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Background
The eResearch system “Prospective Monitoring and Management App (PIA)” allows researchers to implement questionnaires on any topic and to manage biosamples. Currently, we use PIA in the longitudinal study ZIFCO (Integrated DZIF Infection Cohort within the German National Cohort) in Hannover (Germany) to investigate e.g. associations of risk factors and infectious diseases. Our aim was to assess user acceptance and compliance to determine suitability of PIA for epidemiological research on transient infectious diseases.
Methods
ZIFCO participants used PIA to answer weekly questionnaires on health status and report spontaneous onset of symptoms. In case of symptoms of a respiratory infection, the app requested participants to self-sample a nasal swab for viral analysis. To assess user acceptance, we implemented the System Usability Scale (SUS) and fitted a linear regression model on the resulting score. For investigation of compliance with submitting the weekly health questionnaires, we used a logistic regression model with binomial response.
Results
We analyzed data of 313 participants (median age 52.5 years, 52.4% women). An average SUS of 72.0 reveals good acceptance of PIA. Participants with a higher technology readiness score at the beginning of study participation also reported higher user acceptance. Overall compliance with submitting the weekly health questionnaires showed a median of 55.7%. Being female, of younger age and being enrolled for a longer time decreased the odds to respond. However, women over 60 had a higher chance to respond than women under 60, while men under 40 had the highest chance to respond. Compliance with nasal swab self-sampling was 77.2%.
Discussion
Our findings show that PIA is suitable for the use in epidemiologic studies with regular short questionnaires. Still, we will focus on user engagement and gamification for the further development of PIA to help incentivize regular and long-term participation.
For the introduction of technical nursing care innovations, a usability assessment survey is conducted by nursing staff. The questionnaire is used before and after the introduction of technical products. This poster contribution shows the latest comparison of pre- and post-surveys on selected products.
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.
To learn a subject, the acquisition of the associated technical language is important.
Despite this widely accepted importance of learning the technical language, hardly any studies are published that describe the characteristics of most technical languages that students are supposed to learn. This might largely be due to the absence of specialized text corpora to study such languages at lexical, syntactical and textual level. In the present paper we describe a corpus of German physics text that can be used to study the language used in physics. A large and a small variant are compiled. The small version of the corpus consists of 5.3 Million words and is available on request.
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.
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.
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.
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.
In this poster we present the ongoing development of an integrated free and open source toolchain for semantic annotation of digitised cultural heritage. The toolchain development involves the specification of a common data model that aims to increase interoperability across diverse datasets and to enable new collaborative research approaches.
Harmonisation of German Health Care Data Using the OMOP Common Data Model – A Practice Report
(2023)
Data harmonization is an important step in large-scale data analysis and for generating evidence on real world data in healthcare. With the OMOP common data model, a relevant instrument for data harmonization is available that is being promoted by different networks and communities. At the Hannover Medical School (MHH) in Germany, an Enterprise Clinical Research Data Warehouse (ECRDW) is established and harmonization of that data source is the focus of this work. We present MHH’s first implementation of the OMOP common data model on top of the ECRDW data source and demonstrate the challenges concerning the mapping of German healthcare terminologies to a standardized format.
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).
Economic and political/governmental infrastructural factors are major contributors to the economic development/growth of all sectors of a country, such as in the area of healthcare systems and clinical research, including the pharmaceutical industry. But what is the interaction between economic, and political/governmental infrastructural factors and the development of healthcare systems, especially, the performance of the pharmaceutical industry? Information from selected articles of a literature search of PubMed and by using Google Advanced Search led to the generation of five categories of infrastructural factors, and were filled with data from 41 African Countries using the World Health Organization data repository. Median changes over time were given and tested by Wilcoxon signed-rank test and Friedman test, respectively. Analysis of factors related to availability of healthcare facilities showed that physicians and pharmacies were significant increased, with insignificantly decreased number of hospital beds. Healthcare Financing by the Government showed notable differences. Private health spending decreased significantly unlike Gross National Income. Analysis of infrastructural factors showed that stable supply of electricity and the associated use of the Internet improved significantly. The low level of data on the expansion of paved road networks suggests less developed medical services in remote rural areas. Healthcare systems in African countries improved over the last two decades, but differences between the individual countries still prevail and some of the countries cannot yet offer an attractive sales market for the products of pharmaceutical companies.
