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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: Autism Spectrum Disorder (ASD) is characterized by impairments in social communication, limited repetitive behaviors, impaired language development, and interest or activity patterns, which include a group complex neurodevelopmental syndrome with diverse phenotypes that reveal considerable etiological and clinical heterogeneity and are also considered one of the most heritable disorders (over 90%). Genetic, epigenetic, and environmental factors play a role in the development of ASD.
Aim: This study was designed to investigate the extent of DNA damage in parents of autistic children by treating peripheral blood mononuclear cells (PBMCs) with bleomycin and hydrogen peroxide (H2O2).
Methods: Peripheral blood mononuclear cells (PBMCs) were isolated by the Ficoll method and treated with a specific concentration of bleomycin and H2O2 for 30 min and 5 min, respectively. Then, the degree of DNA damage was analyzed by the alkaline comet assay or single cell gel electrophoresis (SCGE), an effective way to measure DNA fragmentation in eukaryotic cells.
Results: Our findings revealed that there is a significant difference in the increase of DNA damage in parents with affected children compared to the control group, which can indicate the inability of the DNA molecule repair system. Furthermore, our study showed a significant association between fathers’ occupational difficulties (exposed to the influence of environmental factors), as well as family marriage, and suffering from ASD in offspring.
Conclusion: Our results suggested that the influence of environmental factors on parents of autistic children may affect the development of autistic disorder in their offspring. Subsequently, based on our results, investigating the effect of environmental factors on the amount of DNA damage in parents with affected children requires more studies.
Digital data on tangible and intangible cultural assets is an essential part of daily life, communication and experience. It has a lasting influence on the perception of cultural identity as well as on the interactions between research, the cultural economy and society. Throughout the last three decades, many cultural heritage institutions have contributed a wealth of digital representations of cultural assets (2D digital reproductions of paintings, sheet music, 3D digital models of sculptures, monuments, rooms, buildings), audio-visual data (music, film, stage performances), and procedural research data such as encoding and annotation formats. The long-term preservation and FAIR availability of research data from the cultural heritage domain is fundamentally important, not only for future academic success in the humanities but also for the cultural identity of individuals and society as a whole. Up to now, no coordinated effort for professional research data management on a national level exists in Germany. NFDI4Culture aims to fill this gap and create a usercentered, research-driven infrastructure that will cover a broad range of research domains from musicology, art history and architecture to performance, theatre, film, and media studies.
The research landscape addressed by the consortium is characterized by strong institutional differentiation. Research units in the consortium's community of interest comprise university institutes, art colleges, academies, galleries, libraries, archives and museums. This diverse landscape is also characterized by an abundance of research objects, methodologies and a great potential for data-driven research. In a unique effort carried out by the applicant and co-applicants of this proposal and ten academic societies, this community is interconnected for the first time through a federated approach that is ideally suited to the needs of the participating researchers. To promote collaboration within the NFDI, to share knowledge and technology and to provide extensive support for its users have been the guiding principles of the consortium from the beginning and will be at the heart of all workflows and decision-making processes. Thanks to these principles, NFDI4Culture has gathered strong support ranging from individual researchers to highlevel cultural heritage organizations such as the UNESCO, the International Council of Museums, the Open Knowledge Foundation and Wikimedia. On this basis, NFDI4Culture will take innovative measures that promote a cultural change towards a more reflective and sustainable handling of research data and at the same time boost qualification and professionalization in data-driven research in the domain of cultural heritage. This will create a long-lasting impact on science, cultural economy and society as a whole.
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.
FID Civil Engineering, Architecture and Urbanism digital - A platform for science (BAUdigital)
(2022)
University Library Braunschweig (UB Braunschweig), University and State Library Darmstadt (ULB Darmstadt), TIB – Leibniz Information Centre for Technology and Natural Sciences and the Fraunhofer Information Centre for Planning and Building (Fraunhofer IRB) are jointly establishing a specialised information service (FID, "Fachinformationsdienst") for the disciplines of civil engineering, architecture and urbanism. The FID BAUdigital, which is funded by the German Research Foundation (DFG, "Deutsche Forschungsgemeinschaft"), will provide researchers working on digital design, planning and production methods in construction engineering with a joint information, networking and data exchange platform and support them with innovative services for documentation, archiving and publication in their data-based research.
All of us are aware of the changes in the information field during the last years. We all see the paradigm shift coming up and have some idea how it will challenge our profession in the future. But how the road to excellence - in education of information specialists in the future - will look like? There are different models (new and old ones) for reorganising the structure of education: * Integration * Specialisation * Step-by step-model * Modul System * Network System / Combination model The paper will present the actual level of discussion on building up a new curriculum at the Department of Information and Communication (IK) at the FH Hannover. Based on the mission statement of the department »Education of information professionals is a part of the dynamic evolution of knowledge society« the direction of change and the main goals will be presented. The different reorganisation models will be explained with its objectives, opportunities and forms of implementation. Some examples will show the ideas and tools for a first draft of a reconstruction plan to become fit for the future. This talk has been held at the German-Dutch University Conference »Information Specialists for the 21st Century« at the Fachhochschule Hannover - University of Applied Sciences, Department of Information and Communication, October 14 -15, 1999 in Hannover, Germany.
