130,381 research outputs found
COVID-19 and myocarditis: a systematic review and overview of current challenges
No full textMyocardial inflammation in COVID-19 has been documented. Its pathogenesis is not fully elucidated, but the two main theories foresee a direct role of ACE2 receptor and a hyperimmune response, which may also lead to isolated presentation of COVID-19-mediated myocarditis. The frequency and prognostic impact of COVID-19-mediated myocarditis is unknown. This review aims to summarise current evidence on this topic. We performed a systematic review of MEDLINE and Cochrane Library (1/12/19–30/09/20). We also searched clinicaltrials.gov for unpublished studies testing therapies with potential implication for COVID-19-mediated cardiovascular complication. Eligible studies had laboratory confirmed COVID-19 and a clinical and/or histological diagnosis of myocarditis by ESC or WHO/ISFC criteria. Reports of 38 cases were included (26 male patients, 24 aged < 50 years). The first histologically proven case was a virus-negative lymphocytic myocarditis; however, biopsy evidence of myocarditis secondary to SARS-CoV-2 cardiotropism has been recently demonstrated. Histological data was found in 12 cases (8 EMB and 4 autopsies) and CMR was the main imaging modality to confirm a diagnosis of myocarditis (25 patients). There was a substantial variability in biventricular systolic function during the acute episode and in therapeutic regimen used. Five patients died in hospital. Cause-effect relationship between SARS-CoV-2 infection and myocarditis is difficult to demonstrate. However, current evidence demonstrates myocardial inflammation with or without direct cardiomyocyte damage, suggesting different pathophysiology mechanisms responsible of COVID-mediated myocarditis. Established clinical approaches should be pursued until future evidence support different actions. Large multicentre registries are advisable to elucidate further
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Scholarly Communication and Publishing Lunch and Learn Talk #11: The ULS Open Access Author Fee Fund
No full textAt the May 2014 talk, you will learn about the ULS Open Access Author Fee Fund--what it is, why we do it, how it works, and how the program is going so far
The R&D Tax Incentives
No full textThis article sets out some background information and reflections of the author on the R&D tax incentive schemes included in the Common Corporate Tax Base (CCTB) Proposal. In particular the author analyzes the stimulus to private R&D through ad hoc tax incentives included in the CCTB Proposal and dives into the actual provisions included in the Proposal highlighting the most relevant issues connected with their design and interpretation. Moreover, the author explores the interaction between the CCTB Proposal and the granting by Member States of domestic R&D tax incentives
Echocardiography versus computed tomography and cardiac magnetic resonance for the detection of left heart thrombosis: a systematic review and meta-analysis
No full textBackground: Accurate and reproducible diagnostic techniques are essential to detect left-sided cardiac thrombi [either in the left ventricle (LV) or in the left atrial appendage (LAA)] and to guide the onset and duration of antithrombotic treatment while minimizing the risk for thromboembolic and hemorrhagic events. Methods: We conducted a systematic review and meta-analysis aiming to compare the diagnostic performance of transthoracic echocardiography (TTE) vs. cardiac magnetic resonance (CMR) for the detection of LV thrombi, and transesophageal echocardiography (TEE) vs. computed tomography (CT) for the detection of LAA thrombi. Results: Six studies were included in the first meta-analysis (TTE vs. CMR for LV thrombosis). Pooled sensitivity and specificity values were 62% [95% confidence interval (CI), 37–81%] and 97% (95% CI, 94–99%). The shape of the hierarchical summary receiver operating characteristic (HSROC) curve and the area under the curve (AUC) of 0.96 suggested a high accuracy. Ten studies were included in the second meta-analysis (CT versus TEE for LAA thrombosis). The pooled values of sensitivity and specificity were 97% (95% CI, 77–100%) and 94% (95% CI, 87–98%). The pooled diagnostic odds ratio (DOR) was 500 (95% CI, 52–4810), and the pooled likelihood ratios (LR + and LR−) were 17% (95% CI, 7–40%) and 3% (95% CI, 0–28%). The shape of the HSROC curve and 0.99 AUC suggested a high accuracy of CT vs. TEE. Conclusions: TTE is a fair alternative to DE-CMR for the identification of LV thrombi, while CT has a good accuracy compared to TEE for the detection of LAA thrombosis. PROSPERO registration: CRD42020185842
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