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.
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.
Chronic kidney disease is one of the main causes of mortality worldwide. It affects more than 800 million patients globally, accounting for approximately 10% of the general population. The significant burden of the disease prompts healthcare systems to implement adequate preventive and therapeutic measures. This systematic review and meta-analysis aimed to provide a concise summary of the findings published in the existing body of research about the influence that mobile health technology has on the outcomes of patients with the disease. A comprehensive systematic literature review was conducted from inception until March 1st, 2023. This systematic review and meta-analysis included all clinical trials that compared the efficacy of mobile app-based educational programs to that of more conventional educational treatment for the patients. Eleven papers were included in the current analysis, representing 759 CKD patients. 381 patients were randomly assigned to use the mobile apps, while 378 individuals were assigned to the control group. The mean systolic blood pressure was considerably lower in the mobile app group (MD -4.86; 95%-9.60, -0.13; p=0.04). Meanwhile, the mean level of satisfaction among patients who used the mobile app was considerably greater (MD 0.75; 95% CI 0.03, 1.46; p=0.04). Additionally, the mean self-management scores in the mobile app groups were significantly higher (SMD 0.534; 95% CI 0.201, 0.867; p=0.002). Mobile health applications are potentially valuable interventions for patients. This technology improved the self-management of the disease, reducing the mean levels of systolic blood pressure with a high degree of patient satisfaction.
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.
Background: The globalization of clinical research should also benefit the population in developing markets. In this context, the approval of tested medicines and the associated expansion of medical care beyond clinical studies would be desirable as a possible long-term benefit.
Objectives: This study was designed to compare the development of the number of clinical trials with the number of marketing authorizations of medicines on the African continent. To contrast these 2 parameters, the data were analyzed using the model of an ecological study.
Methods: To reflect the broad spectrum of African developing countries with diverse levels of development, the data collection was based on 2 geographically selected sample countries each from Central, North, East, West, and Southern Africa. Based on the ClinicalTrials.gov registry, the first step was to collect trends data on the development of the clinical trials in the 10 selected countries of the country list of the African Region published by the World Health Organization for the period 2015 to 2018. Subsequently, data on the current number of marketing authorizations of medicines in the selected sample countries were identified using the online registries of the national authorities. The data were utilized in comparative analyses.
Results: Eight out of 10 model countries showed an increase in the number of clinical trials, with the exceptions of Cameroon and Libya, which showed an overall decline in research activity over the entire time. In direct comparison with drug registrations, the numbers indicate a similar development. The only exception here is Nigeria, a country with a solid performance in clinical research and yet a decrease in medicine registrations since 2015.
Conclusions: The expected increase in the development of clinical research as result of the globalization trend can basically be observed in most of the model countries. However, this increase does not guarantee an improvement in the number of medicine registrations. Although this is evident in some of the selected model countries, it cannot be projected to the entire African region. This may be linked to the diverse development of the individual countries due to the different political situations and the varying degrees of clinical research infrastructure.
Legal documents often have a complex layout with many different headings, headers and footers, side notes, etc. For the further processing, it is important to extract these individual components correctly from a legally binding document, for example a signed PDF. A common approach to do so is to classify each (text) region of a page using its geometric and textual features. This approach works well, when the training and test data have a similar structure and when the documents of a collection to be analyzed have a rather uniform layout. We show that the use of global page properties can improve the accuracy of text element classification: we first classify each page into one of three layout types. After that, we can train a classifier for each of the three page types and thereby improve the accuracy on a manually annotated collection of 70 legal documents consisting of 20,938 text elements. When we split by page type, we achieve an improvement from 0.95 to 0.98 for single-column pages with left marginalia and from 0.95 to 0.96 for double-column pages. We developed our own feature-based method for page layout detection, which we benchmark against a standard implementation of a CNN image classifier. The approach presented here is based on corpus of freely available German contracts and general terms and conditions.
Both the corpus and all manual annotations are made freely available. The method is language agnostic.
Background
Systematic reviews demonstrated that gait variables are the most reliable predictors of future falls, yet are rarely included in fall screening tools. Thus, most tools have higher specificity than sensitivity, hence may be misleading/detrimental to care. Therefore, this study aimed to determine the validity, and reliability of the velocity field diagram (VFD -a gait analytical tool), and the Timed-up-and-go test (TUG)-commonly used in Nigeria as fall screening tools, compared to a gold standard (known fallers) among community-dwelling older adults.