The aim of the podcast Digitization of Medicine is to interest a broader audience and, in particular, young women, in research and work in the field of medical informatics. This article presents the usage figures and discusses their significance for further research on the success of science communication. By 24/02/2022, a total of 24,351 downloads had been made. There were slightly more female than male listeners, and they tended to be younger. Despite the importance podcast are gaining for science communication, little is known about the respective user group and further research is needed. In this context, this paper aims to help make the effectiveness of podcasts comparable.
Research question: Rivalries in team sports are commonly conceptualized as a threat to the fans’ identity. Therefore, past research has mainly focused on the negative consequences. However, theoretical arguments and empirical evidence suggest that rivalry has both negative and positive effects on fans’ self-concept. This research develops and empirically tests a model which captures and integrates these dual effects of rivalry.
Research methods: Data were collected via an on-site survey at home games of eight German Bundesliga football teams (N = 571). Structural equation modeling provides strong support for the proposed model.
Results and findings: In line with previous research, the results show that rivalry threatens fans’ identity as reflected in lower public collective self-esteem in relation to supporters of the rival team. However, the results also show that there are crucial positive consequences, such as higher perceptions of public collective self-esteem in relation to supporters of non-rival opponents, perceived ingroup distinctiveness and ingroup cohesion. These positive effects are mediated through increases in disidentification with the rival and perceived reciprocity of rivalry.
Implications: We contribute to the literature by providing a more balanced view of one of team sports’ key phenomena. Our results indicate that the prevalent conceptualization of rivalry as an identity threat should be amended by the positive consequences. Our research also offers guidance for the promotion of rivalries, where the managerial focus should be on creating a perception that a rivalry is reciprocal.
Research question: In order to reduce fan aggression surrounding rivalry games, team sport organizations often try to placate fans by downplaying the importance of the game (e.g. ‘the derby is not a war’). Drawing on the intergroup conflict literature, this research derives dual identity statements and examines their effectiveness in reducing fan aggressiveness compared to the managerial practice of downplaying rivalry.
Research methods: Three field experimental studies (one face-to-face survey and two online surveys) tested the hypotheses. Established rivalries in the German soccer league Bundesliga served as the empirical setting of the studies. The data were analyzed using ANCOVA and linear regression analyses.
Results and findings: Dual identity statements reduce fan aggressiveness compared to both downplay statements and a no-statement control condition, independent of team identification and trait aggression. Importantly, the managerial practice of downplaying rivalry appears to be counterproductive. It produces even higher levels of fan aggressiveness than making no statement, an effect caused by psychological reactance.
Implications: Sport organizations should not alienate their fan base by attempting to play down the importance of rivalry, which is an integral part of fan identity. Instead, they should strengthen the supporters’ unique identity (as fans of a particular team) while at the same time facilitating identification with the rival at a superordinate level (e.g. as joint fans of a region).
Marketing, get ready to rumble — How rivalry promotes distinctiveness for brands and consumers
(2018)
Scholars typically advise brands to stay away from public conflict with competitors as research has focused on negative consequences - e.g., price wars, escalating hostilities, and derogation. This research distinguishes between rivalry between firms (inter-firm brand rivalry) and rivalry between consumers (inter-consumer brand rivalry). Four studies and six samples show both types of rivalry can have positive consequences for both firms and consumers. Inter-firm brand rivalry boosts perceived distinctiveness of competing brands independent of consumption, attitude, familiarity, and involvement. Inter-consumer brand rivalry increases consumer group distinctiveness, an effect mediated by brand identification and rival brand disidentification. We extend social identity theory by demonstrating that: 1) outside actors like firms can promote inter-consumer rivalry through inter-firm rivalry and 2) promoting such conflict can actually provide benefits to consumers as well as firms. The paper challenges the axiom “never knock the competition,” deriving a counter-intuitive way to accomplish one of marketing's premier objectives.
Social comparison theories suggest that ingroups are strengthened whenever important outgroups are weakened (e.g., by losing status or power). It follows that ingroups have little reason to help outgroups facing an existential threat. We challenge this notion by showing that ingroups can also be weakened when relevant comparison outgroups are weakened, which can motivate ingroups to strategically offer help to ensure the outgroups' survival as a highly relevant comparison target. In three preregistered studies, we showed that an existential threat to an outgroup with high (vs. low) identity relevance affected strategic outgroup helping via two opposing mechanisms. The potential demise of a highly relevant outgroup increased participants’ perceptions of ingroup identity threat, which was positively related to helping. At the same time, the outgroup’s misery evoked schadenfreude, which was negatively related to helping. Our research exemplifies a group's secret desire for strong outgroups by underlining their importance for identity formation.
According to the third-person effect or the influence of presumed media influence approach, the presumption that the media has strong effects on other people can affect individuals’ attitudes and behavior. For instance, if people believe in strong media influences on others, they are more likely to increase their communication activities or support demands for restrictions on media. A standardized online survey among German journalists (N = 960) revealed that the stronger the journalists perceive the political online influence on the public to be, the more frequently they contradict unwanted political views in their articles. Moreover, even journalists are more likely to approve of restrictions on the Internet’s political influence, the stronger they believe the effects of online media to be. The data reveal no connections between communication activities and demands for restrictions.
