If being physically fit is of the outmost importance, then what can be said about the fitness of persons with severe or profound intellectual, visual and motor disabilities? Exactly how could their level of physical fitness be measured? Formulated differently, if a person sees little to nothing and in addition has little comprehension of its immediate environment, then how should one go about testing? How motivated would this person be to be subjected to tests and to perform the tasks as well as possible?' Finding an answer to these questions formed the main incentive for this research. The important concrete results of this research are feasible, reliable, and valid tests for assessing physical fitness of persons with severe or profound intellectual and multiple disabilities, which can be directly implemented into the daily practice.
Decisions are used by organizations to manage and execute their coordinated, value-adding decision-making and are thereby among an organization’s most important assets. To be able to manage deci-sions and underlying business rules, Decision Management (DM) and Business Rules Management (BRM) are increasingly being applied at organisations. One of the latest developments related to the domain of DM and BRM is the introduction of the Decision Model and Notation (DMN) in September 2015 by the Object Management Group (OMG). The goal of this technical paper is to provide students with a case to practice the specification, verification, validation, deployment, execution, monitoring and governance of business rules in practice.
Background: Disease-related malnutrition is a significant problem in hospitalized patients, with high prevalence rates depending on the studied population. Internal Medicine wards are the backbone of the hospital setting. However, prevalence and determinants of malnutrition in these patients remain unclear. We aimed to determine the prevalence of malnutrition in Internal Medicine wards and to identify and characterize malnourished patients. Methods: A cross-sectional observational multicentre study was performed in Internal Medicine wards of 24 Portuguese hospitals during 2017. Demographics, hospital admissions during the previous year, type of admission, primary diagnosis, Charlson comorbidity index, and education level were registered. Malnutrition at admission was assessed using Patient-Generated Subjective Global Assessment (PG-SGA). Demographic characteristics were compared between well-nourished and malnourished patients. Logistic regression analysis was used to identify determinants of malnutrition. Results: 729 participants were included (mean age 74 years, 51% male). Main reason for admission was respiratory disease (32%). Mean Charlson comorbidity index was 5.8 ± 2.8. Prevalence of malnutrition was 73% (56% moderate/suspected malnutrition and 17% severe malnutrition), and 54% had a critical need for multidisciplinary intervention (PG-SGA score ≥9). No education (odds ratio [OR] 1.88, 95% confidence interval [CI]: 1.16–3.04), hospital admissions during previous year (OR 1.53, 95%CI: 1.05–2.26), and multiple comorbidities (OR 1.22, 95%CI: 1.14–1.32) significantly increased the odds of being malnourished. Conclusions: Prevalence of malnutrition in the Internal Medicine population is very high, with the majority of patients having critical need for multidisciplinary intervention. Low education level, admissions during previous year, and multiple comorbidities increase the odds of being malnourished.