Method
This is a cross-sectional observational study of 500 older adults (280 fallers and 220 non-fallers), recruited by convenience sampling technique at community health fora on fall prevention. Participants completed a 7-m distance with the number of steps and time it took determined and used to compute the stride length, stride frequency, and velocity, which regression lines formed the VFD. TUG test was simultaneously conducted to discriminate fallers from non-fallers. The cut-off points for falls were: TUG times ≥ 13.5 s; VFD’s intersection point of the stride frequency, and velocity regression lines (E1) ≥ 3.5velots. The receiver operating characteristic (ROC) area under the curves (AUC) was used to explore the ability of the E1 ≥ 3.5velots to discriminate between fallers and non-fallers. The VFD’s and TUG’s sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were determined. Alpha was set at p < 0.05.
Results
The VFD versus TUG sensitivity, specificity, PPV and NPV were 71%, 27%, 55%, and 42%, versus 39%, 59%, 55%, and 43%, respectively. The ROC’s AUC were 0.74(95%CI:0.597,0.882, p = 0.001) for the VFD. The optimal categorizations for discrimination between fallers/non-fallers were ≥ 3.78 versus ≤ 3.78 for VFD (fallers versus non-fallers prevalence is 60.71% versus 95.45%, respectively), with a classification accuracy or prediction rate of 0.76 unlike TUG with AUC = 0.53 (95% CI:0.353,0.700, p = 0.762), and a classification accuracy of 0.68, and optimal characterization of ≥ 12.81 s versus ≤ 12.81 (fallers and non-fallers prevalence = 92.86% versus 36.36%, respectively).
Conclusion
The VFD demonstrated a fair discriminatory power and greater reliability in identifying fallers than the TUG, and therefore, could replace the TUG as a primary tool in screening those at risk of falls.
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.
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.
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.
In this paper we investigate how concreteness and abstractness are represented in word embedding spaces. We use data for English and German, and show that concreteness and abstractness can be determined independently and turn out to be completely opposite directions in the embedding space. Various methods can be used to determine the direction of concreteness, always resulting in roughly the same vector. Though concreteness is a central aspect of the meaning of words and can be detected clearly in embedding spaces, it seems not as easy to subtract or add concreteness to words to obtain other words or word senses like e.g. can be done with a semantic property like gender.
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
Background: Upsurge in cardiopulmonary dysfunctions in Enugu, Nigeria, involved mainly cement workers, automobile spray painters, woodworkers, and Cleaners and was worsened in the dry season, suggesting the need for an occupation-specific characterization of the disease features and seasonal evaluation of air quality for prevention and management.
Methods: We conducted a randomized cross-sectional study of eighty consenting participants (in Achara Layout, Enugu), comprising 20 cement workers (39.50 ± 14.95 years), 20 automobile spray painters (40.75 ± 9.85 years), 20 woodworkers (52.20 ± 9.77 years), and 20 cleaners (42.30 ± 9.06 years). The air quality, some haematological (fibrinogen-Fc, and C-reactive protein-CRP), and cardiopulmonary parameters were measured and analyzed using ANCOVA, at p < 0.05.
Results: The dry season particulate matter (PM) in ambient air exceeded the WHO standards in the New layout [PM10 = 541.17 ± 258.72 µg/m3; PM2.5 = 72.92 ± 25.81 µg/m3] and the University campus [PM10 = 244 ± 74.79 µg/m3; PM2.5 = 30.33 ± 16.10 µg/m3], but the former was twice higher. The PM differed significantly (p < 0.05) across the sites. Forced expiratory volume at the first second (FEV1) (F = 6.128; p = 0.001), and Peak expiratory flow rate (PEFR) (F = 5.523; p = 0.002), differed significantly across the groups. FEV1/FVC% was < 70% in cement workers (55.33%) and woodworkers (61.79%), unlike, automobile spray painters (72.22%) and cleaners (70.66%). FEV1 and work duration were significantly and negatively related in cement workers (r = -0.46; r2 = 0.2116; p = 0.041 one-tailed). CRP (normal range ≤ 3.0 mg/L) and Fc (normal range—1.5–3.0 g/L) varied in cement workers (3.32 ± 0.93 mg/L versus 3.01 ± 0.85 g/L), automobile spray painters (2.90 ± 1.19 mg/L versus 2.54 ± 0.99 mg/L), woodworkers (2.79 ± 1.10 mg/L versus 2.37 ± 0.92 g/L) and cleaners (3.06 ± 0.82 mg/L versus 2.54 ± 0.70 g/L).
