the process, and identify the unique invariant theta characteristic on the curve. With respect to monopoles, I elucidate the role that the Hitchin conditions play in determining monopole spectral curves, the relation between these conditions and the automorphism group of the curve, and I develop the theory of computing Nahm data of symmetric monopoles. As such I classify all 3-monopoles whose Nahm data may be solved for in terms of elliptic functions

    Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea

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    ObjectiveTo reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.MethodsWe used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.ResultsFollowing the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.ConclusionStrengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK

    An Extensible User Interface for Lean 4

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    Contemporary proof assistants rely on complex automation and process libraries with millions of lines of code. At these scales, understanding the emergent interactions between components can be a serious challenge. One way of managing complexity, long established in informal practice, is through varying external representations. For instance, algebraic notation facilitates term-based reasoning whereas geometric diagrams invoke spatial intuition. Objects viewed one way become much simpler than when viewed differently. In contrast, modern general-purpose ITP systems usually only support limited, textual representations. Treating this as a problem of human-computer interaction, we aim to demonstrate that presentations - UI elements that store references to the objects they are displaying - are a fruitful way of thinking about ITP interface design. They allow us to make headway on two fronts - introspection of prover internals and support for diagrammatic reasoning. To this end we have built an extensible user interface for the Lean 4 prover with an associated ProofWidgets 4 library of presentation-based UI components. We demonstrate the system with several examples including type information popups, structured traces, contextual suggestions, a display for algebraic reasoning, and visualizations of red-black trees. Our interface is already part of the core Lean distribution

    Engineering a Preprocessor for Symmetry Detection

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    State-of-the-art solvers for symmetry detection in combinatorial objects are becoming increasingly sophisticated software libraries. Most of the solvers were initially designed with inputs from combinatorics in mind (nauty, bliss, Traces, dejavu). They excel at dealing with a complicated core of the input. Others focus on practical instances that exhibit sparsity. They excel at dealing with comparatively easy but extremely large substructures of the input (saucy). In practice, these differences manifest in significantly diverging performances on different types of graph classes. We engineer a preprocessor for symmetry detection. The result is a tool designed to shrink sparse, large substructures of the input graph. On most of the practical instances, the preprocessor improves the overall running time significantly for many of the state-of-the-art solvers. At the same time, our benchmarks show that the additional overhead is negligible. Overall we obtain single algorithms with competitive performance across all benchmark graphs. As such, the preprocessor bridges the disparity between solvers that focus on combinatorial graphs and large practical graphs. In fact, on most of the practical instances the combined setup significantly outperforms previous state-of-the-art

    Bootstrapping extensionality

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    Intuitionistic type theory is a formal system designed by Per Martin-Loef to be a full-fledged foundation in which to develop constructive mathematics. One particular variant, intensional type theory (ITT), features nice computational properties like decidable type-checking, making it especially suitable for computer implementation. However, as traditionally defined, ITT lacks many vital extensionality principles, such as function extensionality. We would like to extend ITT with the desired extensionality principles while retaining its convenient computational behaviour. To do so, we must first understand the extent of its expressive power, from its strengths to its limitations. The contents of this thesis are an investigation into intensional type theory, and in particular into its power to express extensional concepts. We begin, in the first part, by developing an extension to the strict setoid model of type theory with a universe of setoids. The model construction is carried out in a minimal intensional type theoretic metatheory, thus providing a way to bootstrap extensionality by ``compiling'' it down to a few building blocks such as inductive families and proof-irrelevance. In the second part of the thesis we explore inductive-inductive types (ITTs) and their relation to simpler forms of induction in an intensional setting. We develop a general method to reduce a subclass of infinitary IITs to inductive families, via an encoding that can be expressed in ITT without any extensionality besides proof-irrelevance. Our results contribute to further understand IITs and the expressive power of intensional type theory, and can be of practical use when formalizing mathematics in proof assistants that do not natively support induction-induction

    30th European Congress on Obesity (ECO 2023)

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    This is the abstract book of 30th European Congress on Obesity (ECO 2023
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