1,481 research outputs found

    The future burden of lung cancer attributable to current modifiable behaviours: a pooled study of seven Australian cohorts

    Get PDF
    BACKGROUND: Knowledge of preventable disease and differences in disease burden can inform public health action to improve health and health equity. We quantified the future lung cancer burden preventable by behavioural modifications across Australia. METHODS: We pooled seven Australian cohort studies (n = 367 058) and linked them to national registries to identify lung cancers and deaths. We estimated population attributable fractions and their 95% confidence intervals (CIs) for modifiable risk factors, using risk estimates from the cohort data and risk factor exposure distribution from contemporary national health surveys. RESULTS: During the first 10-year follow-up, there were 2025 incident lung cancers and 20 349 deaths. Stopping current smoking could prevent 53.7% (95% CI, 50.0-57.2%) of lung cancers over 40 years and 18.3% (11.0-25.1%) in 10 years. The smoking-attributable burden is highest in males, those who smoke <20 cigarettes per day, are <75 years of age, unmarried, of lower educational attainment, live in remote areas or are healthy weight. Increasing physical activity and fruit consumption, if causal, could prevent 15.6% (6.9-23.4%) and 7.5% (1.3-13.3%) of the lung cancer burden, respectively. Jointly, the three behaviour modifications could prevent up to 63.0% (58.0-67.5%) of lung cancers in 40 years, and 31.2% (20.9-40.1%) or 43 300 cancers in 10 years. The preventable burden is highest among those with multiple risk factors. CONCLUSIONS: Smoking remains responsible for the highest burden of lung cancer in Australia. The uneven burden distribution distinguishes subgroups that could benefit the most from activities to control the world's deadliest cancer

    Antiepileptic drugs’ tolerability and safety – a systematic review and meta-analysis of adverse effects in dogs

    Get PDF
    <p>Various anti-epileptic drugs (AEDs) are used for the management of idiopathic epilepsy (IE) in dogs. Their safety profile is an important consideration for regulatory bodies, owners and prescribing clinicians. However, information on their adverse effects still remains limited with most of it derived from non-blinded non-randomized uncontrolled trials and case reports.</p><p><span>This poster won third place, which was presented at the Veterinary Evidence Today conference, Edinburgh November 1-3, 2016. </span></p><br /> <img src="https://www.veterinaryevidence.org/rcvskmod/icons/oa-icon.jpg" alt="Open Access" /

    Incidence and Prediction of Falls in Dementia: A Prospective Study in Older People

    Get PDF
    Falls are a major cause of morbidity and mortality in dementia, but there have been no prospective studies of risk factors for falling specific to this patient population, and no successful falls intervention/prevention trials. This prospective study aimed to identify modifiable risk factors for falling in older people with mild to moderate dementia.179 participants aged over 65 years were recruited from outpatient clinics in the UK (38 Alzheimer's disease (AD), 32 Vascular dementia (VAD), 30 Dementia with Lewy bodies (DLB), 40 Parkinson's disease with dementia (PDD), 39 healthy controls). A multifactorial assessment of baseline risk factors was performed and fall diaries were completed prospectively for 12 months. Dementia participants experienced nearly 8 times more incident falls (9118/1000 person-years) than controls (1023/1000 person-years; incidence density ratio: 7.58, 3.11-18.5). In dementia, significant univariate predictors of sustaining at least one fall included diagnosis of Lewy body disorder (proportional hazard ratio (HR) adjusted for age and sex: 3.33, 2.11-5.26), and history of falls in the preceding 12 months (HR: 2.52, 1.52-4.17). In multivariate analyses, significant potentially modifiable predictors were symptomatic orthostatic hypotension (HR: 2.13, 1.19-3.80), autonomic symptom score (HR per point 0-36: 1.055, 1.012-1.099), and Cornell depression score (HR per point 0-40: 1.053, 1.01-1.099). Higher levels of physical activity were protective (HR per point 0-9: 0.827, 0.716-0.956).The management of symptomatic orthostatic hypotension, autonomic symptoms and depression, and the encouragement of physical activity may provide the core elements for the most fruitful strategy to reduce falls in people with dementia. Randomised controlled trials to assess such a strategy are a priority

    Developing a feeling for error

    Get PDF
    This paper is based on ethnographic research of data practices in a public health project called Weather Health and Air Pollution. (All names are pseudonyms.) I examine two different kinds of practices that make air pollution data, focusing on how they relate to particular modes of sensing and articulating air pollution. I begin by describing the interstitial spaces involved in making measurements of air pollution at monitoring sites and in the running of a computer simulation. Specifically, I attend to a shared dimension of these practices, the checking of a numerical reading for error. Checking a measurement for error is routine practice and a fundamental component of making data, yet these are also moments of interpretation, where the form and meaning of numbers are ambiguous. Through two case studies of modelling and monitoring data practices, I show that making a ‘good’ (error free) measurement requires developing a feeling for the instrument–air pollution interaction in terms of the intended functionality of the measurements made. These affective dimensions of practice are useful analytically, making explicit the interaction of standardised ways of knowing and embodied skill in stabilising data. I suggest that environmental data practices can be studied through researchers’ materialisation of error, which complicate normative accounts of Big Data and highlight the non-linear and entangled relations that are at work in the making of stable, accurate data

