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Utrecht University

EducationUtrecht, Utrecht, Netherlands
About: Utrecht University is a education organization based out in Utrecht, Utrecht, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 58176 authors who have published 139351 publications receiving 6214282 citations. The organization is also known as: UU & Universiteit Utrecht.


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Journal ArticleDOI
TL;DR: To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS, and the accuracy of antibodies for use in seroprevalence surveys is assessed.
Abstract: Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and resulting COVID-19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify current infection, rule out infection, identify people in need of care escalation, or to test for past infection and immune response. Serology tests to detect the presence of antibodies to SARS-CoV-2 aim to identify previous SARS-CoV-2 infection, and may help to confirm the presence of current infection. Objectives To assess the diagnostic accuracy of antibody tests to determine if a person presenting in the community or in primary or secondary care has SARS-CoV-2 infection, or has previously had SARS-CoV-2 infection, and the accuracy of antibody tests for use in seroprevalence surveys. Search methods We undertook electronic searches in the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 27 April 2020. Selection criteria We included test accuracy studies of any design that evaluated antibody tests (including enzyme-linked immunosorbent assays, chemiluminescence immunoassays, and lateral flow assays) in people suspected of current or previous SARS-CoV-2 infection, or where tests were used to screen for infection. We also included studies of people either known to have, or not to have SARS-CoV-2 infection. We included all reference standards to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR) and clinical diagnostic criteria). Data collection and analysis We assessed possible bias and applicability of the studies using the QUADAS-2 tool. We extracted 2x2 contingency table data and present sensitivity and specificity for each antibody (or combination of antibodies) using paired forest plots. We pooled data using random-effects logistic regression where appropriate, stratifying by time since post-symptom onset. We tabulated available data by test manufacturer. We have presented uncertainty in estimates of sensitivity and specificity using 95% confidence intervals (CIs). Main results We included 57 publications reporting on a total of 54 study cohorts with 15,976 samples, of which 8526 were from cases of SARS-CoV-2 infection. Studies were conducted in Asia (n = 38), Europe (n = 15), and the USA and China (n = 1). We identified data from 25 commercial tests and numerous in-house assays, a small fraction of the 279 antibody assays listed by the Foundation for Innovative Diagnostics. More than half (n = 28) of the studies included were only available as preprints. We had concerns about risk of bias and applicability. Common issues were use of multi-group designs (n = 29), inclusion of only COVID-19 cases (n = 19), lack of blinding of the index test (n = 49) and reference standard (n = 29), differential verification (n = 22), and the lack of clarity about participant numbers, characteristics and study exclusions (n = 47). Most studies (n = 44) only included people hospitalised due to suspected or confirmed COVID-19 infection. There were no studies exclusively in asymptomatic participants. Two-thirds of the studies (n = 33) defined COVID-19 cases based on RT-PCR results alone, ignoring the potential for false-negative RT-PCR results. We observed evidence of selective publication of study findings through omission of the identity of tests (n = 5). We observed substantial heterogeneity in sensitivities of IgA, IgM and IgG antibodies, or combinations thereof, for results aggregated across different time periods post-symptom onset (range 0% to 100% for all target antibodies). We thus based the main results of the review on the 38 studies that stratified results by time since symptom onset. The numbers of individuals contributing data within each study each week are small and are usually not based on tracking the same groups of patients over time. Pooled results for IgG, IgM, IgA, total antibodies and IgG/IgM all showed low sensitivity during the first week since onset of symptoms (all less than 30.1%), rising in the second week and reaching their highest values in the third week. The combination of IgG/IgM had a sensitivity of 30.1% (95% CI 21.4 to 40.7) for 1 to 7 days, 72.2% (95% CI 63.5 to 79.5) for 8 to 14 days, 91.4% (95% CI 87.0 to 94.4) for 15 to 21 days. Estimates of accuracy beyond three weeks are based on smaller sample sizes and fewer studies. For 21 to 35 days, pooled sensitivities for IgG/IgM were 96.0% (95% CI 90.6 to 98.3). There are insufficient studies to estimate sensitivity of tests beyond 35 days post-symptom onset. Summary specificities (provided in 35 studies) exceeded 98% for all target antibodies with confidence intervals no more than 2 percentage points wide. False-positive results were more common where COVID-19 had been suspected and ruled out, but numbers were small and the difference was within the range expected by chance. Assuming a prevalence of 50%, a value considered possible in healthcare workers who have suffered respiratory symptoms, we would anticipate that 43 (28 to 65) would be missed and 7 (3 to 14) would be falsely positive in 1000 people undergoing IgG/IgM testing at days 15 to 21 post-symptom onset. At a prevalence of 20%, a likely value in surveys in high-risk settings, 17 (11 to 26) would be missed per 1000 people tested and 10 (5 to 22) would be falsely positive. At a lower prevalence of 5%, a likely value in national surveys, 4 (3 to 7) would be missed per 1000 tested, and 12 (6 to 27) would be falsely positive. Analyses showed small differences in sensitivity between assay type, but methodological concerns and sparse data prevent comparisons between test brands. Authors' conclusions The sensitivity of antibody tests is too low in the first week since symptom onset to have a primary role for the diagnosis of COVID-19, but they may still have a role complementing other testing in individuals presenting later, when RT-PCR tests are negative, or are not done. Antibody tests are likely to have a useful role for detecting previous SARS-CoV-2 infection if used 15 or more days after the onset of symptoms. However, the duration of antibody rises is currently unknown, and we found very little data beyond 35 days post-symptom onset. We are therefore uncertain about the utility of these tests for seroprevalence surveys for public health management purposes. Concerns about high risk of bias and applicability make it likely that the accuracy of tests when used in clinical care will be lower than reported in the included studies. Sensitivity has mainly been evaluated in hospitalised patients, so it is unclear whether the tests are able to detect lower antibody levels likely seen with milder and asymptomatic COVID-19 disease. The design, execution and reporting of studies of the accuracy of COVID-19 tests requires considerable improvement. Studies must report data on sensitivity disaggregated by time since onset of symptoms. COVID-19-positive cases who are RT-PCR-negative should be included as well as those confirmed RT-PCR, in accordance with the World Health Organization (WHO) and China National Health Commission of the People's Republic of China (CDC) case definitions. We were only able to obtain data from a small proportion of available tests, and action is needed to ensure that all results of test evaluations are available in the public domain to prevent selective reporting. This is a fast-moving field and we plan ongoing updates of this living systematic review.