Research information, i.e., data about research projects, organisations, researchers or research outputs such as publications or patents, is spread across the web, usually residing in institutional and personal web pages or in semi-open databases and information systems. While there exists a wealth of unstructured information, structured data is limited and often exposed following proprietary or less-established schemas and interfaces. Therefore, a holistic and consistent view on research information across organisational and national boundaries is not feasible. On the other hand, web crawling and information extraction techniques have matured throughout the last decade, allowing for automated approaches of harvesting, extracting and consolidating research information into a more coherent knowledge graph. In this work, we give an overview of the current state of the art in research information sharing on the web and present initial ideas towards a more holistic approach for boot-strapping research information from available web sources.
Background: One of the major challenges in pediatric intensive care is the detection of life-threatening health conditions under acute time constraints and performance pressure. This includes the assessment of pediatric organ dysfunction (OD) that demands extraordinary clinical expertise and the clinician’s ability to derive a decision based on multiple information and data sources. Clinical decision support systems (CDSS) offer a solution to support medical staff in stressful routine work. Simultaneously, detection of OD by using computerized decision support approaches has been scarcely investigated, especially not in pediatrics.
Objectives: The aim of the study is to enhance an existing, interoperable, and rulebased CDSS prototype for tracing the progression of sepsis in critically ill children by augmenting it with the capability to detect SIRS/sepsis-associated hematologic OD, and to determine its diagnostic accuracy.
Methods: We reproduced an interoperable CDSS approach previously introduced by our working group: (1) a knowledge model was designed by following the commonKADS methodology, (2) routine care data was semantically standardized and harmonized using openEHR as clinical information standard, (3) rules were formulated and implemented in a business rule management system. Data from a prospective diagnostic study, including 168 patients, was used to estimate the diagnostic accuracy of the rule-based CDSS using the clinicians’ diagnoses as reference
Catalogs of competency-based learning objectives (CLO) were introduced and promoted as a prerequisite for high-quality, systematic curriculum development. While this is common in medicine, the consistent use of CLO is not yet well established in epidemiology, biometry, medical informatics, biomedical informatics, and nursing informatics especially in Germany. This paper aims to identify underlying obstacles and give recommendations in order to promote the dissemination of CLO for curricular development in health data and information sciences. To determine these obstacles and recommendations a public online expert workshop was organized. This paper summarizes the findings.
Clinical scores and motion-capturing gait analysis are today’s gold standard for outcome measurement after knee arthroplasty, although they are criticized for bias and their ability to reflect patients’ actual quality of life has been questioned. In this context, mobile gait analysis systems have been introduced to overcome some of these limitations. This study used a previously developed mobile gait analysis system comprising three inertial sensor units to evaluate daily activities and sports. The sensors were taped to the lumbosacral junction and the thigh and shank of the affected limb. The annotated raw data was evaluated using our validated proprietary software. Six patients undergoing knee arthroplasty were examined the day before and 12 months after surgery. All patients reported a satisfactory outcome, although four patients still had limitations in their desired activities. In this context, feasible running speed demonstrated a good correlation with reported impairments in sports-related activities. Notably, knee flexion angle while descending stairs and the ability to stop abruptly when running exhibited good correlation with the clinical stability and proprioception of the knee. Moreover, fatigue effects were displayed in some patients. The introduced system appears to be suitable for outcome measurement after knee arthroplasty and has the potential to overcome some of the limitations of stationary gait labs while gathering additional meaningful parameters regarding the force limits of the knee.
NOA is a search engine for scientific images from open access publications based on full text indexing of all text referring to the images and filtering for disciplines and image type. Images will be annotated with Wikipedia categories for better discoverability and for uploading to WikiCommons. Currently we have indexed approximately 2,7 Million images from over 710 000 scientific papers from all fields of science.
Scientific papers from all disciplines contain many abbreviations and acronyms. In many cases these acronyms are ambiguous. We present a method to choose the contextual correct definition of an acronym that does not require training for each acronym and thus can be applied to a large number of different acronyms with only few instances. We constructed a set of 19,954 examples of 4,365 ambiguous acronyms from image captions in scientific papers along with their contextually correct definition from different domains. We learn word embeddings for all words in the corpus and compare the averaged context vector of the words in the expansion of an acronym with the weighted average vector of the words in the context of the acronym. We show that this method clearly outperforms (classical) cosine similarity. Furthermore, we show that word embeddings learned from a 1 billion word corpus of scientific exts outperform word embeddings learned from much larger general corpora.
Concreteness of words has been studied extensively in psycholinguistic literature. A number of datasets have been created with average values for perceived concreteness of words. We show that we can train a regression model on these data, using word embeddings and morphological features, that can predict these concreteness values with high accuracy. We evaluate the model on 7 publicly available datasets. Only for a few small subsets of these datasets prediction of concreteness values are found in the literature. Our results clearly outperform the reported results for these datasets.
Concreteness of words has been measured and used in psycholinguistics already for decades. Recently, it is also used in retrieval and NLP tasks. For English a number of well known datasets has been established with average values for perceived concreteness.
We give an overview of available datasets for German, their correlation and evaluate prediction algorithms for concreteness of German words. We show that these algorithms achieve similar results as for English datasets. Moreover, we show for all datasets there are no significant differences between a prediction model based on a regression model using word embeddings as features and a prediction algorithm based on word similarity according to the same embeddings.
