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Institution

Brown University

EducationProvidence, Rhode Island, United States
About: Brown University is a education organization based out in Providence, Rhode Island, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 35778 authors who have published 90896 publications receiving 4471489 citations. The organization is also known as: brown.edu & Brown.


Papers
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Journal ArticleDOI
01 May 1984-Cancer
TL;DR: The utility of the Karnofsky Performance Status Scale as a valuable research tool when employed by trained observers is suggested and the relationship of the KPS to longevity in a population of terminal cancer patients documents its predictive validity.
Abstract: The Karnofsky Performance Status Scale (KPS) is widely used to quantify the functional status of cancer patients. However, limited data exist documenting its reliability and validity. The KPS is used in the National Hospice Study (NHS) as both a study eligibility criterion and an outcome measure. As part of intensive training, interviewers were instructed in and tested on guidelines for determining the KPS levels of patients. After 4 months of field experience, interviewers were again tested based on narrative patient descriptions. The interrator reliability of 47 NHS interviewers was found to be 0.97. The construct validity of the KPS was analyzed, and the KPS was found to be strongly related (P less than 0.001) to two other independent measures of patient functioning. Finally, the relationship of the KPS to longevity (r = 0.30) in a population of terminal cancer patients documents its predictive validity. These findings suggest the utility of the KPS as a valuable research tool when employed by trained observers.

965 citations

Book ChapterDOI
20 Aug 2002
TL;DR: This paper presents Aurora, a new DBMS that is currently under construction at Brandeis University, Brown University, and M.I.T. and describes the basic system architecture, a stream-oriented set of operators, optimization tactics, and support for real-time operation.
Abstract: This paper introduces monitoring applications, which we will show differ substantially from conventional business data processing. The fact that a software system must process and react to continual inputs from many sources (e.g., sensors) rather than from human operators requires one to rethink the fundamental architecture of a DBMS for this application area. In this paper, we present Aurora, a new DBMS that is currently under construction at Brandeis University, Brown University, and M.I.T. We describe the basic system architecture, a stream-oriented set of operators, optimization tactics, and support for real-time operation.

963 citations

Journal ArticleDOI
TL;DR: In this article, the imbalance between gross primary production (GPP) and ecosystem respiration (ER) was defined as a measure of the amount of carbon being transferred from one ecosystem to another.
Abstract: Recent projectionsofclimatic change havefocused a great deal of scientific and public attention on patterns of carbon (C) cycling as well as its controls, particularly the factors that determine whether an ecosystem is a net source or sink of atmospheric carbon dioxide (CO2). Net ecosystem production (NEP), a central concept in C-cycling research, has been used by scientists to represent two different concepts. We propose that NEP be restricted to just one of its two original definitions—the imbalance between gross primary production (GPP) and ecosystem respiration (ER). We further propose that a new term—net ecosystem carbon balance (NECB)—be applied to the net rate of C accumulation in (or loss from [negative sign]) ecosystems. Net ecosystem carbon balance differs from NEP when C fluxesotherthanCfixationandrespiration occur,or when inorganic C enters or leaves in dissolved form. These fluxes include the leaching loss or lateral transfer of C from the ecosystem; the emission of volatile organic C, methane, and carbon monoxide; and the release of soot and CO2 from fire. Carbon fluxes in addition to NEP are particularly important determinants of NECB over long time scales. However, even over short time scales, they are important in ecosystems such as streams, estuaries, wetlands, and cities. Recent technological advances have led to a diversity of approaches to the measurement of C fluxes at different temporal and spatial scales. These approaches frequently capture different components of NEP or NECB and can therefore be compared across scales only by carefully specifying the

