Mapping and Quantification of the Cotton Chain in Brazil

The CHAINPlan method developed by Neves (2007) is a practical tool which can be used to construct strategic plans for production chains. A preliminary step in this process includes mapping and quantifying the production chain. We present the results of applying the method to one of the most important agribusiness chains in Brazil-the cotton sector. The Gross Domestic Product for the cotton sector in the 2010-2011 crop year was estimated at nearly $19.2 billion. We show the interconnections between the links in the chain and its ability to generate revenues, taxes and jobs.

Do established prognostic factors explain the different mortality rates in ICU septic patients around the world?

Background. The aim of this paper was to clarify if previously established prognostic factors explain the different mortality, rates observed in ICU septic patients around the world. Methods. This is a sub-study from the PROGRESS study, which was an international, prospective, observational registry of ICU patients with severe sepsis. For this study we included 10930 patients from 24 countries that enrolled more than 100 patients in the PROGRESS. The effect of potential prognostic factors on in-hospital mortality was examined using univariate and multivariate logistic regression. The complete set of data was available for 7022 patients, who were considered in the multivariate analysis. Countries were classified according to country, income, development status, and in-hospital mortality terciles. The relationship between countries' characteristics and hospital mortality mortality was evaluated using linear regression. Results. Mean in-hospital mortality was 49.2%. Severe sepsis in-hospital mortality varied widely in different countries, ranging from 30.6% in New Zealand to 80.4% in Algeria. Classification as developed or developing country was not associated with in-hospital mortality (P=0.16), nor were levels of gross national product per capita (P=0.15). Patients in the group of countries with higher in-hospital mortality, had a crude OR for in-hospital death of 2.8 (95% CI 2.5-3.1) in comparison to those in the lower risk group. After adjustments were made for all other independent variables, the OR changed to 2.9 (95% CI 2.5-3.3). Conclusion. Severe sepsis mortality varies widely, in different countries. All known markers of disease severity and prognosis do not fully, explain the international differences in mortality,. Country, income does not explain this disparity, either. Further studies should be developed to verify if other organizational or structural factors account for disparities in patient care and outcomes. (Minerva Anestesiol 2012;78:1215-25)