108 research outputs found

    A development and assurance process for Medical Application Platform apps

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    Doctor of PhilosophyDepartment of Computing and Information SciencesJohn M. HatcliffMedical devices have traditionally been designed, built, and certified for use as monolithic units. A new vision of "Medical Application Platforms" (MAPs) is emerging that would enable compositional medical systems to be instantiated at the point of care from a collection of trusted components. This work details efforts to create a development environment for applications that run on these MAPs. The first contribution of this effort is a language and code generator that can be used to model and implement MAP applications. The language is a subset of the Architecture, Analysis and Design Language (AADL) that has been tailored to the platform-based environment of MAPs. Accompanying the language is software tooling that provides automated code generation targeting an existing MAP implementation. The second contribution is a new hazard analysis process called the Systematic Analysis of Faults and Errors (SAFE). SAFE is a modified version of the previously-existing System Theoretic Process Analysis (STPA), that has been made more rigorous, partially compositional, and easier. SAFE is not a replacement for STPA, however, rather it more effectively analyzes the hardware- and software-based elements of a full safety-critical system. SAFE has both manual and tool-assisted formats; the latter consists of AADL annotations that are designed to be used with the language subset from the first contribution. An automated report generator has also been implemented to accelerate the hazard analysis process. Third, this work examines how, independent of its place in the system hierarchy or the precise configuration of its environment, a component may contribute to the safety (or lack thereof) of an entire system. Based on this, we propose a reference model which generalizes notions of harm and the role of components in their environment so that they can be applied to components either in isolation or as part of a complete system. Connections between these formalisms and existing approaches for system composition and fault propagation are also established. This dissertation presents these contributions along with a review of relevant literature, evaluation of the SAFE process, and concludes with discussion of potential future work

    Prototyping Closed Loop Physiologic Control With the Medical Device Coordination Framework

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    Medical devices historically have been monolithic units – developed, validated, and approved by regulatory authorities as standalone entities. Despite the fact that modern medical devices increasingly incorporate connectivity mechanisms that enable device data to be streamed to electronic health records and displays that aggregate data from multiple devices, connectivity is not being leveraged to allow an integrated collection of devices to work together as a single system to automate clinical work flows. This is due, in part, to current regulatory policies which prohibit such interactions due to safety concerns. In previous work, we proposed an open source middleware framework and an accompanying model-based development environment that could be used to quickly implement medical device coordination applications – enabling a “systems of systems” paradigm for medical devices. Such a paradigm shows great promise for supporting many applications that increase both the safety and effectiveness of medical care as well as the efficiency of clinical workflows. In this paper, we report on our experience using our Medical Device Coordination Framework (MDCF) to carry out a rapid prototyping of one such application – a multi-device medical system that uses closed loop physiologic control to a affect better patient outcomes for Patient Controlled Anelgesic (PCA) pumps

    Estimation of country-level incidence of early-onset invasive Group B Streptococcus disease in infants using Bayesian methods.

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    Neonatal invasive disease caused by Group B Streptococcus (GBS) is responsible for much acute mortality and long-term morbidity. To guide development of better prevention strategies, including maternal vaccines that protect neonates against GBS, it is necessary to estimate the burden of this condition globally and in different regions. Here, we present a Bayesian model that estimates country-specific invasive GBS (iGBS) disease incidence in children aged 0 to 6 days. The model combines different types of epidemiological data, each of which has its own limitations: GBS colonization prevalence in pregnant women, risk of iGBS disease in children born to GBS-colonized mothers and direct estimates of iGBS disease incidence where available. In our analysis, we present country-specific maternal GBS colonization prevalence after adjustment for GBS detection assay used in epidemiological studies. We then integrate these results with other epidemiological data and estimate country-level incidence of iGBS disease including in countries with no studies that directly estimate incidence. We are able to simultaneously estimate two key epidemiological quantities: the country-specific incidence of early-onset iGBS disease, and the risk of iGBS disease in babies born to GBS-colonized women. Overall, we believe our method will contribute to a more comprehensive quantification of the global burden of this disease, inform cost-effectiveness assessments of potential maternal GBS vaccines and identify key areas where data are necessary

    Delineating associations of progressive pleuroparenchymal fibroelastosis in patients with pulmonary fibrosis

