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Objective
We aimed to investigate the proportion of young patients not returning to work (NRTW) at 1 year after ischemic stroke (IS) and during follow-up, and clinical factors associated with NRTW.
Methods
Patients from the Helsinki Young Stroke Registry with an IS occurring in the years 1994–2007, who were at paid employment within 1 year before IS, and with NIH Stroke Scale score ≤15 points at hospital discharge, were included. Data on periods of payment came from the Finnish Centre for Pensions, and death data from Statistics Finland. Multivariate logistic regression analyses assessed factors associated with NRTW 1 year after IS, and lasagna plots visualized the proportion of patients returning to work over time.
Results
We included a total of 769 patients, of whom 289 (37.6%) were not working at 1 year, 323 (42.0%) at 2 years, and 361 (46.9%) at 5 years from IS. When adjusted for age, sex, socioeconomic status, and NIH Stroke Scale score at admission, factors associated with NRTW at 1 year after IS were large anterior strokes, strokes caused by large artery atherosclerosis, high-risk sources of cardioembolism, and rare causes other than dissection compared with undetermined cause, moderate to severe aphasia vs no aphasia, mild and moderate to severe limb paresis vs no paresis, and moderate to severe visual field deficit vs no deficit.
Conclusions
NRTW is a frequent adverse outcome after IS in young adults with mild to moderate IS. Clinical variables available during acute hospitalization may allow prediction of NRTW.
Integrating distributional and lexical information for semantic classification of words using MRMF
(2016)
Semantic classification of words using distributional features is usually based on the semantic similarity of words. We show on two different datasets that a trained classifier using the distributional features directly gives better results. We use Support Vector Machines (SVM) and Multirelational Matrix Factorization (MRMF) to train classifiers. Both give similar results. However, MRMF, that was not used for semantic classification with distributional features before, can easily be extended with more matrices containing more information from different sources on the same problem. We demonstrate the effectiveness of the novel approach by including information from WordNet. Thus we show, that MRMF provides an interesting approach for building semantic classifiers that (1) gives better results than unsupervised approaches based on vector similarity, (2) gives similar results as other supervised methods and (3) can naturally be extended with other sources of information in order to improve the results.
The CogALex-V Shared Task provides two datasets that consists of pairs of words along with a classification of their semantic relation. The dataset for the first task distinguishes only between related and unrelated, while the second data set distinguishes several types of semantic relations. A number of recent papers propose to construct a feature vector that represents a pair of words by applying a pairwise simple operation to all elements of the feature vector. Subsequently, the pairs can be classified by training any classification algorithm on these vectors. In the present paper we apply this method to the provided datasets. We see that the results are not better than from the given simple baseline. We conclude that the results of the investigated method are strongly depended on the type of data to which it is applied.
In distributional semantics words are represented by aggregated context features. The similarity of words can be computed by comparing their feature vectors. Thus, we can predict whether two words are synonymous or similar with respect to some other semantic relation. We will show on six different datasets of pairs of similar and non-similar words that a supervised learning algorithm on feature vectors representing pairs of words outperforms cosine similarity between vectors representing single words. We compared different methods to construct a feature vector representing a pair of words. We show that simple methods like pairwise addition or multiplication give better results than a recently proposed method that combines different types of features. The semantic relation we consider is relatedness of terms in thesauri for intellectual document classification. Thus our findings can directly be applied for the maintenance and extension of such thesauri. To the best of our knowledge this relation was not considered before in the field of distributional semantics.
For indexing archived documents the Dutch Parliament uses a specialized thesaurus. For good results for full text retrieval and automatic classification it turns out to be important to add more synonyms to the existing thesaurus terms. In the present work we investigate the possibilities to find synonyms for terms of the parliaments thesaurus automatically. We propose to use distributional similarity (DS). In an experiment with pairs of synonyms and non-synonyms we train and test a classifier using distributional similarity and string similarity. Using ten-fold cross validation we were able to classify 75% of the pairs of a set of 6000 word pairs correctly.
Background: After kidney transplantation, immunosuppressive therapy causes impaired cellular immune defense leading to an increased risk of viral complications. Trough level monitoring of immunosuppressants is insufficient to estimate the individual intensity of immunosuppression. We have already shown that virus-specific T cells (Tvis) correlate with control of virus replication as well as with the intensity of immunosuppression. The multicentre IVIST01-trial should prove that additional steering of immunosuppressive and antiviral therapy by Tvis levels leads to better graft function by avoidance of over-immunosuppression (for example, viral infections) and drug toxicity (for example, nephrotoxicity).
Methods/design: The IVIST-trial starts 4 weeks after transplantation. Sixty-four pediatric kidney recipients are randomized either to a non-intervention group that is only treated conservatively or to an intervention group with additional monitoring by Tvis. The randomization is stratified by centre and cytomegalovirus (CMV) prophylaxis. In both groups the immunosuppressive medication (cyclosporine A and everolimus) is adopted in the same target range of trough levels. In the non-intervention group the immunosuppressive therapy (cyclosporine A and everolimus) is only steered by classical trough level monitoring and the antiviral therapy of a CMV infection is performed according to a standard protocol. In contrast, in the intervention group the dose of immunosuppressants is individually adopted according to Tvis levels as a direct measure of the intensity of immunosuppression in addition to classical trough level monitoring. In case of CMV infection or reactivation the antiviral management is based on the individual CMV-specific immune defense assessed by the CMV-Tvis level. Primary endpoint of the study is the glomerular filtration rate 2 years after transplantation; secondary endpoints are the number and severity of viral infections and the incidence of side effects of immunosuppressive and antiviral drugs.