Image captions in scientific papers usually are complementary to the images. Consequently, the captions contain many terms that do not refer to concepts visible in the image. We conjecture that it is possible to distinguish between these two types of terms in an image caption by analysing the text only. To examine this, we evaluated different features. The dataset we used to compute tf.idf values, word embeddings and concreteness values contains over 700 000 scientific papers with over 4,6 million images. The evaluation was done with a manually annotated subset of 329 images. Additionally, we trained a support vector machine to predict whether a term is a likely visible or not. We show that concreteness of terms is a very important feature to identify terms in captions and context that refer to concepts visible in images.
Malnutrition, nutritional deficiency, or undernutrition is an imbalanced nutritional status resulting from insufficient intake of nutrients to meet normal physiologic requirements. Malnutrition in childhood has both short-term consequences and long-term consequences on mental and physical health as well as the overall health development of children. Of all regions in the world, the Asia and the Pacific region has achieved the fastest rate of economic growth. There is no evidence that this rapid economic growth translates into a decline in malnutrition of children in Asian countries such as India.
The present investigation was conducted to investigate the in-vitro activity of ethanolic extract of roots of Centaurea behens by using DPPH radical scavenging activity, nitric oxide radical scavenging activity, hydrogen peroxide radical scavenging activity, hydroxyl radical. Result suggests that the extract possess significant antioxidant activity as compared to the standard ascorbic acid and thus further in vivo investigation is required to evaluate the medicinal significance of the extract which can be used for assessing the possible therapeutic importance of the drug.
Background: Stereotactic radiosurgery (SRS) is an effective treatment for trigeminal neuralgia (TN). Nevertheless, a proportion of patients will experience recurrence and treatment-related sensory disturbances. In order to evaluate the predictors of efficacy and safety of image-guided non-isocentric radiosurgery, we analyzed the impact of trigeminal nerve volume and the nerve dose/volume relationship, together with relevant clinical characteristics.
Methods: Two-hundred and ninety-six procedures were performed on 262 patients at three centers. In 17 patients the TN was secondary to multiple sclerosis (MS). Trigeminal pain and sensory disturbances were classified according to the Barrow Neurological Institute (BNI) scale. Pain-free-intervals were investigated using Kaplan Meier analyses. Univariate and multivariate Cox regression analyses were performed to identify predictors.
Results: The median follow-up period was 38 months, median maximal dose 72.4 Gy, median target nerve volume 25mm3, and median prescription dose 60 Gy. Pain control rate (BNI I-III) at 6, 12, 24, 36, 48, and 60 months were 96.8, 90.9, 84.2, 81.4, 74.2, and 71.2%, respectively. Overall, 18% of patients developed sensory disturbances. Patients with volume ≥ 30mm3 were more likely to maintain pain relief (p = 0.031), and low integral dose (< 1.4 mJ) tended to be associated with more pain recurrence than intermediate (1.4–2.7 mJ) or high integral dose (> 2.7 mJ; low vs. intermediate: log-rank test, χ2 = 5.02, p = 0.019; low vs. high: log-rank test, χ2 = 6.026, p = 0.014). MS, integral dose, and mean dose were the factors associated with pain recurrence, while re-irradiation and MS were predictors for sensory disturbance in the multivariate analysis.
Conclusions: The dose to nerve volume ratio is predictive of pain recurrence in TN, and re-irradiation has a major impact on the development of sensory disturbances after non-isocentric SRS. Interestingly, the integral dose may differ significantly in treatments using apparently similar dose and volume constraints.
Purpose: Radiology reports mostly contain free-text, which makes it challenging to obtain structured data. Natural language processing (NLP) techniques transform free-text reports into machine-readable document vectors that are important for creating reliable, scalable methods for data analysis. The aim of this study is to classify unstructured radiograph reports according to fractures of the distal fibula and to find the best text mining method.
Materials & Methods: We established a novel German language report dataset: a designated search engine was used to identify radiographs of the ankle and the reports were manually labeled according to fractures of the distal fibula. This data was used to establish a machine learning pipeline, which implemented the text representation methods bag-of-words (BOW), term frequency-inverse document frequency (TF-IDF), principal component analysis (PCA), non-negative matrix factorization (NMF), latent Dirichlet allocation (LDA), and document embedding (doc2vec). The extracted document vectors were used to train neural networks (NN), support vector machines (SVM), and logistic regression (LR) to recognize distal fibula fractures. The results were compared via cross-tabulations of the accuracy (acc) and area under the curve (AUC).
Results: In total, 3268 radiograph reports were included, of which 1076 described a fracture of the distal fibula. Comparison of the text representation methods showed that BOW achieved the best results (AUC = 0.98; acc = 0.97), followed by TF-IDF (AUC = 0.97; acc = 0.96), NMF (AUC = 0.93; acc = 0.92), PCA (AUC = 0.92; acc = 0.9), LDA (AUC = 0.91; acc = 0.89) and doc2vec (AUC = 0.9; acc = 0.88). When comparing the different classifiers, NN (AUC = 0,91) proved to be superior to SVM (AUC = 0,87) and LR (AUC = 0,85).
Conclusion: An automated classification of unstructured reports of radiographs of the ankle can reliably detect findings of fractures of the distal fibula. A particularly suitable feature extraction method is the BOW model.
Key Points:
- The aim was to classify unstructured radiograph reports according to distal fibula fractures.
- Our automated classification system can reliably detect fractures of the distal fibula.
- A particularly suitable feature extraction method is the BOW model.
Data and Information Science: Book of Abstracts at BOBCATSSS 2022 Hybrid Conference, 23rd - 25th of May 2022, Debrecen.