Conclusion(s): Poor air quality was evident at the study sites, especially in the dry season. Cement workers and automobile spray painters showed significant risks of obstructive pulmonary diseases while woodworkers had restrictive lung diseases. Cement workers and cleaners recorded the highest risk of coronary heart disease (CRP ≥ 3.0 mg/L). The similarity in Fc and CRP trends suggests a role for the inflammation-sensitive proteins in the determination of cardiovascular risk in cement workers and cleaners. Therefore, there are occupation-specific disease endpoints of public health concern that likewise warrant specific preventive and management approaches among the workers.
In the context of the ongoing digitization of interdisciplinary subjects, the need for digital literacy is increasing in all areas of everyday life. Furthermore, communication between science and society is facing new challenges, not least since the COVID-19 pandemic. In order to deal with these challenges and to provide target-oriented online teaching, new educational concepts for the transfer of knowledge to society are necessary. In the transfer project “Zukunftslabor Gesundheit” (ZLG), a didactic concept for the creation of E-Learning classes was developed. A key factor for the didactic concept is addressing heterogeneous target groups to reach the broadest possible spectrum of participants. The concept has already been used for the creation of the first ZLG E-Learning courses. This article outlines the central elements of the developed didactic concept and addresses the creation of the ZLG courses. The courses created so far appeal to different target groups and convey diverse types of knowledge at different levels of difficulty.
Objective
Cyberknife robotic radiosurgery (RRS) provides single-session high-dose radiotherapy of brain tumors with a steep dose gradient and precise real-time image-guided motion correction. Although RRS appears to cause more radiation necrosis (RN), the radiometabolic changes after RRS have not been fully clarified. 18F-FET-PET/CT is used to differentiate recurrent tumor (RT) from RN after radiosurgery when MRI findings are indecisive. We explored the usefulness of dynamic parameters derived from 18F-FET PET in differentiating RT from RN after Cyberknife treatment in a single-center study population.
Methods
We retrospectively identified brain tumor patients with static and dynamic 18F-FET-PET/CT for suspected RN after Cyberknife. Static (tumor-to-background ratio) and dynamic PET parameters (time-activity curve, time-to-peak) were quantified. Analyses were performed for all lesions taken together (TOTAL) and for brain metastases only (METS). Diagnostic accuracy of PET parameters (using mean tumor-to-background ratio >1.95 and time-to-peak of 20 min for RT as cut-offs) and their respective improvement of diagnostic probability were analyzed.
Results
Fourteen patients with 28 brain tumors were included in quantitative analysis. Time-activity curves alone provided the highest sensitivities (TOTAL: 95%, METS: 100%) at the cost of specificity (TOTAL: 50%, METS: 57%). Combined mean tumor-to-background ratio and time-activity curve had the highest specificities (TOTAL: 63%, METS: 71%) and led to the highest increase in diagnosis probability of up to 16% p. – versus 5% p. when only static parameters were used.
Conclusions
This preliminary study shows that combined dynamic and static 18F-FET PET/CT parameters can be used in differentiating RT from RN after RRS.
Background
Symptoms of depression are prevalent in people living with human immune deficiency virus/acquired immune deficiency syndrome (PLWHA), and worsened by lack of physical activity/exercises, leading to restriction in social participation/functioning. This raises the question: what is the extent to which physical exercise training affected, symptoms of depression, physical activity level (PAL) and social participation in PLWHA compared to other forms of intervention, usual care, or no treatment controls?
Method
Eight databases were searched up to July 2020, according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol. Only randomised controlled trials involving adults who were either on HAART/HAART-naïve and reported in the English language, were included. Two independent reviewers determined the eligibility of the studies, extracted data, assessed their quality, and risk of bias using the Physiotherapy Evidence Database (PEDro) tool. Standardised mean difference (SMD) was used as summary statistics for the mean primary outcome (symptoms of depression) and secondary outcomes (PAL and social participation) since different measuring tools/units were used across the included studies. Summary estimates of effects were determined using a random-effects model (I2).