Discussion: This IVIST01-trial will answer the question whether the new concept of steering immunosuppressive and antiviral therapy by Tvis levels leads to better future graft function. In terms of an effect-related drug monitoring, the study design aims to realize a personalization of immunosuppressive and antiviral management after transplantation. Based on the IVIST01-trial, immunomonitoring by Tvis might be incorporated into routine care after kidney transplantation.
Introduction:
Human Immunodeficiency Virus (HIV) infection remains prevalent co-morbidity, and among fracture patients. Few studies have investigated the role of exercise interventions in preventing bone demineralization in people who have fractures and HIV. If exercise exposed, HIV-infected individuals may experience improved bone health outcomes (BMD), function, quality of life (QoL). The study will aim to assess the impact of home based exercises on bone mineral density, functional capacity, QoL, and some serological markers of health in HIV infection among Nigerians and South Africans.
Methods and design:
The study is an assessor-blinded randomized controlled trial. Patients managed with internal and external fixation for femoral shaft fracture at the study sites will be recruited to participate in the study. The participants will be recruited 2 weeks post-discharge at the follow-up clinic with the orthopaedic surgeon. The study population will consist of all persons with femoral fracture and HIV-positive and negative (HIV-positive medically confirmed) aged 18 to 60 years attending the above-named health facilities. For the HIV-positive participants, a documented positive HIV result, as well as a history of being followed-up at the HIV treatment and care center. A developed home based exercise programme will be implemented in the experimental group while the control group continues with the usual rehabilitation programme. The primary outcome measures will be function, gait, bone mineral density, physical activity, and QoL.
Discussion:
The proposed trial will compare the effect of a home-based physical exercise-training programme in the management of femoral fracture to the usual physiotherapy management programmes with specific outcomes of bone mineral density, function, and inflammatory markers.
Background: Health information systems (HIS) are one of the most important areas for biomedical and health informatics. In order to professionally deal with HIS well-educated informaticians are needed. Because of these reasons, in 2001 an international course has been established: The Frank – van Swieten Lectures on Strategic Information Management of Health Information Systems.
Objectives: Reporting about the Frank – van Swieten Lectures and about our students‘ feedback on this course during the last 16 years. Summarizing our lessons learned and making recommendations for such international courses on HIS.
Methods: The basic concept of the Frank – van Swieten lectures is to teach the theoretical background in local lectures, to organize practical exercises on modelling sub-information systems of the respective local HIS and finally to conduct Joint Three Days as an international meeting were the resulting models are introduced and compared.
Results: During the last 16 years, the Universities of Amsterdam, Braunschweig, Heidelberg/Heilbronn, Leipzig as well as UMIT were involved in running this course. Overall, 517 students from these universities participated. Our students‘ feedback was clearly positive.
The Joint Three Days of the Frank – van Swieten Lectures, where at the end of the course all students can meet, turned out to be an important component of this course. Based on the last 16 years, we recommend common teaching materials, agreement on equivalent clinical areas for the exercises, support of group building of international student groups, motivation of using a collaboration platform, ensuring quality management of the course, addressing different levels of knowledge of the students, and ensuring sufficient funding for joint activities.
Conclusions: Although associated with considerable additional efforts, we can clearly recommend establishing such international courses on HIS, such as the Frank – van Swieten Lectures.
Die Reproduzierbarkeit von Studien ist wichtig, um ihre Ergebnisse prüfen zu können. Auch bei Forschung, die auf frühere Ergebnisse aufbaut, wird zuweilen ein Zugang zu den alten Daten oder dem Source Code benötigt. Diese Arbeit analysiert Studien aus der Computerlinguistik hinsichtlich ihrer Reproduzierbarkeit. Zunächst werden die Begrifflichkeiten zu diesem speziellen Gebiet definiert und im folgenden Schritt wird ein Datensatz erstellt, in dem ausgewählte Open-Access-Studien aus dem Jahre 2018 auf der Basis zuvor festgelegter Kriterien bewertet werden. Diese sind unter anderem die Zugänglichkeit des benutzten Materials, der angewendeten Methoden und der Ergebnisse. Neben den Kriterien werden auch Hypothesen zu diesem Datensatz aufgestellt. Schließlich werden die Ergebnisse visualisiert und hinsichtlich besagter Hypothesen interpretiert. Basierend auf der resultierenden Auswertung sind die meisten Studien reproduzierbar. Im Ausblick werden mögliche Weiterführungen und Erweiterungen dieser Untersuchung erläutert.
Die vorliegende Diplomarbeit beschäftigt sich mit dem Qualitätsmanagementverfahren der Arbeitsgemeinschaft der Kunst- und Museumsbibliotheken (AKMB). Dargestellt werden Hintergrund, Entwicklung und Praxis des Qualitätsmanagementverfahrens. Im Fokus stehen dabei die 83 Standards der AKMB. Die Arbeit verfolgt einen sehr praxisorientierten Ansatz, beleuchtet die Standards aus mehreren Perspektiven und liefert zahlreiche Empfehlungen, Erläuterungen, Checklisten und Hintergrundinformationen. Wer sich mit Qualitätsmanagement in Bibliotheken beschäftigen, auf ein Audit vorbereiten oder einen Einblick in die Entwicklung eines QM-Verfahrens erhalten möchte, findet in der vorliegenden Arbeit entsprechende Informationen.