Assessing the Power and Quality of Epidemiologic Studies of Asbestos-Exposed Populations

1985 ◽  
Vol 1 (4) ◽  
pp. 93-110 ◽  
Author(s):  
Devra Lee Davis ◽  
Barbara Mandula ◽  
John Van Ryzin
Keyword(s):  
Statistical Power ◽  
National Research Council ◽  
Epidemiologic Studies ◽  
Risk Assessments ◽  
Royal Commission ◽  
Paper Briefly ◽  
Exposure Data ◽  
Exposed Workers ◽  
Commission Report

This paper briefly discusses criteria for evaluating epidemiologic studies for risk assessment purposes, using asbestos as an example. Asbestos is one of the few carcinogens for which substantial data exist on exposures to humans. However, there are major difficulties in using these data for conducting risk assessments. In particular, exposure data are often incomplete, and risk assessments usually involve extrapolating from the higher exposures of the occupational environments to the lower levels typically encountered in the nonoccupational environment. The term "asbestos" refers to the fibrous form of several minerals, and levels of exposures to these fibers are not easily assessed. Criteria for evaluating epidemiologic studies used in an Ontario Royal Commission report on asbestos are discussed. The importance of considering the statistical power of studies to detect an excess risk is examined using as examples major cohort studies of asbestos-exposed workers, as summarized in a report by the U. S. National Research Council.

A Survey on Internet of Things : Applications and Layered Wise Security Issues

2019 ◽  
pp. 171-180
Author(s):  
Uppuluri Sirisha ◽  
G. Lakshme Eswari
Keyword(s):  
Quality Of Life ◽  
Internet Of Things ◽  
Security And Privacy ◽  
Global Network ◽  
Business Growth ◽  
Paper Briefly ◽  
Smart Meters ◽  
Security Issues ◽  
Data Points

This paper briefly introduces Internet of Things(IOT) as a intellectual connectivity among the physical objects or devices which are gaining massive increase in the fields like efficiency, quality of life and business growth. IOT is a global network which is interconnecting around 46 million smart meters in U.S. alone with 1.1 billion data points per day[1]. The total installation base of IOT connecting devices would increase to 75.44 billion globally by 2025 with a increase in growth in business, productivity, government efficiency, lifestyle, etc., This paper familiarizes the serious concern such as effective security and privacy to ensure exact and accurate confidentiality, integrity, authentication access control among the devices.

scholarly journals Ordinal outcome analysis improves the detection of between-hospital differences in outcome

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
I. E. Ceyisakar ◽  
N. van Leeuwen ◽  
Diederik W. J. Dippel ◽  
Ewout W. Steyerberg ◽  
H. F. Lingsma
Keyword(s):  
Logistic Regression ◽  
Quality Of Care ◽  
Outcome Measures ◽  
Statistical Power ◽  
Ordinal Scale ◽  
Efficiency Gain ◽  
Number Of Patients ◽  
Dichotomous Outcomes ◽  
Ordinal Outcome

Abstract Background There is a growing interest in assessment of the quality of hospital care, based on outcome measures. Many quality of care comparisons rely on binary outcomes, for example mortality rates. Due to low numbers, the observed differences in outcome are partly subject to chance. We aimed to quantify the gain in efficiency by ordinal instead of binary outcome analyses for hospital comparisons. We analyzed patients with traumatic brain injury (TBI) and stroke as examples. Methods We sampled patients from two trials. We simulated ordinal and dichotomous outcomes based on the modified Rankin Scale (stroke) and Glasgow Outcome Scale (TBI) in scenarios with and without true differences between hospitals in outcome. The potential efficiency gain of ordinal outcomes, analyzed with ordinal logistic regression, compared to dichotomous outcomes, analyzed with binary logistic regression was expressed as the possible reduction in sample size while keeping the same statistical power to detect outliers. Results In the IMPACT study (9578 patients in 265 hospitals, mean number of patients per hospital = 36), the analysis of the ordinal scale rather than the dichotomized scale (‘unfavorable outcome’), allowed for up to 32% less patients in the analysis without a loss of power. In the PRACTISE trial (1657 patients in 12 hospitals, mean number of patients per hospital = 138), ordinal analysis allowed for 13% less patients. Compared to mortality, ordinal outcome analyses allowed for up to 37 to 63% less patients. Conclusions Ordinal analyses provide the statistical power of substantially larger studies which have been analyzed with dichotomization of endpoints. We advise to exploit ordinal outcome measures for hospital comparisons, in order to increase efficiency in quality of care measurements. Trial registration We do not report the results of a health care intervention.