Results
Thirteen studies met the inclusion criteria with 779 participants (n = 596 participants at study completion) randomised into the study groups, comprising 378 males, 310 females and 91 participants with undisclosed gender, and with an age range of 18–86 years. Across the studies, aerobic or aerobic plus resistance exercises were performed 2–3 times/week, at 40–60 min/session, and for between 6-24 weeks, and the risk of bias vary from high to low. Comparing the intervention to control groups showed significant difference in the symptoms of depression (SMD = − 0.74, 95% confidence interval (CI) − 1.01, − 0.48, p ≤ 0.0002; I2 = 47%; 5 studies; 205 participants) unlike PAL (SMD = 0.98, 95% CI − 0.25, 2.17, p = 0.11; I2 = 82%; 2 studies; 62 participants) and social participation (SMD = 0.04, 95% CI − 0.65, 0.73, p = 0.91; I2 = 90%; 6 studies; 373 participants).
Conclusion
Physical exercise training could have an antidepressant-like effect in PLWHA but did not affect PAL and social participation. However, the high heterogeneity in the included studies, implies that adequately powered randomised controlled trials with clinical/methodological similarity are required in future studies.
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.
Aim:
The most suitable method for assessment of response to peptide receptor radionuclide therapy (PRRT) of neuroendocrine tumors (NET) is still under debate. In this study we aimed to compare size (RECIST 1.1), density (Choi), Standardized Uptake Value (SUV) and a newly defined ZP combined parameter derived from Somatostatin Receptor (SSR) PET/CT for prediction of both response to PRRT and overall survival (OS).
Material and Methods:
Thirty-four NET patients with progressive disease (F:M 23:11; mean age 61.2 y; SD ± 12) treated with PRRT using either Lu-177 DOTATOC or Lu-177 DOTATATE and imaged with Ga-68 SSR PET/CT approximately 10–12 weeks prior to and after each treatment cycle were retrospectively analyzed. Median duration of follow-up after the first cycle was 63.9 months (range 6.2–86.2). A total of 77 lesions (2–8 per patient) were analyzed. Response assessment was performed according to RECIST 1.1, Choi and modified EORTC (MORE) criteria. In addition, a new parameter named ZP, the product of Hounsfield unit (HU) and SUVmean (Standard Uptake Value) of a tumor lesion, was tested. Further, SUV values (max and mean) of the tumor were normalized to SUV of normal liver parenchyma. Tumor response was defined as CR, PR, or SD. Gold standard for comparison of baseline parameters for prediction of response of individual target lesions to PRRT was change in size of lesions according to RECIST 1.1. For prediction of overall survival, the response after the first and second PRRT were tested.
Results:
Based on RECIST 1.1, Choi, MORE, and ZP, 85.3%, 64.7%, 61.8%, and 70.6% achieved a response whereas 14.7%, 35.3%, 38.2%, and 29.4% demonstrated PD (progressive disease), respectively. Baseline ZP and ZPnormalized were found to be the only parameters predictive of lesion progression after three PRRT cycles (AUC ZP 0.753; 95% CI 0.6–0.9, p 0.037; AUC ZPnormalized 0.766; 95% CI 0.6–0.9; p 0.029). Based on a cut-off-value of 1201, ZP achieved a sensitivity of 86% and a specificity of 67%, while ZPnormalized reached a sensitivity of 86% and a specificity of 76% at a cut-off-value of 198. Median OS in the total cohort was not reached. In univariate analysis amongst all parameters, only patients having progressive disease according to MORE after the second cycle of PRRT were found to have significantly shorter overall survival (median OS in objective responders not reached, in PD 29.2 months; p 0.015). Patients progressive after two cycles of PRRT according to ZP had shorter OS compared to those responding (median OS for responders not reached, for PD 47.2 months, p 0.066).
Conclusions:
In this explorative study, we showed that Choi, RECIST 1.1, and SUVmax-based response evaluation varied significantly from each other. Only patients showing progressive disease after two PRRT cycles according to MORE criteria had a worse prognosis while baseline ZP and
ZPnormalized performed best in predicting lesion progression after three cycles of PRRT.
