1,137 research outputs found

    Role of targeted therapies in rheumatic patients on COVID-19 outcomes: results from the COVIDSER study

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    Objectives: To analyse the effect of targeted therapies, either biological (b) disease-modifying antirheumatic drugs (DMARDs), targeted synthetic (ts) DMARDs and other factors (demographics, comorbidities or COVID-19 symptoms) on the risk of COVID-19 related hospitalisation in patients with inflammatory rheumatic diseases. Methods: The COVIDSER study is an observational cohort including 7782 patients with inflammatory rheumatic diseases. Multivariable logistic regression was used to estimate ORs and 95% CIs of hospitalisation. Antirheumatic medication taken immediately prior to infection, demographic characteristics, rheumatic disease diagnosis, comorbidities and COVID-19 symptoms were analysed. Results: A total of 426 cases of symptomatic COVID-19 from 1 March 2020 to 13 April 2021 were included in the analyses: 106 (24.9%) were hospitalised and 19 (4.4%) died. In multivariate-adjusted models, bDMARDs and tsDMARDs in combination were not associated with hospitalisation compared with conventional synthetic DMARDs (OR 0.55, 95% CI 0.24 to 1.25 of b/tsDMARDs, p=0.15). Tumour necrosis factor inhibitors (TNF-i) were associated with a reduced likelihood of hospitalisation (OR 0.32, 95% CI 0.12 to 0.82, p=0.018), whereas rituximab showed a tendency to an increased risk of hospitalisation (OR 4.85, 95% CI 0.86 to 27.2). Glucocorticoid use was not associated with hospitalisation (OR 1.69, 95% CI 0.81 to 3.55). A mix of sociodemographic factors, comorbidities and COVID-19 symptoms contribute to patients' hospitalisation. Conclusions: The use of targeted therapies as a group is not associated with COVID-19 severity, except for rituximab, which shows a trend towards an increased risk of hospitalisation, while TNF-i was associated with decreased odds of hospitalisation in patients with rheumatic disease. Other factors like age, male gender, comorbidities and COVID-19 symptoms do play a role.This Project has been financed by Bristol-Myers Squibb, Galapagos Biopharma Spain SLU, Gebro Pharma, Roche Farma and Sanofi Aventis

    Influence of Antisynthetase Antibodies Specificities on Antisynthetase Syndrome Clinical Spectrum TimeCourse

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    Introduction: Increased cardiovascular (CV) morbidity and mortality is observed in inflammatory joint diseases (IJDs) such as rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis. However, the management of CV disease in these conditions is far from being well established.Areas covered: This review summarizes the main epidemiologic, pathophysiological, and clinical risk factors of CV disease associated with IJDs. Less common aspects on early diagnosis and risk stratification of the CV disease in these conditions are also discussed. In Europe, the most commonly used risk algorithm in patients with IJDs is the modified SCORE index based on the revised recommendations proposed by the EULAR task force in 2017.Expert opinion: Early identification of IJD patients at high risk of CV disease is essential. It should include the use of complementary noninvasive imaging techniques. A multidisciplinary approach aimed to improve heart-healthy habits, including strict control of classic CV risk factors is crucial. Adequate management of the underlying IJD is also of main importance since the reduction of disease activity decreases the risk of CV events. Non-steroidal anti-inflammatory drugs may have a lesser harmful effect in IJD than in the general population, due to their anti-inflammatory effects along with other potential beneficial effects.This research was partially funded by FOREUM—Foundation for Research in Rheumatolog

    Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

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    Background Genome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease. Methods We did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation. Findings Between Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16–36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10−7). Interpretation These data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data. Funding The National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources)

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

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    Measurement of the Splitting Function in &ITpp &ITand Pb-Pb Collisions at root&ITsNN&IT=5.02 TeV

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    Data from heavy ion collisions suggest that the evolution of a parton shower is modified by interactions with the color charges in the dense partonic medium created in these collisions, but it is not known where in the shower evolution the modifications occur. The momentum ratio of the two leading partons, resolved as subjets, provides information about the parton shower evolution. This substructure observable, known as the splitting function, reflects the process of a parton splitting into two other partons and has been measured for jets with transverse momentum between 140 and 500 GeV, in pp and PbPb collisions at a center-of-mass energy of 5.02 TeV per nucleon pair. In central PbPb collisions, the splitting function indicates a more unbalanced momentum ratio, compared to peripheral PbPb and pp collisions.. The measurements are compared to various predictions from event generators and analytical calculations.Peer reviewe

    Measurement of the top quark forward-backward production asymmetry and the anomalous chromoelectric and chromomagnetic moments in pp collisions at √s = 13 TeV

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    Abstract The parton-level top quark (t) forward-backward asymmetry and the anomalous chromoelectric (d̂ t) and chromomagnetic (μ̂ t) moments have been measured using LHC pp collisions at a center-of-mass energy of 13 TeV, collected in the CMS detector in a data sample corresponding to an integrated luminosity of 35.9 fb−1. The linearized variable AFB(1) is used to approximate the asymmetry. Candidate t t ¯ events decaying to a muon or electron and jets in final states with low and high Lorentz boosts are selected and reconstructed using a fit of the kinematic distributions of the decay products to those expected for t t ¯ final states. The values found for the parameters are AFB(1)=0.048−0.087+0.095(stat)−0.029+0.020(syst),μ̂t=−0.024−0.009+0.013(stat)−0.011+0.016(syst), and a limit is placed on the magnitude of | d̂ t| < 0.03 at 95% confidence level. [Figure not available: see fulltext.

    Measurement of t(t)over-bar normalised multi-differential cross sections in pp collisions at root s=13 TeV, and simultaneous determination of the strong coupling strength, top quark pole mass, and parton distribution functions

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    Search for anomalous couplings in boosted WW/WZ -> l nu q(q)over-bar production in proton-proton collisions at root s=8TeV

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    An embedding technique to determine ττ backgrounds in proton-proton collision data

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    An embedding technique is presented to estimate standard model tau tau backgrounds from data with minimal simulation input. In the data, the muons are removed from reconstructed mu mu events and replaced with simulated tau leptons with the same kinematic properties. In this way, a set of hybrid events is obtained that does not rely on simulation except for the decay of the tau leptons. The challenges in describing the underlying event or the production of associated jets in the simulation are avoided. The technique described in this paper was developed for CMS. Its validation and the inherent uncertainties are also discussed. The demonstration of the performance of the technique is based on a sample of proton-proton collisions collected by CMS in 2017 at root s = 13 TeV corresponding to an integrated luminosity of 41.5 fb(-1).Peer reviewe
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