962 citations

Journal ArticleDOI
Ali H. Mokdad1, Katherine Ballestros1, Michelle Echko1, Scott D Glenn1, Helen E Olsen1, Erin C Mullany1, Alexander Lee1, Abdur Rahman Khan2, Alireza Ahmadi3, Alireza Ahmadi4, Alize J. Ferrari5, Alize J. Ferrari6, Alize J. Ferrari1, Amir Kasaeian7, Andrea Werdecker, Austin Carter1, Ben Zipkin1, Benn Sartorius8, Benn Sartorius9, Berrin Serdar10, Bryan L. Sykes11, Christopher Troeger1, Christina Fitzmaurice1, Christina Fitzmaurice12, Colin D. Rehm13, Damian Santomauro6, Damian Santomauro5, Damian Santomauro1, Daniel Kim14, Danny V. Colombara1, David C. Schwebel15, Derrick Tsoi1, Dhaval Kolte16, Elaine O. Nsoesie1, Emma Nichols1, Eyal Oren17, Fiona J Charlson5, Fiona J Charlson1, Fiona J Charlson6, George C Patton18, Gregory A. Roth1, H. Dean Hosgood19, Harvey Whiteford1, Harvey Whiteford6, Harvey Whiteford5, Hmwe H Kyu1, Holly E. Erskine1, Holly E. Erskine6, Holly E. Erskine5, Hsiang Huang20, Ira Martopullo1, Jasvinder A. Singh15, Jean B. Nachega21, Jean B. Nachega22, Jean B. Nachega23, Juan Sanabria24, Juan Sanabria25, Kaja Abbas26, Kanyin Ong1, Karen M. Tabb27, Kristopher J. Krohn1, Leslie Cornaby1, Louisa Degenhardt1, Louisa Degenhardt28, Mark Moses1, Maryam S. Farvid29, Max Griswold1, Michael H. Criqui30, Michelle L. Bell31, Minh Nguyen1, Mitch T Wallin32, Mitch T Wallin33, Mojde Mirarefin1, Mostafa Qorbani, Mustafa Z. Younis34, Nancy Fullman1, Patrick Liu1, Paul S Briant1, Philimon Gona35, Rasmus Havmoller4, Ricky Leung36, Ruth W Kimokoti37, Shahrzad Bazargan-Hejazi38, Shahrzad Bazargan-Hejazi39, Simon I. Hay40, Simon I. Hay1, Simon Yadgir1, Stan Biryukov1, Stein Emil Vollset41, Stein Emil Vollset1, Tahiya Alam1, Tahvi Frank1, Talha Farid2, Ted R. Miller42, Ted R. Miller43, Theo Vos1, Till Bärnighausen29, Till Bärnighausen44, Tsegaye Telwelde Gebrehiwot45, Yuichiro Yano46, Ziyad Al-Aly47, Alem Mehari48, Alexis J. Handal49, Amit Kandel50, Ben Anderson51, Brian J. Biroscak52, Brian J. Biroscak31, Dariush Mozaffarian53, E. Ray Dorsey54, Eric L. Ding29, Eun-Kee Park55, Gregory R. Wagner29, Guoqing Hu56, Honglei Chen57, Jacob E. Sunshine51, Jagdish Khubchandani58, Janet L Leasher59, Janni Leung6, Janni Leung51, Joshua A. Salomon29, Jürgen Unützer51, Leah E. Cahill60, Leah E. Cahill29, Leslie T. Cooper61, Masako Horino, Michael Brauer62, Michael Brauer1, Nicholas J K Breitborde63, Peter J. Hotez64, Roman Topor-Madry65, Roman Topor-Madry66, Samir Soneji67, Saverio Stranges68, Spencer L. James1, Stephen M. Amrock69, Sudha Jayaraman70, Tejas V. Patel, Tomi Akinyemiju15, Vegard Skirbekk41, Vegard Skirbekk71, Yohannes Kinfu72, Zulfiqar A Bhutta73, Jost B. Jonas44, Christopher J L Murray1 
Institute for Health Metrics and Evaluation1, University of Louisville2, Kermanshah University of Medical Sciences3, Karolinska Institutet4, Centre for Mental Health5, University of Queensland6, Tehran University of Medical Sciences7, South African Medical Research Council8, University of KwaZulu-Natal9, University of Colorado Boulder10, University of California, Irvine11, Fred Hutchinson Cancer Research Center12, Montefiore Medical Center13, Northeastern University14, University of Alabama at Birmingham15, Brown University16, San Diego State University17, University of Melbourne18, Albert Einstein College of Medicine19, Cambridge Health Alliance20, Johns Hopkins University21, University of Pittsburgh22, University of Cape Town23, Marshall University24, Case Western Reserve University25, University of London26, University of Illinois at Urbana–Champaign27, National Drug and Alcohol Research Centre28, Harvard University29, University of California, San Diego30, Yale University31, Georgetown University32, Veterans Health Administration33, Jackson State University34, University of Massachusetts Boston35, State University of New York System36, Simmons College37, University of California, Los Angeles38, Charles R. Drew University of Medicine and Science39, University of Oxford40, Norwegian Institute of Public Health41, Curtin University42, Pacific Institute43, Heidelberg University44, Jimma University45, Northwestern University46, Washington University in St. Louis47, Howard University48, University of New Mexico49, University at Buffalo50, University of Washington51, University of South Florida52, Tufts University53, University of Rochester Medical Center54, Kosin University55, Central South University56, Michigan State University57, Ball State University58, Nova Southeastern University59, Dalhousie University60, Mayo Clinic61, University of British Columbia62, Ohio State University63, Baylor University64, Jagiellonian University Medical College65, Wrocław Medical University66, Dartmouth College67, University of Western Ontario68, Oregon Health & Science University69, Virginia Commonwealth University70, Columbia University71, University of Canberra72, Aga Khan University73
10 Apr 2018-JAMA
TL;DR: There are wide differences in the burden of disease at the state level and specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention.
Abstract: Introduction Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.