This year marks the 30th anniversary of the BOBCATSSS. The BOBCATSSS is an international, annual symposium designed for librarians and information professionals in a rapidly changing environment. Over the past 30 years, the conference has included exciting topics, great venues, interested guests and engaging presenters.
This year we would like to introduce the topics of the many papers presented in the Book of Abstracts for the first time in presence at the University of Debrecen and hybrid. The Book of Abstracts provides an overview of all presentations given at BOBCATSSS. Presentations are listed in alphabetical order by title and include speeches, Pecha Kuchas, posters and workshops.
The theme of BOBCATSSS is Data and Information Science. Data and information are the basis for decisions and processes in business, politics and science. Particularly important in the current era of digital transformation. This is exactly where this year's subthemes come in. They deal with data science, openness as well as institutional roles.
Background: Maintenance of metal homeostasis is crucial in bacterial pathogenicity as metal starvation is the most important mechanism in the nutritional immunity strategy of host cells. Thus, pathogenic bacteria have evolved sensitive metal scavenging systems to overcome this particular host defence mechanism. The ruminant pathogen Mycobacterium avium ssp. paratuberculosis (MAP) displays a unique gut tropism and causes a chronic progressive intestinal inflammation. MAP possesses eight conserved lineage specific large sequence polymorphisms (LSP), which distinguish MAP from its ancestral M. avium ssp. hominissuis or other M. avium subspecies. LSP14 and LSP15 harbour many genes proposed to be involved in metal homeostasis and have been suggested to substitute for a MAP specific, impaired mycobactin synthesis.
Results: In the present study, we found that a LSP14 located putative IrtAB-like iron transporter encoded by mptABC was induced by zinc but not by iron starvation. Heterologous reporter gene assays with the lacZ gene under control of the mptABC promoter in M. smegmatis (MSMEG) and in a MSMEGΔfurB deletion mutant revealed a zinc dependent, metalloregulator FurB mediated expression of mptABC via a conserved mycobacterial FurB recognition site. Deep sequencing of RNA from MAP cultures treated with the zinc chelator TPEN revealed that 70 genes responded to zinc limitation. Remarkably, 45 of these genes were located on a large genomic island of approximately 90 kb which harboured LSP14 and LSP15. Thirty-five of these genes were predicted to be controlled by FurB, due to the presence of putative binding sites. This clustering of zinc responsive genes was exclusively found in MAP and not in other mycobacteria.
Conclusions: Our data revealed a particular genomic signature for MAP given by a unique zinc specific locus, thereby suggesting an exceptional relevance of zinc for the metabolism of MAP. MAP seems to be well adapted to maintain zinc homeostasis which might contribute to the peculiarity of MAP pathogenicity.
Appropriate data models are essential for the systematic collection, aggregation, and integration of health data and for subsequent analysis. However, recommendations for modeling health data are often not publicly available within specific projects. Therefore, the project Zukunftslabor Gesundheit investigates recommendations for modeling. Expert interviews with five experts were conducted and analyzed using qualitative content analysis. Based on the condensed categories “governance”, “modeling” and “standards”, the project team generated eight hypotheses for recommendations on health data modeling. In addition, relevant framework conditions such as different roles, international cooperation, education/training and political influence were identified. Although emerging from interviewing a small convenience sample of experts, the results help to plan more extensive data collections and to create recommendations for health data modeling.
BACKGROUND: Even though physician rating websites (PRWs) have been gaining in importance in both practice and research, little evidence is available on the association of patients' online ratings with the quality of care of physicians. It thus remains unclear whether patients should rely on these ratings when selecting a physician. The objective of this study was to measure the association between online ratings and structural and quality of care measures for 65 physician practices from the German Integrated Health Care Network "Quality and Efficiency" (QuE). METHODS: Online reviews from two German PRWs were included which covered a three-year period (2011 to 2013) and included 1179 and 991 ratings, respectively. Information for 65 QuE practices was obtained for the year 2012 and included 21 measures related to structural information (N = 6), process quality (N = 10), intermediate outcomes (N = 2), patient satisfaction (N = 1), and costs (N = 2). The Spearman rank coefficient of correlation was applied to measure the association between ratings and practice-related information. RESULTS: Patient satisfaction results from offline surveys and the patients per doctor ratio in a practice were shown to be significantly associated with online ratings on both PRWs. For one PRW, additional significant associations could be shown between online ratings and cost-related measures for medication, preventative examinations, and one diabetes type 2-related intermediate outcome measure. There again, results from the second PRW showed significant associations with the age of the physicians and the number of patients per practice, four process-related quality measures for diabetes type 2 and asthma, and one cost-related measure for medication. CONCLUSIONS: Several significant associations were found which varied between the PRWs. Patients interested in the satisfaction of other patients with a physician might select a physician on the basis of online ratings. Even though our results indicate associations with some diabetes and asthma measures, but not with coronary heart disease measures, there is still insufficient evidence to draw strong conclusions. The limited number of practices in our study may have weakened our findings.
