Increased hemorrhagic transformation and altered infarct size and localization after experimental stroke in a rat model type 2 diabetes

<p>Abstract</p> <p>Background</p> <p>Interruption of flow through of cerebral blood vessels results in acute ischemic stroke. Subsequent breakdown of the blood brain barrier increases cerebral injury by the development of vasogenic edema and secondary hemorrhage known as hemorrhagic transformation (HT). Diabetes is a risk factor for stroke as well as poor outcome of stroke. The current study tested the hypothesis that diabetes-induced changes in the cerebral vasculature increase the risk of HT and augment ischemic injury.</p> <p>Methods</p> <p>Diabetic Goto-Kakizaki (GK) or control rats underwent 3 hours of middle cerebral artery occlusion and 21 h reperfusion followed by evaluation of infarct size, hemorrhage and neurological outcome.</p> <p>Results</p> <p>Infarct size was significantly smaller in GK rats (10 ± 2 vs 30 ± 4%, p < 0.001). There was significantly more frequent hematoma formation in the ischemic hemisphere in GK rats as opposed to controls. Cerebrovascular tortuosity index was increased in the GK model (1.13 ± 0.01 vs 1.34 ± 0.06, P < 0.001) indicative of changes in vessel architecture.</p> <p>Conclusion</p> <p>These findings provide evidence that there is cerebrovascular remodeling in diabetes. While diabetes-induced remodeling appears to prevent infarct expansion, these changes in blood vessels increase the risk for HT possibly exacerbating neurovascular damage due to cerebral ischemia/reperfusion in diabetes.</p

HIV testing within general practices in Europe : A mixed-methods systematic review

Funding Information: This work was supported by IWT (Belgium) and the ANRS (France) through the framework of HIVERA JTC 2014. Publisher Copyright: © 2018 The Author(s).Background: Late diagnosis of HIV infection remains a key challenge in Europe. It is acknowledged that general practitioners (GPs) may contribute greatly to early case finding, yet there is evidence that many diagnostic opportunities are being missed. To further promote HIV testing in primary care and to increase the utility of available research, the existing evidence has been synthesised in a systematic review adhering to the PRISMA guidelines. Methods: The databases PubMed, Scopus and Embase were searched for the period 2006-2017. Two authors judged independently on the eligibility of studies. Through a mixed-methods systematic review of 29 studies, we provide a description of HIV testing in general practices in Europe, including barriers and facilitators. Results: The findings of the study show that although various approaches to target patients are used by GPs, most tests are still carried out based on the patient's request. Several barriers obstruct HIV testing in general practice. Included are a lack of communication skills on sexual health, lack of knowledge about HIV testing recommendations and epidemic specificities, difficulties with using the complete list of clinical HIV indicator diseases and lack of experience in delivering and communicating test results. The findings also suggest that the provision of specific training, practical tools and promotion programmes has an impact on the testing performance of GPs. Conclusions: GPs could have an increased role in provider-initiated HIV-testing for early case finding. To achieve this objective, solutions to the reported barriers should be identified and testing criteria adapted to primary healthcare defined. Providing guidance and training to better identify priority groups for HIV testing, as well as information on the HIV epidemic's characteristics, will be fundamental to increasing awareness and testing by GPs.publishersversionPeer reviewe

The role of networks to overcome large-scale challenges in tomography: The non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological systematic review of health technology assessments

Background: Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. Methods: We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. Results: The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. Conclusions: The uptake of appropriate meta-analysis methods for synthesising evidence on diagnostic test accuracy in UK NIHR HTAs has improved in recent years. Future research should focus on other evidence requirements for cost-effectiveness assessment, threshold effects for quantitative tests and the impact of multiple diagnostic tests

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P &lt; 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men