scholarly journals Reviewer Acknowledgements for Journal of Plant Studies, Vol. 6, No. 2

2017 ◽  
Vol 6 (2) ◽  
pp. 108
Author(s):  
Joan Lee
Keyword(s):  
National Research Council ◽  
University Of Virginia ◽  
University Of Mississippi ◽  
Application Form ◽  
National Education ◽  
Agricultural Experiment ◽  
University Of Florence ◽  
Academy Of Sciences ◽  
E Mail

Journal of Plant Studies wishes to acknowledge the following individuals for their assistance with peer review of manuscripts for this issue. Their help and contributions in maintaining the quality of the journal are greatly appreciated.Journal of Plant Studies is recruiting reviewers for the journal. If you are interested in becoming a reviewer, we welcome you to join us. Please find the application form and details at http://www.ccsenet.org/reviewer and e-mail the completed application form to [email protected] for Volume 6, Number 2Ahmed Ghannam, University of Strasbourg, FranceAlfredo Benavente, Consejería de Agricultura, Pesca y Medioambiente, SpainAmi Lokhandwala, University of Mississippi, Department of Biology, USABingcheng Xu, Chinese Academy of Sciences and Ministry of Water Resources, ChinaChrystian Iezid Maia e Almeida Feres, Tocantins Federal University, BrazilEstelle Dumont, université Aix-Marseille, FranceHoma Mahmoodzadeh, Department of Biology, Mashhad Branch, Islamic Azad University, Mashhad, IranKhyati Hitesh Shah, Stanford University, United StatesKinga Kostrakiewicz-Gieralt, Institute of Botany, Jagiellonian University, PolandKonstantinos Vlachonasios , Aristotle University of Thessaloniki, School of Biology, GreeceMartina Pollastrini, University of Florence, ItalyMassimo Zacchini, National Research Council of Italy (CNR), ItalyMelekber Sulusoglu, Arslanbey Vocational School Kocaeli University, TurkeyMohamed Trigui, Sfax Preparatory Engineering Institute and CBS, TunisiaRajiv Ranjan, T. P. Varma College, IndiaRajnish Sharma, Dr YS Parmar University of Horticulture & Forestry, Solan (HP), IndiaRakesh Ponnala, Zoetis Inc, United StatesRocío Deanna, Instituto Multidisciplinario de Biología Vegetal, ArgentinaSaid Laarabi, University Mohammed V/Ministry of National Education, MoroccoSlawomir Borek, Adam Mickiewicz University, PolandSuheb Mohammed, University of Virginia, United StatesTomoo misawa, Donan Agricultural Experiment Station, Hokkaido Research Organization, Japan

scholarly journals Quality of life, diagnosis, and treatment of patients with major depression: a prospective cohort study in primary care

2011 ◽  
Vol 33 (3) ◽  
pp. 245-251 ◽  
Author(s):  
Ana Flávia Barros da Silva Lima ◽  
Marcelo Pio de Almeida Fleck
Keyword(s):  
Quality Of Life ◽  
Primary Care ◽  
Cohort Study ◽  
Major Depression ◽  
Antidepressant Treatment ◽  
Epidemiologic Studies ◽  
World Health ◽  
World Health Organization Quality

OBJECTIVE: To describe the demographic and clinical characteristics, adequacy of antidepressant treatment, and changes in quality of life of patients with major depression receiving follow-up care from primary care centers. METHOD: A cohort study was performed in which major depression patients were followed-up over a nine-month period. Several evaluation instruments were used, including the World Health Organization Quality of Life and the Quality of Life-Depression, Centers for Epidemiologic Studies-Depression questionnaires. RESULTS: The sample comprised 179 individuals, mostly female (73%), with a mean age of 38 years and mean education of 9 years. At the end of the follow-up period, 42% of the individuals still presented with major depression, 25% had complete symptom remission, and only 9% were properly treated with antidepressants. In relation to quality of life, there were significant differences especially between baseline and after nine months in almost all measures. CONCLUSION: This study demonstrated that depressive symptoms are poorly recognized and that treatment is often inadequate for patients followed-up in primary care units in the south of Brazil. Most of the patients continued to have symptoms of depression over the nine-month period which were associated with impaired quality of life.

scholarly journals Field verification of a new asphalt compactor, AMIR

1991 ◽  
Vol 18 (3) ◽  
pp. 465-471 ◽  
Author(s):  
Otto J. Svec ◽  
A. O. Abd El Halim
Keyword(s):  
Key Words ◽  
Laboratory Testing ◽  
Research Council ◽  
Joint Venture ◽  
National Research Council ◽  
Field Trials ◽  
Full Scale ◽  
Field Verification ◽  
Asphalt Mix

