Publications by authors named "Hutchings A"

Background: Takayasu arteritis (TAK) and giant cell arteritis (GCA), the most common forms of large-vessel vasculitis (LVV), can result in serious morbidity. Understanding the molecular basis of LVV should aid in developing better biomarkers and treatments.

Methods: Plasma proteomic profiling of 184 proteins was performed in two cohorts.

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Alkaline lakes are thought to have facilitated prebiotic synthesis reactions on the early Earth because their modern analogs accumulate vital chemical feedstocks such as phosphate through the evaporation of dilute groundwaters. Yet, the conditions required for some building block synthesis reactions are distinct from others, and these conditions are generally incompatible with those permissible for nascent cellular function. However, because current scenarios for prebiotic synthesis have not taken account of the physical processes that drive the chemical evolution of alkaline lakes, the potential for the co-occurrence of both prebiotic synthesis and the origins and early evolution of life in prebiotic alkaline lake environments remains poorly constrained.

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Background: Machine learning (ML) methods can identify complex patterns of treatment effect heterogeneity. However, before ML can help to personalize decision making, transparent approaches must be developed that draw on clinical judgment. We develop an approach that combines clinical judgment with ML to generate appropriate comparative effectiveness evidence for informing decision making.

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Increasing evidence suggests an essential function for autophagy in unconventional protein secretion (UPS). However, despite its relevance for the secretion of aggregate-prone proteins, the mechanisms of secretory autophagy in neurons have remained elusive. Here we show that the lower motoneuron disease-associated guanine exchange factor Plekhg5 drives the UPS of Sod1.

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Background: Policymakers across countries promote cross-sector collaboration as a route to improving health and health equity. In England, major health system reforms in 2022 established 42 integrated care systems (ICSs)-area-based partnerships between health care, social care, public health, and other sectors-to plan and coordinate local services. ICSs cover the whole of England and have been given explicit policy objectives to reduce health inequalities, alongside other national priorities.

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Objectives: Major reforms to the organisation of the National Health Service (NHS) in England established 42 integrated care systems (ICSs) to plan and coordinate local services. The changes are based on the idea that cross-sector collaboration is needed to improve health and reduce health inequalities-and similar policy changes are happening elsewhere in the UK and internationally. We explored local interpretations of national policy objectives on reducing health inequalities among senior leaders working in three ICSs.

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Objectives: International health technology assessment (HTA) agencies recommend that real-world data (RWD) are used in some circumstances to add to the evidence base about the effectiveness and cost-effectiveness of health interventions. The target trial framework applies the design principles of randomized-controlled trials to RWD and can help alleviate inevitable concerns about bias and design flaws with nonrandomized studies. This article aimed to tackle the lack of guidance and exemplar applications on how this methodology can be applied to RWD to inform HTA decision making.

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Background: The COVID-19 pandemic brought rapid and major changes to research, and those wishing to carry out Patient and Public Involvement (PPI) activities faced challenges, such as restrictions on movement and contact, illness, bereavement and risks to potential participants. Some researchers moved PPI to online settings during this time but remote consultations raise, as well as address, a number of challenges. It is important to learn from PPI undertaken in this period as face-to-face consultation may no longer be the dominant method for PPI.

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Objective: To develop and validate updated classification criteria for giant cell arteritis (GCA).

Methods: Patients with vasculitis or comparator diseases were recruited into an international cohort. The study proceeded in six phases: (1) identification of candidate items, (2) prospective collection of candidate items present at the time of diagnosis, (3) expert panel review of cases, (4) data-driven reduction of candidate items, (5) derivation of a points-based risk classification score in a development data set and (6) validation in an independent data set.

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Objective: To develop and validate new classification criteria for Takayasu arteritis (TAK).

Methods: Patients with vasculitis or comparator diseases were recruited into an international cohort. The study proceeded in six phases: (1) identification of candidate criteria items, (2) collection of candidate items present at diagnosis, (3) expert panel review of cases, (4) data-driven reduction of candidate items, (5) derivation of a points-based classification score in a development data set and (6) validation in an independent data set.

