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Institution

Monash University

EducationMelbourne, Victoria, Australia
About: Monash University is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 35920 authors who have published 100681 publications receiving 3027002 citations.


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Journal ArticleDOI
Juanita A. Haagsma1, Nicholas Graetz1, Ian Bolliger1, Mohsen Naghavi1, Hideki Higashi1, Erin C Mullany1, Semaw Ferede Abera2, Jerry Puthenpurakal Abraham3, Koranteng Adofo4, Ubai Alsharif5, Emmanuel A. Ameh6, Walid Ammar, Carl Abelardo T. Antonio7, Lope H Barrero8, Tolesa Bekele9, Dipan Bose10, Alexandra Brazinova, Ferrán Catalá-López, Lalit Dandona1, Rakhi Dandona11, Paul I. Dargan12, Diego De Leo13, Louisa Degenhardt14, Sarah Derrett15, Samath D Dharmaratne16, Tim Driscoll17, Leilei Duan18, Sergey Petrovich Ermakov19, Farshad Farzadfar20, Valery L. Feigin21, Richard C. Franklin22, Belinda J. Gabbe23, Richard A. Gosselin24, Nima Hafezi-Nejad20, Randah R. Hamadeh25, Martha Híjar, Guoqing Hu26, Sudha Jayaraman27, Guohong Jiang, Yousef Khader28, Ejaz Ahmad Khan29, Sanjay Krishnaswami30, Chanda Kulkarni, Fiona Lecky31, Ricky Leung32, Raimundas Lunevicius33, Ronan A Lyons34, Marek Majdan, Amanda J. Mason-Jones35, Richard Matzopoulos36, Peter A. Meaney37, Wubegzier Mekonnen38, Ted R. Miller39, Charles Mock40, Rosana E. Norman41, Ricardo Orozco, Suzanne Polinder, Farshad Pourmalek42, Vafa Rahimi-Movaghar20, Amany H. Refaat43, David Rojas-Rueda, Nobhojit Roy44, David C. Schwebel45, Amira Shaheen46, Saeid Shahraz47, Vegard Skirbekk48, Kjetil Søreide49, Sergey Soshnikov, Dan J. Stein50, Bryan L. Sykes51, Karen M. Tabb52, Awoke Misganaw Temesgen, Eric Y. Tenkorang53, Alice Theadom21, Bach Xuan Tran54, Bach Xuan Tran55, Tommi Vasankari, Monica S. Vavilala40, Vasiliy Victorovich Vlassov56, Solomon Meseret Woldeyohannes57, Paul S. F. Yip58, Naohiro Yonemoto, Mustafa Z. Younis59, Chuanhua Yu60, Christopher J L Murray1, Theo Vos1 
Institute for Health Metrics and Evaluation1, College of Health Sciences, Bahrain2, Harvard University3, Kwame Nkrumah University of Science and Technology4, Charité5, Ahmadu Bello University6, University of the Philippines Manila7, Pontifical Xavierian University8, Madawalabu University9, World Bank10, Public Health Foundation of India11, Guy's and St Thomas' NHS Foundation Trust12, Griffith University13, University of New South Wales14, Massey University15, University of Peradeniya16, University of Sydney17, Chinese Center for Disease Control and Prevention18, Russian Academy of Sciences19, Tehran University of Medical Sciences20, Auckland University of Technology21, James Cook University22, Monash University23, University of California, San Francisco24, Arabian Gulf University25, Central South University26, Virginia Commonwealth University27, Jordan University of Science and Technology28, Health Services Academy29, Oregon Health & Science University30, University of Sheffield31, University at Albany, SUNY32, Aintree University Hospitals NHS Foundation Trust33, Swansea University34, University of York35, South African Medical Research Council36, Children's Hospital of Philadelphia37, Addis Ababa University38, Curtin University39, University of Washington40, Queensland University of Technology41, University of British Columbia42, Suez Canal University43, Karolinska Institutet44, University of Alabama at Birmingham45, An-Najah National University46, Tufts Medical Center47, Norwegian Institute of Public Health48, Stavanger University Hospital49, University of Cape Town50, University of California, Irvine51, University of Illinois at Urbana–Champaign52, St. John's University53, Johns Hopkins University54, Hanoi Medical University55, National Research University – Higher School of Economics56, University of Gondar57, University of Hong Kong58, Jackson State University59, Wuhan University60
TL;DR: An overview of injury estimates from the 2013 update of GBD is provided, with detailed information on incidence, mortality, DALYs and rates of change from 1990 to 2013 for 26 causes of injury, globally, by region and by country.
Abstract: Background The Global Burden of Diseases (GBD), Injuries, and Risk Factors study used the disability-adjusted life year (DALY) to quantify the burden of diseases, injuries, and risk factors. This paper provides an overview of injury estimates from the 2013 update of GBD, with detailed information on incidence, mortality, DALYs and rates of change from 1990 to 2013 for 26 causes of injury, globally, by region and by country. Methods Injury mortality was estimated using the extensive GBD mortality database, corrections for ill-defined cause of death and the cause of death ensemble modelling tool. Morbidity estimation was based on inpatient and outpatient data sets, 26 cause-of-injury and 47 nature-of-injury categories, and seven follow-up studies with patient-reported long-term outcome measures. Results In 2013, 973 million (uncertainty interval (UI) 942 to 993) people sustained injuries that warranted some type of healthcare and 4.8 million (UI 4.5 to 5.1) people died from injuries. Between 1990 and 2013 the global age-standardised injury DALY rate decreased by 31% (UI 26% to 35%). The rate of decline in DALY rates was significant for 22 cause-of-injury categories, including all the major injuries. Conclusions Injuries continue to be an important cause of morbidity and mortality in the developed and developing world. The decline in rates for almost all injuries is so prominent that it warrants a general statement that the world is becoming a safer place to live in. However, the patterns vary widely by cause, age, sex, region and time and there are still large improvements that need to be made.