BACKGROUND: Over the past decade, physician-rating websites have been gaining attention in scientific literature and in the media. However, little knowledge is available about the awareness and the impact of using such sites on health care professionals. It also remains unclear what key predictors are associated with the knowledge and the use of physician-rating websites. OBJECTIVE: To estimate the current level of awareness and use of physician-rating websites in Germany and to determine their impact on physician choice making and the key predictors which are associated with the knowledge and the use of physician-rating websites. METHODS: This study was designed as a cross-sectional survey. An online panel was consulted in January 2013. A questionnaire was developed containing 28 questions; a pretest was carried out to assess the comprehension of the questionnaire. Several sociodemographic (eg, age, gender, health insurance status, Internet use) and 2 health-related independent variables (ie, health status and health care utilization) were included. Data were analyzed using descriptive statistics, chi-square tests, and t tests. Binary multivariate logistic regression models were performed for elaborating the characteristics of physician-rating website users. Results from the logistic regression are presented for both the observed and weighted sample. RESULTS: In total, 1505 respondents (mean age 43.73 years, SD 14.39; 857/1505, 57.25% female) completed our survey. Of all respondents, 32.09% (483/1505) heard of physician-rating websites and 25.32% (381/1505) already had used a website when searching for a physician. Furthermore, 11.03% (166/1505) had already posted a rating on a physician-rating website. Approximately 65.35% (249/381) consulted a particular physician based on the ratings shown on the websites; in contrast, 52.23% (199/381) had not consulted a particular physician because of the publicly reported ratings. Significantly higher likelihoods for being aware of the websites could be demonstrated for female participants (P<.001), those who were widowed (P=.01), covered by statutory health insurance (P=.02), and with higher health care utilization (P<.001). Health care utilization was significantly associated with all dependent variables in our multivariate logistic regression models (P<.001). Furthermore, significantly higher scores could be shown for health insurance status in the unweighted and Internet use in the weighted models. CONCLUSIONS: Neither health policy makers nor physicians should underestimate the influence of physician-rating websites. They already play an important role in providing information to help patients decide on an appropriate physician. Assuming there will be a rising level of public awareness, the influence of their use will increase well into the future. Future studies should assess the impact of physician-rating websites under experimental conditions and investigate whether physician-rating websites have the potential to reflect the quality of care offered by health care providers.
Objective: To evaluate the impact of different dissemination channels on the awareness and usage of hospital performance reports among referring physicians, as well as the usefulness of such reports from the referring physicians’ perspective.
Data sources/Study setting: Primary data collected from a survey with 277 referring physicians (response rate = 26.2%) in Nuremberg, Germany (03–06/2016).
Study design: Cluster-randomised controlled trial at the practice level. Physician practices were randomly assigned to one of two conditions: (1) physicians in the control arm could become aware of the performance reports via mass media channels (Mass Media, npr MM=132, nph MM=147); (2) physicians in the intervention arm also received a printed version of the report via mail (Mass and Special Media, npr MSM=117; nph MSM=130). <br> Principal findings: Overall, 68% of respondents recalled hospital performance reports and 21% used them for referral decisions. Physicians from the Mass and Special Media group were more likely to be aware of the performance reports (OR 4.16; 95% CI 2.16–8.00, p < .001) but not more likely to be influenced when referring patients into hospitals (OR 1.73; 95% CI 0.72–4.12, p > .05). On a 1 (very good) to 6 (insufficient) scale, the usefulness of the performance reports was rated 3.67 (±1.40). Aggregated presentation formats were rated more helpful than detailed hospital quality information.
Conclusions: Hospital quality reports have limited impact on referral practices. To increase the latter, concerns raised by referring physicians must be given more weight. Those principally refer to the underlying data, the design of the reports, and the lack of important information.
Background: Physician-rating websites have become a popular tool to create more transparency about the quality of health care providers. So far, it remains unknown whether online-based rating websites have the potential to contribute to a better standard of care. Objective: Our goal was to examine which health care providers use online rating websites and for what purposes, and whether health care providers use online patient ratings to improve patient care. Methods: We conducted an online-based cross-sectional study by surveying 2360 physicians and other health care providers (September 2015). In addition to descriptive statistics, we performed multilevel logistic regression models to ascertain the effects of providers' demographics as well as report card-related variables on the likelihood that providers implement measures to improve patient care. Results: Overall, more than half of the responding providers surveyed (54.66%, 1290/2360) used online ratings to derive measures to improve patient care (implemented measures: mean 3.06, SD 2.29). Ophthalmologists (68%, 40/59) and gynecologists (65.4%, 123/188) were most likely to implement any measures. The most widely implemented quality measures were related to communication with patients (28.77%, 679/2360), the appointment scheduling process (23.60%, 557/2360), and office workflow (21.23%, 501/2360). Scaled-survey results had a greater impact on deriving measures than narrative comments. Multilevel logistic regression models revealed medical specialty, the frequency of report card use, and the appraisal of the trustworthiness of scaled-survey ratings to be significantly associated predictors for implementing measures to improve patient care because of online ratings. Conclusions: Our results suggest that online ratings displayed on physician-rating websites have an impact on patient care. Despite the limitations of our study and unintended consequences of physician-rating websites, they still may have the potential to improve patient care.
Purpose: The calculation of aggregated composite measures is a widely used strategy to reduce the amount of data on hospital report cards. Therefore, this study aims to elicit and compare preferences of both patients as well as referring physicians regarding publicly available hospital quality information.
Methods: Based on systematic literature reviews as well as qualitative analysis, two discrete choice experiments (DCEs) were applied to elicit patients’ and referring physicians’ preferences. The DCEs were conducted using a fractional factorial design. Statistical data analysis was performed using multinomial logit models.
