Institution
University of Southern Denmark
Education•Odense, Syddanmark, Denmark•
About: University of Southern Denmark is a education organization based out in Odense, Syddanmark, Denmark. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 11928 authors who have published 37918 publications receiving 1258559 citations. The organization is also known as: SDU.
Papers published on a yearly basis
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Monash University1, University of Amsterdam2, University of Paris3, Bond University4, University of Texas Health Science Center at San Antonio5, University of Ottawa6, American University of Beirut7, Oregon Health & Science University8, University of York9, Ottawa Hospital Research Institute10, University of Southern Denmark11, Johns Hopkins University12, Brigham and Women's Hospital13, Indiana University14, University of Bristol15, University College London16, University of Toronto17
TL;DR: The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement as discussed by the authors was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found.
Abstract: The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, published in 2009, was designed to help systematic reviewers transparently report why the review was done, what the authors did, and what they found. Over the past decade, advances in systematic review methodology and terminology have necessitated an update to the guideline. The PRISMA 2020 statement replaces the 2009 statement and includes new reporting guidance that reflects advances in methods to identify, select, appraise, and synthesise studies. The structure and presentation of the items have been modified to facilitate implementation. In this article, we present the PRISMA 2020 27-item checklist, an expanded checklist that details reporting recommendations for each item, the PRISMA 2020 abstract checklist, and the revised flow diagrams for original and updated reviews.
16,613 citations
University of Bristol1, University Hospitals Bristol NHS Foundation Trust2, Monash University3, Cochrane Collaboration4, French Institute of Health and Medical Research5, Paris Descartes University6, St George's, University of London7, University of York8, Queen Mary University of London9, Clinical Trial Service Unit10, Harvard University11, University of Oxford12, University of Southern Denmark13, Odense University Hospital14, University of Alberta15, University of Toronto16, University of Manchester17, Johns Hopkins University18, McGill University19, University College London20
TL;DR: The Cochrane risk-of-bias tool has been updated to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.
Abstract: Assessment of risk of bias is regarded as an essential component of a systematic review on the effects of an intervention. The most commonly used tool for randomised trials is the Cochrane risk-of-bias tool. We updated the tool to respond to developments in understanding how bias arises in randomised trials, and to address user feedback on and limitations of the original tool.
9,228 citations
University of Bristol1, Harvard University2, University Hospitals Bristol NHS Foundation Trust3, Research Triangle Park4, University of Toronto5, University of Oxford6, University of Ottawa7, Paris Descartes University8, University of London9, University of York10, University of Birmingham11, University of Southern Denmark12, University of Liverpool13, University of East Anglia14, Loyola University Chicago15, University of Aberdeen16, Kaiser Permanente17, Baruch College18, McMaster University19, Cochrane Collaboration20, McGill University21, Ottawa Hospital Research Institute22, University of Louisville23, University of Melbourne24
TL;DR: Risk of Bias In Non-randomised Studies - of Interventions is developed, a new tool for evaluating risk of bias in estimates of the comparative effectiveness of interventions from studies that did not use randomisation to allocate units or clusters of individuals to comparison groups.
Abstract: Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.
8,028 citations
TL;DR: The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.
Abstract: Recent successes illustrate the role of mass spectrometry-based proteomics as an indispensable tool for molecular and cellular biology and for the emerging field of systems biology. These include the study of protein-protein interactions via affinity-based isolations on a small and proteome-wide scale, the mapping of numerous organelles, the concurrent description of the malaria parasite genome and proteome, and the generation of quantitative protein profiles from diverse species. The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.
6,597 citations
TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as discussed by the authors, the authors used the GBD 2010 methods with some refinements to improve accuracy applied to an updated database of vital registration, survey, and census data.
5,792 citations
Authors
Showing all 12150 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Bente Klarlund Pedersen | 134 | 689 | 72177 |
| Joel N. Hirschhorn | 133 | 431 | 101061 |
| Philipp E. Scherer | 132 | 522 | 74300 |
| Paul M. Vanhoutte | 127 | 868 | 62177 |
| Bart W. Koes | 124 | 730 | 57630 |
| Matt McGue | 122 | 653 | 54733 |
| Henrik Toft Sørensen | 120 | 1591 | 74943 |
| Torben Hansen | 120 | 1058 | 89876 |
| Claudio Franceschi | 120 | 856 | 59868 |
| Guido Reifenberger | 116 | 425 | 57396 |
| Mark A. Hlatky | 115 | 553 | 65656 |
| Thorkild I. A. Sørensen | 114 | 747 | 60060 |
| Lars Køber | 114 | 1155 | 77298 |
| Jonathan L. Sessler | 111 | 997 | 48758 |
| William G. Iacono | 110 | 648 | 48886 |