Hybrid Approaches of Verbal Decision Analysis in the Selection of Project Management Approaches

AbstractDecision support methods aim at assisting in the decision-making process by simplifying the analysis of the problem and justifying the choice of a particular potential action. Recent researches have shown that the hybridization of methods is able to overcome limitations presented by the methods when applied separately: the classification of alternatives before submitting them to an ordination methodology would be an e ective way of filtering the set to be ordered. Specific Practices of Capability Maturity Model Integration were analyzed through a decision making model, assisted by the methods SAC and ZAPROS III-i. The results will be compared to previous studies

Towards the Selection of Prototypes for Educational Tools: A Hybrid Model in the Verbal Decision Analysis

Abstract Aiming to attend the growing demand for professionals with knowledge about software processes, this paper presents ideas for creating educational tools that supports its teaching. The paper defines six options of educational tools prototypes and illustrates the research of preferences elicitation in the application of a hybrid method using ORCLASS and PACOM Decision Support Systems (DSS) from Verbal Decision Analysis (VDA) framework to classify and rank the prototypes according to the decision maker preferences. The application with prototypes was chosen because the software engineering is an area that allows a wide research in the preferences elicitation process. The research results show that, the adoption of qualitative methods of decision support can benefit significantly the selection of the interface aiming to use the selected interface from the approved group and ranked for future development of real educational tools applications

OrclassWeb: A Tool Based on the Classification Methodology ORCLASS from Verbal Decision Analysis Framework

The decision making is present in every activity of the human world, either in simple day-by-day problems or in complex situations inside of an organization. Sometimes emotions and reasons become hard to separate; therefore decision support methods were created to help decision makers to make complex decisions, and Decision Support Systems (DSS) were created to aid the application of such methods. The paper presents the development of a new tool, which reproduces the procedure to apply the Verbal Decision Analysis (VDA) methodology ORCLASS. The tool, called OrclassWeb, is software that supports the process of the mentioned DSS method and the paper provides proof of concepts, that which presents its reliability with ORCLASS

Factors Associated with Periodontitis in Patients with and without HIV

Purpose. The aim of this study was to compare clinical periodontal conditions in HIV-positive people on HAART with an HIV-negative group, in addition to investigating factors associated with periodontitis in the entire sample. Methods. This was a cross-sectional study. Data were collected by oral clinical examination for the diagnosis of periodontitis, review of medical records, and application of a questionnaire containing personal data, deleterious habits, and oral hygiene habits for the other variables. The results were analyzed by Pearson’s χ2 test and Student’s t-test. A logistic regression model was constructed for the multivariate analysis and periodontitis was defined as a dependent variable. The analysis was performed on the entire sample (HIV+ and HIV−) and also on the group consisting of only people living with HIV. Results. Individuals older than 43 years old and with HIV were more likely to develop moderate and severe periodontitis (47.80 and 4.84 times, respectively). When analyzing only HIV+, in addition to age (OR = 2.795; CI = 1.080−7.233), the use of nonnucleoside reverse transcriptase inhibitors (NNRTIs) (OR = 2.841; CI = 1.135−7.112) was also associated with moderate and severe periodontitis. Conclusion. It was possible to observe a higher prevalence of periodontitis among individuals with HIV, showing an association between the virus, advanced age, and moderate or severe periodontitis

CLA-supplemented diet accelerates experimental colorectal cancer by inducing TGF-β-producing macrophages and T cells

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Consumption of conjugated linoleic acid (CLA)-supplemented diet during colitis development ameliorates gut inflammation without causing steatosis in mice.

Dietary supplementation with conjugated linoleic acid (CLA) has been proposed for weight management and to prevent gut inflammation. However, some animal studies suggest that supplementation with CLA leads to the development of nonalcoholic fatty liver disease. The aims of this study were to test the efficiency of CLA in preventing dextran sulfate sodium (DSS)-induced colitis, to analyze the effects of CLA in the liver function, and to access putative liver alterations upon CLA supplementation during colitis. So, C57BL/6 mice were supplemented for 3 weeks with either control diet (AIN-G) or 1% CLA-supplemented diet. CLA content in the diet and in the liver of mice fed CLA containing diet were accessed by gas chromatography. On the first day of the third week of dietary treatment, mice received ad libitum a 1.5%?2.5% DSS solution for 7 days. Disease activity index score was evaluated; colon and liver samples were stained by hematoxylin and eosin for histopathology analysis and lamina propria cells were extracted to access the profile of innate cell infiltrate. Metabolic alterations before and after colitis induction were accessed by an open calorimetric circuit. Serum glucose, cholesterol, triglycerides and alanine aminotransaminase were measured; the content of fat in liver and feces was also accessed. CLA prevented weight loss, histopathologic and macroscopic signs of colitis, and inflammatory infiltration. Mice fed CLA-supplemented without colitis induction diet developed steatosis, which was prevented in mice with colitis probably due to the higher lipid consumption as energy during gut inflammation. This result suggests that CLA is safe for use during gut inflammation but not at steady-state conditions

Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients

Abstract Background Acute kidney injury (AKI) is frequently associated with COVID-19, and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalised COVID-19 patients, and to assess the incidence of AKI and KRT requirement. Methods This study is part of a multicentre cohort, the Brazilian COVID-19 Registry. A total of 5212 adult COVID-19 patients were included between March/2020 and September/2020. Variable selection was performed using generalised additive models (GAM), and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. Accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Results The median age of the model-derivation cohort was 59 (IQR 47–70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalisation. The temporal validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in-hospital mortality. The geographic validation cohort had similar age and sex; however, this cohort had higher rates of ICU admission, AKI, need for KRT and in-hospital mortality. Four predictors of the need for KRT were identified using GAM: need for mechanical ventilation, male sex, higher creatinine at hospital presentation and diabetes. The MMCD score had excellent discrimination in derivation (AUROC 0.929, 95% CI 0.918–0.939) and validation (temporal AUROC 0.927, 95% CI 0.911–0.941; geographic AUROC 0.819, 95% CI 0.792–0.845) cohorts and good overall performance (Brier score: 0.057, 0.056 and 0.122, respectively). The score is implemented in a freely available online risk calculator ( https://www.mmcdscore.com/ ). Conclusions The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalised COVID-19 patients who may require more intensive monitoring, and can be useful for resource allocation