Results: Apart from five identical attributes, one specific attribute was identified for each study group, respectively. Overall, 322 patients (mean age 68.99) and 187 referring physicians (mean age 53.60) were included. Our models displayed significant coefficients for all attributes (p < 0.001 each). Among patients, “Postoperative complication rate” (20.6%; level range of 1.164) was rated highest, followed by “Mobility at hospital discharge” (19.9%; level range of 1.127), and ‘‘The number of cases treated” (18.5%; level range of 1.045). In contrast, referring physicians valued most the ‘‘One-year revision surgery rate’’ (30.4%; level range of 1.989), followed by “The number of cases treated” (21.0%; level range of 1.372), and “Postoperative complication rate” (17.2%; level range of 1.123).
Conclusion: We determined considerable differences between both study groups when calculating the relative value of publicly available hospital quality information. This may have an impact when calculating aggregated composite measures based on consumer-based weighting.
Background: Physician-rating websites are currently gaining in popularity because they increase transparency in the health care system. However, research on the characteristics and content of these portals remains limited.
Objective: To identify and synthesize published evidence in peer-reviewed journals regarding frequently discussed issues about physician-rating websites.
Methods: Peer-reviewed English and German language literature was searched in seven databases (Medline (via PubMed), the Cochrane Library, Business Source Complete, ABI/Inform Complete, PsycInfo, Scopus, and ISI web of knowledge) without any time constraints. Additionally, reference lists of included studies were screened to assure completeness. The following eight previously defined questions were addressed: 1) What percentage of physicians has been rated? 2) What is the average number of ratings on physician-rating websites? 3) Are there any differences among rated physicians related to socioeconomic status? 4) Are ratings more likely to be positive or negative? 5) What significance do patient narratives have? 6) How should physicians deal with physician-rating websites? 7) What major shortcomings do physician-rating websites have? 8) What recommendations can be made for further improvement of physician-rating websites?
Results: Twenty-four articles published in peer-reviewed journals met our inclusion criteria. Most studies were published by US (n=13) and German (n=8) researchers; however, the focus differed considerably. The current usage of physician-rating websites is still low but is increasing. International data show that 1 out of 6 physicians has been rated, and approximately 90% of all ratings on physician-rating websites were positive. Although often a concern, we could not find any evidence of "doctor-bashing". Physicians should not ignore these websites, but rather, monitor the information available and use it for internal and ex-ternal purpose. Several shortcomings limit the significance of the results published on physician-rating websites; some recommendations to address these limitations are presented.
Conclusions: Although the number of publications is still low, physician-rating websites are gaining more attention in research. But the current condition of physician-rating websites is lacking. This is the case both in the United States and in Germany. Further research is necessary to increase the quality of the websites, especially from the patients’ perspective.
Background: Physician-rating websites (PRWs) may lead to quality improvements in case they enable and establish a peer-to-peer communication between patients and physicians. Yet, we know little about whether and how physicians respond on the Web to patient ratings.
Objective: The objective of this study was to describe trends in physicians’ Web-based responses to patient ratings over time, to identify what physician characteristics influence Web-based responses, and to examine the topics physicians are likely to respond to.
Methods: We analyzed physician responses to more than 1 million patient ratings displayed on the German PRW, jameda, from 2010 to 2015. Quantitative analysis contained chi-square analyses and the Mann-Whitney U test. Quantitative content techniques were applied to determine the topics physicians respond to based on a randomly selected sample of 600 Web-based ratings and corresponding physician responses.
Results: Overall, physicians responded to 1.58% (16,640/1,052,347) of all Web-based ratings, with an increasing trend over time from 0.70% (157/22,355) in 2010 to 1.88% (6377/339,919) in 2015. Web-based ratings that were responded to had significantly worse rating results than ratings that were not responded to (2.15 vs 1.74, P<.001). Physicians who respond on the Web to patient ratings differ significantly from nonresponders regarding several characteristics such as gender and patient recommendation results (P<.001 each). Regarding scaled-survey rating elements, physicians were most likely to respond to the waiting time within the practice (19.4%, 99/509) and the time spent with the patient (18.3%, 110/600). Almost one-third of topics in narrative comments were answered by the physicians (30.66%, 382/1246).
Conclusions: So far, only a minority of physicians have taken the chance to respond on the Web to patient ratings. This is likely because of (1) the low awareness of PRWs among physicians, (2) the fact that only a few PRWs enable physicians to respond on the Web to patient ratings, and (3) the lack of an active moderator to establish peer-to-peer communication. PRW providers should foster more frequent communication between the patient and the physician and encourage physicians to respond on the Web to patient ratings. Further research is needed to learn more about the motivation of physicians to respond or not respond to Web-based patient ratings.
Purpose
This study aims to determine the intention to use hospital report cards (HRCs) for hospital referral purposes in the presence or absence of patient-reported outcomes (PROs) as well as to explore the relevance of publicly available hospital performance information from the perspective of referring physicians.
Methods
We identified the most relevant information for hospital referral purposes based on a literature review and qualitative research. Primary survey data were collected (May–June 2021) on a sample of 591 referring orthopedists in Germany and analyzed using structural equation modeling. Participating orthopedists were recruited using a sequential mixed-mode strategy and randomly allocated to work with HRCs in the presence (intervention) or absence (control) of PROs.