A semiparametric approach for meta-analysis of diagnostic accuracy studies with multiple cut-offs
(2022)
The accuracy of a diagnostic test is often expressed using a pair of measures: sensitivity (proportion of test positives among all individuals with target condition) and specificity (proportion of test negatives among all individuals without targetcondition). If the outcome of a diagnostic test is binary, results from different studies can easily be summarized in a meta-analysis. However, if the diagnostic test is based on a discrete or continuous measure (e.g., a biomarker), several cut-offs within one study as well as among different studies are published. Instead of taking all information of the cut-offs into account in the meta-analysis, a single cut-off per study is often selected arbitrarily for the analysis, even though there are statistical methods for the incorporation of several cut-offs. For these methods, distributional assumptions have to be met and/or the models may not converge when specific data structures occur. We propose a semiparametric approach to overcome both problems. Our simulation study shows that the diagnostic accuracy is underestimated, although this underestimation in sensitivity and specificity is relatively small. The comparative approach of Steinhauser et al. is better in terms of coverage probability, but may lead to convergence problems. In addition to the simulation results, we illustrate the application of the semiparametric approach using a published meta-analysis for a diagnostic test differentiating between bacterial and viral meningitis in children.
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.
Wikidata and Wikibase as complementary research data management services for cultural heritage data
(2022)
The NFDI (German National Research Data Infrastructure) consortia are associations of various institutions within a specific research field, which work together to develop common data infrastructures, guidelines, best practices and tools that conform to the principles of FAIR data. Within the NFDI, a common question is: What is the potential of Wikidata to be used as an application for science and research? In this paper, we address this question by tracing current research usecases and applications for Wikidata, its relation to standalone Wikibase instances, and how the two can function as complementary services to meet a range of research needs. This paper builds on lessons learned through the development of open data projects and software services within the Open Science Lab at TIB, Hannover, in the context of NFDI4Culture – the consortium including participants across the broad spectrum of the digital libraries, archives, and museums field, and the digital humanities.
Introduction
Atopic dermatitis (AD) is a common inflammatory skin disease. Many patients are initiating a systemic therapy, if the disease is not adequately controlled with topical treatment only. Currently, there is little real-world evidence on the AD-related medical care situation in Germany. This study analyzed patient characteristics, treatment patterns, healthcare resource utilization and costs associated with systemically treated AD for the German healthcare system.
Methods
In this descriptive, retrospective cohort study, aggregated anonymized German health claims data from the InGef research database were used. Within a representative sample of four million insured individuals, patients with AD and systemic drug therapy initiation (SDTI) in the index year 2017 were identified and included into the study cohort. Systemic drug therapy included dupilumab, systemic corticosteroids (SCS) and systemic immunosuppressants (SIS). Patients were observed for one year starting from the date of SDTI in 2017.
Results
9975 patients were included (57.8% female, mean age 39.6 years [SD 25.5]). In the one-year observation period, the most common systemic drug therapy was SCS (> 99.0%). Administrations of dupilumab (0.3%) or dispensations of SIS were rare (cyclosporine: 0.5%, azathioprine: 0.6%, methotrexate: 0.1%). Median treatment duration of SCS, cyclosporine and azathioprine was 27 days, 102 days, and 109 days, respectively. 2.8% of the patients received phototherapy; 41.6% used topical corticosteroids and/or topical calcineurin inhibitor. Average annual costs for medications amounted to € 1237 per patient. Outpatient services were used by 99.6% with associated mean annual costs of € 943; 25.4% had at least one hospitalization (mean annual costs: € 5836). 5.3% of adult patients received sickness benefits with associated mean annual costs of € 5026.
Conclusions
Despite unfavorable risk–benefit profile, this study demonstrated a common treatment with SCS, whereas other systemic drug therapy options were rarely used. Furthermore, the results suggest a substantial economic burden for patients with AD and SDTI.
