Children with severe malnutrition: can those at highest risk of death be identified with the WHO protocol?

Background With strict adherence to international recommended treatment guidelines, the case fatality for severe malnutrition ought to be less than 5%. In African hospitals, fatality rates of 20% are common and are often attributed to poor training and faulty case management. Improving outcome will depend upon the identification of those at greatest risk and targeting limited health resources. We retrospectively examined the major risk factors associated with early (<48 h) and late in-hospital death in children with severe malnutrition with the aim of identifying admission features that could distinguish a high-risk group in relation to the World Health Organization (WHO) guidelines. Methods and Findings Of 920 children in the study, 176 (19%) died, with 59 (33%) deaths occurring within 48 h of admission. Bacteraemia complicated 27% of all deaths: 52% died before 48 h despite 85% in vitro antibiotic susceptibility of cultured organisms. The sensitivity, specificity, and likelihood ratio of the WHO-recommended “danger signs” (lethargy, hypothermia, or hypoglycaemia) to predict early mortality was 52%, 84%, and 3.4% (95% confidence interval [CI] = 2.2 to 5.1), respectively. In addition, four bedside features were associated with early case fatality: bradycardia, capillary refill time greater than 2 s, weak pulse volume, and impaired consciousness level; the presence of two or more features was associated with an odds ratio of 9.6 (95% CI = 4.8 to 19) for early fatality (p < 0.0001). Conversely, the group of children without any of these seven features, or signs of dehydration, severe acidosis, or electrolyte derangements, had a low fatality (7%). Conclusions Formal assessment of these features as emergency signs to improve triage and to rationalize manpower resources toward the high-risk groups is required. In addition, basic clinical research is necessary to identify and test appropriate supportive treatments

Motivation for Technology Adoption and Its Impact on Abandonment: A Case Study of U.S. Cotton Farmers

We estimate a bivariate probit model with sample selection to identify factors affecting adoption and abandonment of precision farming technologies for cotton farmers, using the 2009 Southern Cotton Precision Farming Survey conducted in 12 Southern states in the United States. Farmers for whom being at the forefront of agricultural technology is not an important reason for adoption are more likely to abandon precision farming technologies. This study identified various factors associated with adoption and retention of precision farming technologies. Findings from this study offer significant information to policy‐makers for a better formulation of agri‐environmental programs that encourage farmers to adopt environmentally benign farming practices including precision farming technologies.Technology Abandonment, Technology Adoption, Bivariate Probit with Sample Selection, Multinomial Logit, Precision Farming, Agribusiness, Crop Production/Industries, Farm Management, Production Economics, Research and Development/Tech Change/Emerging Technologies, Q10, Q12, Q16,

Clinical Research Informatics

This seminar describes programs and resources available through the Biomedical Informatics component of the UMCCTS

A LOGIT ANALYSIS OF PARTICIPATION IN TENNESSEE'S FOREST STEWARDSHIP PROGRAM

This study determines the likely effect of cost-share incentives on participation in the Tennessee Forest Stewardship Program and identifies other factors that may contribute to participation. A random utility model is used to determine the probability that a landowner will choose to participate in the program. A binary choice model is specified to represent the dichotomous decision and a logit procedure is used to fit the model. Data are obtained from mail surveys of 4,000 randomly selected landowners. Results indicate that attitudes and knowledge of forestry programs may be more influential in a landowner's decision to participate than monetary incentives.Cost-share incentive, Stewardship Incentive Program, Logit, Nonindustrial private forest, NIPF, Participation, Forestry, Trees, Resource /Energy Economics and Policy,

Forecast of Future Aviation Fuels. Part 1: Scenarios

A preliminary set of scenarios is described for depicting the air transport industry as it grows and changes, up to the year 2025. This provides the background for predicting the needs for future aviation fuels to meet the requirements of the industry as new basic sources, such as oil shale and coal, which are utilized to supplement petroleum. Five scenarios are written to encompass a range of futures from a serious resource-constrained economy to a continuous and optimistic economic growth. A unique feature is the choice of one immediate range scenario which is based on a serious interruption of economic growth occasioned by an energy shortfall. This is presumed to occur due to lags in starting a synfuels program

Factors Influencing Cotton Farmers’ Perceptions about the Importance of Information Sources in Precision Farming Decisions

Information generated by precision farming technologies is of particular importance to producers. Precision farming technologies implies the ability to improve the management of production factors using site-specific information. This study examines factors influencing cotton farmers’ perceptions about the importance of crop consultants, farm input dealerships, Extension, other farmers, trade shows, the Internet and printed news/media for making precision farming decisions using a rank ordered logit model (ROLM). Results suggest that age, land tenure, income, percentage of income from farming, and location may affect farmers’ perceptions about the importance of different information sources when making decisions about precision farming technologies. Results suggest that regardless of farmer/farm business characteristics other farmers (OF) is one of the most important information sources when making precision farming decisions. Findings suggest that high income producers are more likely to prefer crop consultants, University/Extension, trade shows, and the Internet over OF as a source of information when making decisions about precision farming technologies. Findings also suggest that researchers need to be very careful when designing questions that ask respondents to rank alternatives so that they guarantee that individuals with different skills are able to precisely understand what is being asked. Decreasing the number of alternatives respondents must consider may be one strategy to reduce the complexity of ranking questions to minimize the probability of the respondents leaving alternatives unranked or ranking them randomly.Information-source preferences, Rank Ordered Logit Model, Precision Farming, Production Economics, Research Methods/ Statistical Methods, Q16, C25,

Polarization dependent photoionization cross-sections and radiative lifetimes of atomic states in Ba

The photoionization cross-sections of two even-parity excited states, $5d6d ^3D_1$ and $6s7d ^3D_{2}$, of atomic Ba at the ionization-laser wavelength of 556.6 nm were measured. We found that the total cross-section depends on the relative polarization of the atoms and the ionization-laser light. With density-matrix algebra, we show that, in general, there are at most three parameters in the photoionization cross-section. Some of these parameters are determined in this work. We also present the measurement of the radiative lifetime of five even-parity excited states of barium.Comment: 11 pages, 7 figure

Factors Influencing the Selection of Precision Farming Information Sources by Cotton Producers

Precision farming information demanded by cotton producers is provided by various suppliers, including consultants, farm input dealerships, University Extension systems, and media sources. Factors associated with the decisions to select among information sources to search for precision farming information are analyzed using a multivariate probit regression accounting for correlation among the different selection decisions. Factors influencing these decisions are age, education, and income. These findings should be valuable to precision farming information providers who may be able to better meet their target clientele needs.Extension, information-source-use decisions, media, multivariate probit, precision agriculture technologies, private sources, Farm Management, Teaching/Communication/Extension/Profession,

Factors Influencing Selection of Information Sources by Cotton Producers Considering Adoption of Precision Agriculture Technologies

Acknowledgements: The authors thank Cotton Incorporated and the Tennessee Agricultural Experiment Station for financial supportInformation source use decisions, Precision Agriculture Technologies, Extension, Media, Private sources, Multivariate Probit, Teaching/Communication/Extension/Profession, Q12, Q16,

Changes in Producers’ Perceptions of Within-field Yield Variability Following Adoption of Cotton Yield Monitors

Precision Farming, Risk, Yield Monitor, Yield Variability, Yield Perceptions, Spatial Yield Distributions, Within Field Variability, Farm Management, Production Economics, Risk and Uncertainty, Q12, Q16,