962 citations

Journal ArticleDOI
TL;DR: A CGA, with or without screening, and with follow-up, should be used in older cancer patients, in order to detect unaddressed problems, improve their functional status, and possibly their survival.
Abstract: Background: As more and more cancers occur in elderly people, oncologists are increasingly confronted with the necessity of integrating geriatric parameters in the treatment of their patients. Methods: The International Society of Geriatric Oncology (SIOG) created a task force to review the evidence on the use of a comprehensive geriatric assessment (CGA) in cancer patients. A systematic review of the evidence was conducted. Results: Several biological and clinical correlates of aging have been identified. Their relative weight and clinical usefulness is still poorly defined. There is strong evidence that a CGA detects many problems missed by a regular assessment in general geriatric and in cancer patients. There is also strong evidence that a CGA improves function and reduces hospitalization in the elderly. There is heterogeneous evidence that it improves survival and that it is cost-effective. There is corroborative evidence from a few studies conducted in cancer patients. Screening tools exist and were successfully used in settings such as the emergency room, but globally were poorly tested. The article contains recommendations for the use of CGA in research and clinical care for older cancer patients. Conclusions: A CGA, with or without screening, and with follow-up, should be used in older cancer patients, in order to detect unaddressed problems, improve their functional status, and possibly their survival. The task force cannot recommend any specific tool or approach above others at this point and general geriatric experience should be used.

962 citations


Authors

Showing all 36143 results

NameH-indexPapersCitations
Walter C. Willett3342399413322
Robert Langer2812324326306
Robert M. Califf1961561167961
Eric J. Topol1931373151025
Joan Massagué189408149951
Joseph Biederman1791012117440
Gonçalo R. Abecasis179595230323
James F. Sallis169825144836
Steven N. Blair165879132929
Charles M. Lieber165521132811
J. S. Lange1602083145919
Christopher J. O'Donnell159869126278
Charles M. Perou156573202951
David J. Mooney15669594172
Richard J. Davidson15660291414
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023126
2022591
20215,549
20205,321
20194,806
20184,462