651 citations

Journal ArticleDOI
08 Oct 2020-Nature
TL;DR: A global N2O inventory is presented that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N 2O emissions, using bottom-up, top-down and process-based model approaches.
Abstract: Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum-maximum estimates: 12.2-23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9-17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2-11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies-particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O-climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

650 citations

Journal ArticleDOI
TL;DR: As light availability in the forest is generally much lower than this threshold level, it follows that interspecific variation in growth in a forest environment is mainly owing to variation in morphology.
Abstract: 1. Growth of seedlings of 15 rain-forest tree species was compared under controlled conditions, at six different light levels (3, 6, 12, 25, 50 and 100% daylight). 2. Most plant variables showed strong ontogenetic changes; they were highly dependent on the biomass of the plant. 3. Growth rate was highest at intermediate light levels (25–50%) above which it declined. Most plant variables showed a curvilinear response to irradiance, with the largest changes at the lowest light levels. 4. There was a consistent ranking in growth between species; species that were fast growing in a low-light environment were also fast growing in a high-light environment. 5. At low light, interspecific variation in relative growth rate was determined mainly by differences in a morphological trait, the leaf area ratio (LAR), whereas at high light it was determined mainly by differences in a physiological trait, the net assimilation rate (NAR). 6. NAR became a stronger determinant of growth than LAR in more than 10–15% daylight. As light availability in the forest is generally much lower than this threshold level, it follows that interspecific variation in growth in a forest environment is mainly owing to variation in morphology.

650 citations

Journal ArticleDOI
31 May 2018
TL;DR: The success of MRSA is a consequence of the extensive arsenal of virulence factors produced by S. aureus combined with β-lactam resistance and, for most clones, resistance to other antibiotic classes as discussed by the authors.
Abstract: Since the 1960s, methicillin-resistant Staphylococcus aureus (MRSA) has emerged, disseminated globally and become a leading cause of bacterial infections in both health-care and community settings. However, there is marked geographical variation in MRSA burden owing to several factors, including differences in local infection control practices and pathogen-specific characteristics of the circulating clones. Different MRSA clones have resulted from the independent acquisition of staphylococcal cassette chromosome mec (SCCmec), which contains genes encoding proteins that render the bacterium resistant to most β-lactam antibiotics (such as methicillin), by several S. aureus clones. The success of MRSA is a consequence of the extensive arsenal of virulence factors produced by S. aureus combined with β-lactam resistance and, for most clones, resistance to other antibiotic classes. Clinical manifestations of MRSA range from asymptomatic colonization of the nasal mucosa to mild skin and soft tissue infections to fulminant invasive disease with high mortality. Although treatment options for MRSA are limited, several new antimicrobials are under development. An understanding of colonization dynamics, routes of transmission, risk factors for progression to infection and conditions that promote the emergence of resistance will enable optimization of strategies to effectively control MRSA. Vaccine candidates are also under development and could become an effective prevention measure.

650 citations

Journal ArticleDOI
01 Aug 2003-Stroke
TL;DR: Risk factors for ICH appeared to be age, male sex, hypertension, and high alcohol intake, while high cholesterol tends to be associated with a lower risk of ICH.
Abstract: Background and Purpose— Although data on some risk factors for intracerebral hemorrhage (ICH) already are beyond doubt, for other factors, the evidence is less clear. We performed a systematic overview of case-control and cohort studies on risk factors for ICH. Methods— We searched MEDLINE, LILACS, EXTRAMED, and Pascal from 1966 to 2001 to identify studies. Studies were included if they met predefined methodological criteria. When possible, 2×2 tables were extracted and combined with the Mantel-Haenszel method. Summary odds ratios (ORs) were calculated for case-control studies, and summary relative risks (RRs) were found for cohort studies and for case-control and cohort studies combined. Results— Fourteen case-control and 11 cohort studies were identified. We could not always combine the results of case-control and cohort studies. In cohort studies, the crude RR for age (every 10-year increase) was 1.97 (95% confidence interval [CI], 1.79 to 2.16). In case-control studies, the crude OR for high alcohol i...

649 citations


Authors

Showing all 58756 results

NameH-indexPapersCitations
Ronald C. Kessler2741332328983
Albert Hofman2672530321405
Douglas G. Altman2531001680344
Hans Clevers199793169673
Craig B. Thompson195557173172
Patrick W. Serruys1862427173210
Ruedi Aebersold182879141881
Dennis S. Charney179802122408
Kenneth S. Kendler1771327142251
Jean Louis Vincent1611667163721
Vilmundur Gudnason159837123802
Monique M.B. Breteler15954693762
Lex M. Bouter158767103034
Elio Riboli1581136110499
Roy F. Baumeister157650132987
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023429
20221,014
20218,993
20208,578
20197,862
20187,020