A prototype of a new asphalt compactor termed "asphalt multi-integrated roller (AMIR)" was built as a joint venture between the National Research Council of Canada (NRC) and a Canadian manufacturer, Lovat Tunnel Equipment, Inc. The purpose of this project was to prove this new compaction concept in a full-scale environment. This paper describes one of the field trials carried out on the campus of the NRC and reports the results quantifying the quality of the AMIR compaction. Key words: compactor, asphalt mix, field trials, laboratory testing.

scholarly journals Enlisting Supervised Machine Learning in Mapping Scientific Uncertainty Expressed in Food Risk Analysis

2017 ◽  
Vol 48 (3) ◽  
pp. 608-641 ◽  
Author(s):  
Akos Rona-Tas ◽  
Antoine Cornuéjols ◽  
Sandrine Blanchemanche ◽  
Antonin Duroy ◽  
Christine Martin
Keyword(s):  
Machine Learning ◽  
Food Safety ◽  
Supervised Machine Learning ◽  
Risk Assessments ◽  
Scientific Uncertainty ◽  
Empirical Measure ◽  
Taxonomic Structure ◽  
Safety Risk ◽  
Food Safety Risk

Recently, both sociology of science and policy research have shown increased interest in scientific uncertainty. To contribute to these debates and create an empirical measure of scientific uncertainty, we inductively devised two systems of classification or ontologies to describe scientific uncertainty in a large corpus of food safety risk assessments with the help of machine learning (ML). We ask three questions: (1) Can we use ML to assist with coding complex documents such as food safety risk assessments on a difficult topic like scientific uncertainty? (2) Can we assess using ML the quality of the ontologies we devised? (3) And, finally, does the quality of our ontologies depend on social factors? We found that ML can do surprisingly well in its simplest form identifying complex meanings, and it does not benefit from adding certain types of complexity to the analysis. Our ML experiments show that in one ontology which is a simple typology, against expectations, semantic opposites attract each other and support the taxonomic structure of the other. And finally, we found some evidence that institutional factors do influence how well our taxonomy of uncertainty performs, but its ability to capture meaning does not vary greatly across the time, institutional context, and cultures we investigated.

The win ratio approach for composite endpoints: practical guidance based on previous experience

2020 ◽  
Vol 41 (46) ◽  
pp. 4391-4399 ◽  
Author(s):  
Björn Redfors ◽  
John Gregson ◽  
Aaron Crowley ◽  
Thomas McAndrew ◽  
Ori Ben-Yehuda ◽  
...  
Keyword(s):  
Statistical Power ◽  
Fatal Outcome ◽  
Composite Endpoint ◽  
Exercise Tests ◽  
Time To Death ◽  
Ratio Approach ◽  
Practical Guidance ◽  
Composite Endpoints ◽  
Available Information

Abstract The win ratio was introduced in 2012 as a new method for examining composite endpoints and has since been widely adopted in cardiovascular (CV) trials. Improving upon conventional methods for analysing composite endpoints, the win ratio accounts for relative priorities of the components and allows the components to be different types of outcomes. For example, the win ratio can combine the time to death with the number of occurrences of a non-fatal outcome such as CV-related hospitalizations (CVHs) in a single hierarchical composite endpoint. The win ratio can provide greater statistical power to detect and quantify a treatment difference by using all available information contained in the component outcomes. The win ratio can also incorporate quantitative outcomes such as exercise tests or quality-of-life scores. There is a need for more practical guidance on how best to design trials using the win ratio approach. This manuscript provides an overview of the principles behind the win ratio and provides insights into how to implement the win ratio in CV trial design and reporting, including how to determine trial size.

scholarly journals Trends in the development of psychiatric services in India

1996 ◽  
Vol 20 (1) ◽  
pp. 43-45 ◽  
Author(s):  
Mohan Isaac
Keyword(s):  
Mentally Ill ◽  
Service Provision ◽  
Mental Hospital ◽  
Quality Of Services ◽  
Paper Briefly ◽  
The Past ◽  
Primary Health ◽  
Primary Health Centres ◽  
Health Centres

Over the past five decades, services for the mentally ill in India have steadily improved. From a predominantly mental hospital based service, provision has now moved to general hospitals and primary health centres. A variety of factors have contributed to changes in the quality of services. This paper briefly reviews the changes and discusses the relevance of some of them.

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