Danube University Krems

About: Danube University Krems is a education organization based out in Krems, Niederösterreich, Austria. It is known for research contribution in the topics: Stroke & Population. The organization has 498 authors who have published 1572 publications receiving 68797 citations.

Bridging an asbru protocol to an existing electronic patient record

Abstract: Clinical protocols can improve the quality of care if implemented in Decision Support Systems (DSS) that are used in clinical practice. For optimal user acceptance, they must use data from the existing Electronic Patient Records (EPR) and enforce only small changes in the care process and minimal extra effort for data entry. In this paper we describe how we handle the challenge of mapping a breast cancer treatment protocol encoded in Asbru to a legacy EPR which has been used by oncologists at the point of care for years. We identified different levels of integration effort ranging from readily available data in the EPR to abstractions which can only be performed by domain experts. By involving the author of the protocol in the implementation process, we were able to design a system which promises to improve the daily routine at the places of application.

Building a Reference Model and an Evaluation Method for cities of the Brazilian Network of Smart and Human Cities

Abstract: Smart Cities theme has evolved in the last years, leading the cities to implement initiatives related to technical aspects to improve quality of life. Another focus on this theme is how to measure the added value of these initiatives to the population. The Brazilian Network of Smart and Human Cities (RBCIH) was created in order to join both approaches in Brazil, putting together members from academy, private initiative and local (municipality) government. Nowadays, RBCIH is composed by 350 Brazilian cities (in a universe of 5570 cities), indicating that a long-term work has to be executed by RBCIH in Brazil. Two purposes of RBCIH are presenting good practices and evaluating how smart and human a city is. In this work, a methodology is presented for constructing a Brazilian reference model and an evaluation method for smart cities, adherent to the Brazilian reality.

Three-dimensional analyses of the mandible and the occlusal architecture of mandibular dentition

Abstract: Introduction The position and inclination of the long axis of teeth in the human dentition can be described by a set of rules. The purpose of this study was to analyze the architecture of the mandibular dentition of adult Caucasians using virtual three-dimensional (3D) reconstruction of skulls and mandibles.

SAMURAI: Sensitivity analysis of a meta-analysis with unpublished but registered analytical investigations (software)

Abstract: The non-availability of clinical trial results contributes to publication bias, diminishing the validity of systematic reviews and meta-analyses. Although clinical trial registries have been established to reduce non-publication, the results from over half of all trials registered in ClinicalTrials.gov remain unpublished even 30 months after completion. Our goals were i) to utilize information available in registries (specifically, the number and sample sizes of registered unpublished studies) to gauge the sensitivity of a meta-analysis estimate of the effect size and its confidence interval to the non-publication of studies and ii) to develop user-friendly open-source software to perform this quantitative sensitivity analysis. The open-source software, the R package SAMURAI, was developed using R functions available in the R package metafor. The utility of SAMURAI is illustrated with two worked examples. Our open-source software SAMURAI, can handle meta-analytic datasets of clinical trials with two independent treatment arms. Both binary and continuous outcomes are supported. For each unpublished study, the dataset requires only the sample sizes of each treatment arm and the user predicted ‘outlook’ for the studies. The user can specify five outlooks ranging from ‘very positive’ (i.e., very favorable towards intervention) to ‘very negative’ (i.e., very favorable towards control). SAMURAI assumes that control arms of unpublished studies have effects similar to the effect across control arms of published studies. For each experimental arm of an unpublished study, utilizing the user-provided outlook, SAMURAI randomly generates an effect estimate using a probability distribution, which may be based on a summary effect across published trials. SAMURAI then calculates the estimated summary treatment effect with a random effects model (DerSimonian & Laird method), and outputs the result as a forest plot. To our knowledge, SAMURAI is currently the only tool that allows systematic reviewers to incorporate information about sample sizes of treatment groups in registered but unpublished clinical trials in their assessment of the potential impact of publication bias on meta-analyses. SAMURAI produces forest plots for visualizing how inclusion of registered unpublished studies might change the results of a meta-analysis. We hope systematic reviewers will find SAMURAI to be a useful addition to their toolkit.