    Maximum Likelihood Estimation of the Negative Binomial Dispersion Parameter for Highly Overdispersed Data, with Applications to Infectious Diseases

    Get PDF
    BACKGROUND: The negative binomial distribution is used commonly throughout biology as a model for overdispersed count data, with attention focused on the negative binomial dispersion parameter, k. A substantial literature exists on the estimation of k, but most attention has focused on datasets that are not highly overdispersed (i.e., those with k≥1), and the accuracy of confidence intervals estimated for k is typically not explored. METHODOLOGY: This article presents a simulation study exploring the bias, precision, and confidence interval coverage of maximum-likelihood estimates of k from highly overdispersed distributions. In addition to exploring small-sample bias on negative binomial estimates, the study addresses estimation from datasets influenced by two types of event under-counting, and from disease transmission data subject to selection bias for successful outbreaks. CONCLUSIONS: Results show that maximum likelihood estimates of k can be biased upward by small sample size or under-reporting of zero-class events, but are not biased downward by any of the factors considered. Confidence intervals estimated from the asymptotic sampling variance tend to exhibit coverage below the nominal level, with overestimates of k comprising the great majority of coverage errors. Estimation from outbreak datasets does not increase the bias of k estimates, but can add significant upward bias to estimates of the mean. Because k varies inversely with the degree of overdispersion, these findings show that overestimation of the degree of overdispersion is very rare for these datasets

    Lit up and left dark: Failures of imagination in urban broadband networks

    Get PDF
    The design and deployment of urban broadband infrastructures inscribe particular imaginations of Internet access onto city streets. The different manifestations and locations of these networks, their uses, and access points often expose material excesses of urban broadband networks, as well as failures of Internet service providers, urban planners, and public officials to imagine the diverse ways that people incorporate Internet connection into their everyday lives. We approach the study of urban broadband networks through the juxtaposition of invisible networks that are buried under the streets and have always been “turned off” (dark fiber) versus hypervisible that are “turned on” and prominently displayed on city streets (LinkNYC). In our analysis of these two case studies, we critique themes of visibility and invisibility as indexes of power and access. Our findings are meant to provide a critical analysis of urban technology policy as well as theories of infrastructure, visibility, and access

    Evaluation of a Previously Suggested Plasma Biomarker Panel to Identify Alzheimer's Disease

    Get PDF
    There is an urgent need for biomarkers in plasma to identify Alzheimer's disease (AD). It has previously been shown that a signature of 18 plasma proteins can identify AD during pre-dementia and dementia stages (Ray et al, Nature Medicine, 2007). We quantified the same 18 proteins in plasma from 174 controls, 142 patients with AD, and 88 patients with other dementias. Only three of these proteins (EGF, PDG-BB and MIP-1δ) differed significantly in plasma between controls and AD. The 18 proteins could classify patients with AD from controls with low diagnostic precision (area under the ROC curve was 63%). Moreover, they could not distinguish AD from other dementias. In conclusion, independent validation of results is important in explorative biomarker studies

    Impacts of climate change on plant diseases – opinions and trends

    Get PDF
    There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

    Screening of healthcare workers for SARS-CoV-2 highlights the role of asymptomatic carriage in COVID-19 transmission.

    Get PDF
    Significant differences exist in the availability of healthcare worker (HCW) SARS-CoV-2 testing between countries, and existing programmes focus on screening symptomatic rather than asymptomatic staff. Over a 3 week period (April 2020), 1032 asymptomatic HCWs were screened for SARS-CoV-2 in a large UK teaching hospital. Symptomatic staff and symptomatic household contacts were additionally tested. Real-time RT-PCR was used to detect viral RNA from a throat+nose self-swab. 3% of HCWs in the asymptomatic screening group tested positive for SARS-CoV-2. 17/30 (57%) were truly asymptomatic/pauci-symptomatic. 12/30 (40%) had experienced symptoms compatible with coronavirus disease 2019 (COVID-19)>7 days prior to testing, most self-isolating, returning well. Clusters of HCW infection were discovered on two independent wards. Viral genome sequencing showed that the majority of HCWs had the dominant lineage B∙1. Our data demonstrates the utility of comprehensive screening of HCWs with minimal or no symptoms. This approach will be critical for protecting patients and hospital staff.This work was supported by the Wellcome Trust Senior Research Fellowships 108070/Z/15/Z to MPW, 215515/Z/19/Z to SGB and 207498/Z/17/Z to IGG; Collaborative award 206298/B/17/Z to IGG; Principal Research Fellowship 210688/Z/18/Z to PJL; Investigator Award 200871/Z/16/Z to KGCS; Addenbrooke’s Charitable Trust (to MPW, SGB, IGG and PJL); the Medical Research Council (CSF MR/P008801/1 to NJM); NHS Blood and Transfusion (WPA15-02 to NJM); National Institute for Health Research (Cambridge Biomedical Research Centre at CUHNFT), to JRB, MET, AC and GD, Academy of Medical Sciences and the Health Foundation (Clinician Scientist Fellowship to MET), Engineering and Physical Sciences Research Council (EP/P031447/1 and EP/N031938/1 to RS),Cancer Research UK (PRECISION Grand Challenge C38317/A24043 award to JY). Components of this work were supported by the COVID-19 Genomics UK Consortium, (COG-UK), which is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institut
    corecore