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Apeldoorn, Netherlands

Di Giacomo E.,University of Perugia | Didimo W.,University of Perugia | Liotta G.,University of Perugia | Meijer H.,Roosevelt Academy
Theory of Computing Systems | Year: 2011

In this paper we study non-planar drawings of graphs, and study trade-offs between the crossing resolution (i. e., the minimum angle formed by two crossing segments), the curve complexity (i. e., maximum number of bends per edge), the total number of bends, and the area. © 2010 Springer Science+Business Media, LLC. Source


Spoorenberg S.M.C.,St. Antonius Hospital | Bos W.J.W.,St. Antonius Hospital | Heijligenberg R.,Gelderse Vallei Hospital | Voorn P.G.P.,St. Antonius Hospital | And 5 more authors.
BMC Infectious Diseases | Year: 2014

Background: The aim of this study was to investigate the clinical outcome and especially costs of hospitalisation for community-acquired pneumonia (CAP) in relation to microbial aetiology. This knowledge is indispensable to estimate cost-effectiveness of new strategies aiming to prevent and/or improve clinical outcome of CAP.Methods: We performed our observational analysis in a cohort of 505 patients hospitalised with confirmed CAP between 2004 and 2010. Hospital administrative databases were extracted for all resource utilisation on a patient level. Resource items were grouped in seven categories: general ward nursing, nursing on ICU, clinical chemistry laboratory tests, microbiology exams, radiology exams, medication drugs, and other.linear regression analyses were conducted to identify variables predicting costs of hospitalisation for CAP.Results: Streptococcus pneumoniae was the most identified causative pathogen (25%), followed by Coxiella burnetii (6%) and Haemophilus influenzae (5%). Overall median length of hospital stay was 8.5 days, in-hospital mortality rate was 4.8%.Total median hospital costs per patient were €3,899 (IQR 2,911-5,684). General ward nursing costs represented the largest share (57%), followed by nursing on the intensive care unit (16%) and diagnostic microbiological tests (9%). In multivariate regression analysis, class IV-V Pneumonia Severity Index (indicative for severe disease), Staphylococcus aureus, or Streptococcus pneumonia as causative pathogen, were independent cost driving factors. Coxiella burnetii was a cost-limiting factor.Conclusions: Median costs of hospitalisation for CAP are almost €4,000 per patient. Nursing costs are the main cause of these costs. Apart from prevention, low-cost interventions aimed at reducing length of hospital stay therefore will most likely be cost-effective. © 2014 Spoorenberg et al.; licensee BioMed Central Ltd. Source


Klaassen E.M.M.,Maastricht University | Van De Kant K.D.G.,Maastricht University | Jobsis Q.,Maastricht University | Van Schayck O.C.P.,Maastricht University | And 9 more authors.
American Journal of Respiratory and Critical Care Medicine | Year: 2015

Rationale: A reliable asthma diagnosis is difficult in wheezing preschool children. Objectives: To assess whether exhaled biomarkers, expression of in flammation genes, and early lung function measurements can improve a reliable asthma prediction in preschool wheezing children. Methods: Two hundred two preschool recurrent wheezers (aged 2-4 yr) were prospectively followed up until 6 years of age. At 6 years of age, a diagnosis (asthma or transient wheeze) was based on symptoms, lung function, and asthma medication use. The added predictive value (area under the receiver operating characteristic curve [AUC]) of biomarkers to clinical information (assessed with the Asthma Predictive Index [API]) assessed at preschool age in diagnosing asthma at 6 years of age was determined with a validation set. Biomarkers in exhaled breath condensate, exhaled volatile organic compounds (VOCs), gene expression, and airway resistance were measured. Measurements and Main Results: At 6 years of age, 198 children were diagnosed (76 with asthma, 122 with transient wheeze). Information on exhaled VOCs significantly improved asthma prediction (AUC, 89% [increase of 28%]; positive predictive value [PPV]/negative predictive value [NPV], 82/83%), which persisted in the validation set. Information on gene expression of toll-like receptor 4, catalase, and tumor necrosis factor-α significantly improved asthma prediction (AUC, 75% [increase of 17%]; PPV/NPV, 76/73%). This could not be confirmed after validation. Biomarkers in exhaled breath condensate and airway resistance (pre- and post- bronchodilator) did not improve an asthma prediction. The combined model with VOCs, gene expression, and API had an AUC of 95% (PPV/NPV, 90/89%). Conclusions: Adding information on exhaled VOCs and possibly expression of inflammation genes to the API significantly improves an accurate asthma diagnosis in preschool children. Clinical trial registered with www.clinicaltrial.gov (NCT 00422747). Copyright © 2015 by the American Thoracic Society. Source


Rijkers G.T.,St. Antonius Hospital Nieuwegein | Rijkers G.T.,Roosevelt Academy
Critical Care | Year: 2011

Probiotics are live micro-organisms with a health promoting effect. Because of their immunomodulating capacity as well as improvement of gut barrier function, probiotics have the capacity to prevent infectious complications in a variety of clinical settings. Now selected probiotics show potential for improving the clinical outcome of severe trauma patients. © 2011 BioMed Central Ltd. Source


Rahut D.B.,South Asian University | Micevska Scharf M.,Leiden University | Micevska Scharf M.,Roosevelt Academy
Australian Journal of Agricultural and Resource Economics | Year: 2012

This article examines livelihood diversification strategies of rural households using survey data from the Himalayas. We present and explore an analytical framework that yields different activity choices as optimal solutions to a simple utility maximization problem. By classifying the range of activities of rural households into a few distinct categories based on their profitability and by considering portfolios of farm and non-farm activities, we provide novel insights into diversification behaviour of rural households. The evidence shows that while the poor are mainly agricultural labourers and work in the low-return non-farm sector, the better-off diversify in high-return non-farm activities. As expected, we find strong evidence that education plays a major role in accessing more remunerative non-farm employment. A somewhat less intuitive finding is that larger household size is associated with higher probability of diversification into the high-return non-farm sector. The finding that the farm size is not a constraint to diversification in lucrative non-farm employment is also surprising. Geographical location plays a role in diversification behaviour of rural households indicating the importance of local context. © 2012 The Authors. AJARE © 2012 Australian Agricultural and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd. Source

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