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    BACKGROUND: Computer quantification of baseline computed tomography (CT) radiological pleuroparenchymal fibroelastosis (PPFE) associates with mortality in idiopathic pulmonary fibrosis (IPF). We examined mortality associations of longitudinal change in computer-quantified PPFE-like lesions in IPF and fibrotic hypersensitivity pneumonitis (FHP). METHODS: Two CT scans 6-36 months apart were retrospectively examined in one IPF (n=414) and one FHP population (n=98). Annualised change in computerised upper-zone pleural surface area comprising radiological PPFE-like lesions (Δ-PPFE) was calculated. Δ-PPFE >1.25% defined progressive PPFE above scan noise. Mixed-effects models evaluated Δ-PPFE against change in visual CT interstitial lung disease (ILD) extent and annualised forced vital capacity (FVC) decline. Multivariable models were adjusted for age, sex, smoking history, baseline emphysema presence, antifibrotic use and diffusion capacity of the lung for carbon monoxide. Mortality analyses further adjusted for baseline presence of clinically important PPFE-like lesions and ILD change. RESULTS: Δ-PPFE associated weakly with ILD and FVC change. 22-26% of IPF and FHP cohorts demonstrated progressive PPFE-like lesions which independently associated with mortality in the IPF cohort (hazard ratio 1.25, 95% CI 1.16-1.34, p<0.0001) and the FHP cohort (hazard ratio 1.16, 95% CI 1.00-1.35, p=0.045). INTERPRETATION: Progression of PPFE-like lesions independently associates with mortality in IPF and FHP but does not associate strongly with measures of fibrosis progression

    Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

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    Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

    Global, regional, and national estimates of the population at increased risk of severe COVID-19 due to underlying health conditions in 2020: a modelling study

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    Background: The risk of severe COVID-19 if an individual becomes infected is known to be higher in older individuals and those with underlying health conditions. Understanding the number of individuals at increased risk of severe COVID-19 and how this varies between countries should inform the design of possible strategies to shield or vaccinate those at highest risk. Methods: We estimated the number of individuals at increased risk of severe disease (defined as those with at least one condition listed as “at increased risk of severe COVID-19” in current guidelines) by age (5-year age groups), sex, and country for 188 countries using prevalence data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 and UN population estimates for 2020. The list of underlying conditions relevant to COVID-19 was determined by mapping the conditions listed in GBD 2017 to those listed in guidelines published by WHO and public health agencies in the UK and the USA. We analysed data from two large multimorbidity studies to determine appropriate adjustment factors for clustering and multimorbidity. To help interpretation of the degree of risk among those at increased risk, we also estimated the number of individuals at high risk (defined as those that would require hospital admission if infected) using age-specific infection–hospitalisation ratios for COVID-19 estimated for mainland China and making adjustments to reflect country-specific differences in the prevalence of underlying conditions and frailty. We assumed males were twice at likely as females to be at high risk. We also calculated the number of individuals without an underlying condition that could be considered at increased risk because of their age, using minimum ages from 50 to 70 years. We generated uncertainty intervals (UIs) for our estimates by running low and high scenarios using the lower and upper 95% confidence limits for country population size, disease prevalences, multimorbidity fractions, and infection–hospitalisation ratios, and plausible low and high estimates for the degree of clustering, informed by multimorbidity studies. Findings: We estimated that 1·7 billion (UI 1·0–2·4) people, comprising 22% (UI 15–28) of the global population, have at least one underlying condition that puts them at increased risk of severe COVID-19 if infected (ranging from &lt;5% of those younger than 20 years to &gt;66% of those aged 70 years or older). We estimated that 349 million (186–787) people (4% [3–9] of the global population) are at high risk of severe COVID-19 and would require hospital admission if infected (ranging from &lt;1% of those younger than 20 years to approximately 20% of those aged 70 years or older). We estimated 6% (3–12) of males to be at high risk compared with 3% (2–7) of females. The share of the population at increased risk was highest in countries with older populations, African countries with high HIV/AIDS prevalence, and small island nations with high diabetes prevalence. Estimates of the number of individuals at increased risk were most sensitive to the prevalence of chronic kidney disease, diabetes, cardiovascular disease, and chronic respiratory disease. Interpretation: About one in five individuals worldwide could be at increased risk of severe COVID-19, should they become infected, due to underlying health conditions, but this risk varies considerably by age. Our estimates are uncertain, and focus on underlying conditions rather than other risk factors such as ethnicity, socioeconomic deprivation, and obesity, but provide a starting point for considering the number of individuals that might need to be shielded or vaccinated as the global pandemic unfolds. Funding: UK Department for International Development, Wellcome Trust, Health Data Research UK, Medical Research Council, and National Institute for Health Research

    The evolution of non-small cell lung cancer metastases in TRACERx

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    Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relaps

    The lure of postwar London:networks of people, print and organisations

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    TXS 0506+056 with Updated IceCube Data

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    Past results from the IceCube Collaboration have suggested that the blazar TXS 0506+056 is a potential source of astrophysical neutrinos. However, in the years since there have been numerous updates to event processing and reconstruction, as well as improvements to the statistical methods used to search for astrophysical neutrino sources. These improvements in combination with additional years of data have resulted in the identification of NGC 1068 as a second neutrino source candidate. This talk will re-examine time-dependent neutrino emission from TXS 0506+056 using the most recent northern-sky data sample that was used in the analysis of NGC 1068. The results of using this updated data sample to obtain a significance and flux fit for the 2014 TXS 0506+056 "untriggered" neutrino flare are reported

    Conditional normalizing flows for IceCube event reconstruction

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