Results
Overall, 420 orthopedists (mean age 53.48, SD 8.04) were included in the analysis. The presence of PROs on HRCs was not associated with an increased intention to use HRCs (p = 0.316). Performance expectancy was shown to be the most important determinant for using HRCs (path coefficient: 0.387, p < .001). However, referring physicians have doubts as to whether HRCs can help them. We identified “complication rate” and “the number of cases treated” as most important for the hospital referral decision making; PROs were rated slightly less important.
Conclusions
This study underpins the purpose of HRCs, namely to support referring physicians in searching for a hospital. Nevertheless, only a minority would support the use of HRCs for the next hospital search in its current form. We showed that presenting relevant information on HRCs did not increase their use intention.
This paper aims to provide a structured overview of four open, participatory formats that are particularly applicable in inquiry-based teaching and learning contexts: hackathons, book sprints, barcamps, and learning circles. Using examples, mostly from the work and experience context of the Open Science Lab at TIB Hannover, we address concrete processes, working methods, possible outcomes and challenges.
The compilation offers an introduction to the topic and is intended to provide tools for testing in practice.
The Logical Observation Identifiers, Names and Codes (LOINC) is a common terminology used for standardizing laboratory terms. Within the consortium of the HiGHmed project, LOINC is one of the central terminologies used for health data sharing across all university sites. Therefore, linking the LOINC codes to the site-specific tests and measures is one crucial step to reach this goal. In this work we report our ongoing efforts in implementing LOINC to our laboratory information system and research infrastructure, as well as our challenges and the lessons learned. 407 local terms could be mapped to 376 LOINC codes of which 209 are already available to routine laboratory data. In our experience, mapping of local terms to LOINC is a widely manual and time consuming process for reasons of language and expert knowledge of local laboratory procedures.
Type 2 Diabetes Mellitus: Risk Evaluation and Advice in Undergraduate Students in Ashrafieh, Lebanon
(2016)
Type 2 diabetes mellitus (T2DM) is a chronic lifestyle disease. It has become evident that T2DM occurs even among the younger age groups.1 In Lebanon, T2DM has a major public health impact through high disease prevalence, significant downstream pathophysiologic effects, and enormous financial liabilities.2
Monitoring of clinical trials is a fundamental process required by regulatory agencies. It assures the compliance of a center to the required regulations and the trial protocol. Traditionally, monitoring teams relied on extensive on-site visits and source data verification. However, this is costly, and the outcome is limited. Thus, central statistical monitoring (CSM) is an additional approach recently embraced by the International Council for Harmonisation (ICH) to detect problematic or erroneous data by using visualizations and statistical control measures. Existing implementations have been primarily focused on detecting inlier and outlier data. Other approaches include principal component analysis and distribution of the data. Here we focus on the utilization of comparisons of centers to the Grand mean for different model types and assumptions for common data types, such as binomial, ordinal, and continuous response variables. We implement the usage of multiple comparisons of single centers to the Grand mean of all centers. This approach is also available for various non-normal data types that are abundant in clinical trials. Further, using confidence intervals, an assessment of equivalence to the Grand mean can be applied. In a Monte Carlo simulation study, the applied statistical approaches have been investigated for their ability to control type I error and the assessment of their respective power for balanced and unbalanced designs which are common in registry data and clinical trials. Data from the German Multiple Sclerosis Registry (GMSR) including proportions of missing data, adverse events and disease severity scores were used to verify the results on Real-World-Data (RWD).
Improving Risk Assessment in Clinical Trials: Toward a Systematic Risk-Based Monitoring Approach
(2021)
Regulatory authorities have encouraged the usage of a risk-based monitoring (RBM) system in clinical trials before trial initiation for detection of potential risks and inclusion of a mitigation plan in the monitoring strategy. Several RBM tools were developed after the International Council for Harmonization gave sponsors the flexibility to initiate an approach to enhance quality management in a clinical trial. However, various studies have demonstrated the need for improvement of the available RBM tools as each does not provide a comprehensive overview of the characteristics, focus, and application. This research lays out a rationale for a risk methodology assessment (RMA) within the RBM system. The core purpose of RMA is to deliver a scientifically based evaluation and decision of any potential risk in a clinical trial. Thereby, a monitoring plan can be developed to elude prior identified risk outcome. To demonstrate RMA’s theoretical approach in practice, a Shiny web application (R Foundation for Statistical Computing) was designed to describe the assessment process of risk analysis and visualization tools that eventually aid in focusing monitoring activities. RMA focuses on the identification of an individual risk and visualizes its weight on the trial. The scoring algorithm of the presented approach computes the assessment of the individual risk in a radar plot and computes the overall score of the trial. Moreover, RMA’s novelty lies in its ability to decrease biased decision making during risk assessment by categorizing risk influence and detectability; a characteristic pivotal to serve RBM in assessing risks, and in contributing to a better understanding in the monitoring technique necessary for developing a functional monitoring plan. Future research should focus on validating the power of RMAs to demonstrate its efficiency. This would facilitate the process of characterizing the strengths and weaknesses of RMA in practice.
Acute stroke care is a time-critical process. Improving communication
and documentation process may support a positive effect on medical outcome. To achieve this goal, a new system using a mobile application has been integrated into existing infrastructure at Hannover Medical School (MHH). Within a pilot project, this system has been brought into clinical daily routine in February 2022. Insights generated may support further applications in clinical use-cases.