883 citations

Journal ArticleDOI
TL;DR: Evidence is provided that clinically acceptable errors are possible in gait analysis, andVariability between studies, however, suggests that they are not always achieved.

882 citations

Journal ArticleDOI
TL;DR: A minimum set of common outcome measures for studies of COVID-19, which includes a measure of viral burden, patient survival, and patient progression through the health-care system by use of the WHO Clinical Progression Scale are urged.
Abstract: Summary Clinical research is necessary for an effective response to an emerging infectious disease outbreak. However, research efforts are often hastily organised and done using various research tools, with the result that pooling data across studies is challenging. In response to the needs of the rapidly evolving COVID-19 outbreak, the Clinical Characterisation and Management Working Group of the WHO Research and Development Blueprint programme, the International Forum for Acute Care Trialists, and the International Severe Acute Respiratory and Emerging Infections Consortium have developed a minimum set of common outcome measures for studies of COVID-19. This set includes three elements: a measure of viral burden (quantitative PCR or cycle threshold), a measure of patient survival (mortality at hospital discharge or at 60 days), and a measure of patient progression through the health-care system by use of the WHO Clinical Progression Scale, which reflects patient trajectory and resource use over the course of clinical illness. We urge investigators to include these key data elements in ongoing and future studies to expedite the pooling of data during this immediate threat, and to hone a tool for future needs.

882 citations

Journal ArticleDOI
06 Jun 2017-JAMA
TL;DR: More than 1 million pregnant women had gestational weight gain greater than or less than guideline recommendations, compared with weight gain within recommended levels, was associated with higher risk of adverse maternal and infant outcomes.
Abstract: Importance Body mass index (BMI) and gestational weight gain are increasing globally. In 2009, the Institute of Medicine (IOM) provided specific recommendations regarding the ideal gestational weight gain. However, the association between gestational weight gain consistent with theIOM guidelines and pregnancy outcomes is unclear. Objective To perform a systematic review, meta-analysis, and metaregression to evaluate associations between gestational weight gain above or below the IOM guidelines (gain of 12.5-18 kg for underweight women [BMI Data Sources and Study Selection Search of EMBASE, Evidence-Based Medicine Reviews, MEDLINE, and MEDLINE In-Process between January 1, 1999, and February 7, 2017, for observational studies stratified by prepregnancy BMI category and total gestational weight gain. Data Extraction and Synthesis Data were extracted by 2 independent reviewers. Odds ratios (ORs) and absolute risk differences (ARDs) per live birth were calculated using a random-effects model based on a subset of studies with available data. Main Outcomes and Measures Primary outcomes were small for gestational age (SGA), preterm birth, and large for gestational age (LGA). Secondary outcomes were macrosomia, cesarean delivery, and gestational diabetes mellitus. Results Of 5354 identified studies, 23 (n = 1 309 136 women) met inclusion criteria. Gestational weight gain was below or above guidelines in 23% and 47% of pregnancies, respectively. Gestational weight gain below the recommendations was associated with higher risk of SGA (OR, 1.53 [95% CI, 1.44-1.64]; ARD, 5% [95% CI, 4%-6%]) and preterm birth (OR, 1.70 [1.32-2.20]; ARD, 5% [3%-8%]) and lower risk of LGA (OR, 0.59 [0.55-0.64]; ARD, −2% [−10% to −6%]) and macrosomia (OR, 0.60 [0.52-0.68]; ARD, −2% [−3% to −1%]); cesarean delivery showed no significant difference (OR, 0.98 [0.96-1.02]; ARD, 0% [−2% to 1%]). Gestational weight gain above the recommendations was associated with lower risk of SGA (OR, 0.66 [0.63-0.69]; ARD, −3%; [−4% to −2%]) and preterm birth (OR, 0.77 [0.69-0.86]; ARD, −2% [−2% to −1%]) and higher risk of LGA (OR, 1.85 [1.76-1.95]; ARD, 4% [2%-5%]), macrosomia (OR, 1.95 [1.79-2.11]; ARD, 6% [4%-9%]), and cesarean delivery (OR, 1.30 [1.25-1.35]; ARD, 4% [3%-6%]). Gestational diabetes mellitus could not be evaluated because of the nature of available data. Conclusions and Relevance In this systematic review and meta-analysis of more than 1 million pregnant women, 47% had gestational weight gain greater than IOM recommendations and 23% had gestational weight gain less than IOM recommendations. Gestational weight gain greater than or less than guideline recommendations, compared with weight gain within recommended levels, was associated with higher risk of adverse maternal and infant outcomes.

881 citations

Journal ArticleDOI
TL;DR: The Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists, believes that it will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge.
Abstract: Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.

880 citations


Authors

Showing all 36568 results

NameH-indexPapersCitations
Bert Vogelstein247757332094
Kenneth W. Kinzler215640243944
David J. Hunter2131836207050
David R. Williams1782034138789
Yang Yang1712644153049
Lei Jiang1702244135205
Dongyuan Zhao160872106451
Christopher J. O'Donnell159869126278
Leif Groop158919136056
Mark E. Cooper1581463124887
Theo Vos156502186409
Mark J. Smyth15371388783
Rinaldo Bellomo1471714120052
Detlef Weigel14251684670
Geoffrey Burnstock141148899525
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023250
20221,020
20219,402
20208,419
20197,409
20186,437