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Article Synopsis
  • The study aimed to create and validate new classification criteria for giant cell arteritis (GCA) through a structured, multi-phase approach involving expert review and data analysis.
  • The final criteria for classifying GCA include specific test results and symptoms, with a scoring system where a total of 6 points or more indicates a positive classification.
  • Testing of these criteria showed high accuracy, with a sensitivity of 87% and specificity of 94.8%, leading to their validation for use in clinical research by the American College of Rheumatology/EULAR.
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Objective: To develop and validate new classification criteria for Takayasu arteritis (TAK).

Methods: Patients with vasculitis or comparator diseases were recruited into an international cohort. The study proceeded in 6 phases: 1) identification of candidate criteria items, 2) collection of candidate items present at diagnosis, 3) expert panel review of cases, 4) data-driven reduction of candidate items, 5) derivation of a points-based classification score in a development data set, and 6) validation in an independent data set.

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Background: This study assessed the impact of the first COVID-19 wave in England on outcomes for acute appendicitis, gallstone disease, intestinal obstruction, diverticular disease, and abdominal wall hernia.

Methods: Emergency surgical admissions for patients aged 18 years and older to 124 NHS Trust hospitals between January and June in 2019 and 2020 were extracted from Hospital Episode Statistics. The risk of 90-day mortality after admission during weeks 11-19 in 2020 (national lockdown) and 2019 (pre-COVID-19) was estimated using multilevel logistic regression with case-mix adjustment.

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Collaboration between local agencies is no replacement for national policy and investment, argue , , and

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Objective: To evaluate the impact of the 'Getting it Right First Time' (GIRFT) national improvement programme in orthopaedics, which started in 2012.

Design: Mixed-methods study comprising statistical analysis of linked national datasets (National Joint Registry; Hospital Episode Statistics; Patient-Reported Outcomes); economic analysis and qualitative case studies in six National Health Service (NHS) Trusts.

Setting: NHS elective orthopaedic surgery in England.

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Background: Electronic health records (EHRs) offer opportunities for comparative effectiveness research to inform decision making. However, to provide useful evidence, these studies must address confounding and treatment effect heterogeneity according to unmeasured prognostic factors. Local instrumental variable (LIV) methods can help studies address these challenges, but have yet to be applied to EHR data.

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The effectiveness of emergency surgery vs. non-emergency surgery strategies for emergency admissions with acute appendicitis, gallstone disease, diverticular disease, abdominal wall hernia or intestinal obstruction is unknown. Data on emergency admissions for adult patients from 2010 to 2019 at 175 acute National Health Service hospitals in England were extracted from the Hospital Episode Statistics database.

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Population health management is an emerging technique to link and analyse patient data across several organisations in order to identify population needs and plan care. It is increasingly used in England and has become more important as health policy has sought to drive greater integration across health and care organisations. This protocol describes a mixed-methods process evaluation of an innovative population health management system in North Central London, England, serving a population of 1.

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Background: In response to the COVID-19 pandemic, the first vaccine was administered in December 2020 in England. However, vaccination uptake has historically been lower in London than in other English regions.

Methods: Mixed-methods: This comprised an analysis of cumulative percentage uptake across London between 8 December 2020 and 6 June 2021 by vaccine priority cohorts and ethnicity.

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Objectives: An increasing number of innovative therapies (e.g., gene- and cell-based treatments) have been developed in the past 20 years.

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Objective: To develop and validate revised classification criteria for eosinophilic granulomatosis with polyangiitis (EGPA).

Methods: Patients with vasculitis or comparator diseases were recruited into an international cohort. The study proceeded in five phases: (1) identification of candidate criteria items using consensus methodology, (2) prospective collection of candidate items present at the time of diagnosis, (3) data-driven reduction of the number of candidate items, (4) expert panel review of cases to define the reference diagnosis and (5) derivation of a points-based risk score for disease classification in a development set using least absolute shrinkage and selection operator logistic regression, with subsequent validation of performance characteristics in an independent set of cases and comparators.

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