A new FOSS (free and open source software) toolchain and associated workflow is being developed in the context of NFDI4Culture, a German consortium of research- and cultural heritage institutions working towards a shared infrastructure for research data that meets the needs of 21st century data creators, maintainers and end users across the broad spectrum of the digital libraries and archives field, and the digital humanities. This short paper and demo present how the integrated toolchain connects: 1) OpenRefine - for data reconciliation and batch upload; 2) Wikibase - for linked open data (LOD) storage; and 3) Kompakkt - for rendering and annotating 3D models. The presentation is aimed at librarians, digital curators and data managers interested in learning how to manage research datasets containing 3D media, and how to make them available within an open data environment with 3D-rendering and collaborative annotation features.
Background and Objectives:
Drawing causal conclusions from real-world data (RWD) poses methodological challenges and risk of bias. We aimed to systematically assess the type and impact of potential biases that may occur when analyzing RWD using the case of progressive ovarian cancer.
Methods:
We retrospectively compared overall survival with and without second-line chemotherapy (LOT2) using electronic medical records. Potential biases were determined using directed acyclic graphs. We followed a stepwise analytic approach ranging from crude analysis and multivariable-adjusted Cox model up to a full causal analysis using a marginal structural Cox model with replicates emulating a reference randomized controlled trial (RCT). To assess biases, we compared effect estimates (hazard ratios [HRs]) of each approach to the
HR of the reference trial.
Results:
The reference trial showed an HR for second line vs. delayed therapy of 1.01 (95% confidence interval [95% CI]: 0.82e1.25). The corresponding HRs from the RWD analysis ranged from 0.51 for simple baseline adjustments to 1.41 (95% CI: 1.22e1.64) accounting for immortal time bias with time-varying covariates. Causal trial emulation yielded an HR of 1.12 (95% CI: 0.96e1.28).
Conclusion:
Our study, using ovarian cancer as an example, shows the importance of a thorough causal design and analysis if one is expecting RWD to emulate clinical trial results.
Aim
Musculoskeletal disorders are a major public health problem in most developed countries. As a main cause of chronic pain, they have resulted in an increasing prescription of opioids worldwide. With regard to the situation in Germany, this study aimed at estimating the prevalence of musculoskeletal diseases such as chronic low back pain (CLBP) and hip/knee osteoarthritis (OA) and at depicting the applied treatment patterns.
Subject and methods
German claims data from the InGef Research Database were analyzed over a 6-year period (2011–2016). The dataset contains over 4 million people, enrolled in German statutory health insurances. Inpatient and outpatient diagnoses were considered for case identification of hip/knee OA and CLBP. The World Health Organization (WHO) analgesic ladder was applied to categorize patients according to their pain management interventions. Information on demographics, comorbidities, and adjuvant medication was collected.
Results
In 2016, n = 2,693,481 individuals (50.5% female, 49.5% male) were assigned to the study population; 62.5% of them were aged 18–60 years. In 2016, n = 146,443 patients (5.4%) with CLBP and n = 307,256 patients (11.4%) with hip/knee OA were identified. Of those with pre-specified pain management interventions (CLBP: 66.3%; hip/knee OA: 65.1%), most patients received WHO I class drugs (CLBP: 73.6%; hip/knee OA: 68.7%) as the highest level.
Conclusion
This study provides indications that CLBP and hip/knee OA are common chronic pain conditions in Germany, which are often subjected to pharmacological pain management. Compared to non-opioid analgesic prescriptions of the WHO I class, the dispensation of WHO class II and III opioids was markedly lower, though present to a considerable extent.
This research focuses on the fundamental ideas and underlying principles of E-Learning technology, as well as theoretical considerations for an optimal learning environment. This theoretical exploration was then used as a basis for the design and construction of a new, interactive Web-Based ESH-Training. The quality and effectiveness of this new course was then compared with that of the existing analog PDF-Training via a test with a diverse sample of employee learners. Learners were later surveyed to ascertain their views on both trainings in terms of the quality of the content, facilitator, resources, and length. Results clearly showed that regardless of demographic factors, most employee learners preferred the new, Web-Based ESH-Training to the analog PDF-Training.
The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named “openEHR-to-FHIR” that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles. The tool provides a REST web service for ad hoc conversion of openEHR compositions to FHIR profiles.
Lack of knowledge regarding antibiotics use has been widely identified as a main reason for inappropriate antibiotics use which leads to antibiotic resistance phenomenon. This study aimed to evaluate the effects of pharmacist-initiated educational intervention on promoting appropriate use of antibiotics and reducing self-medication with antibiotics. A pre and post intervention study using two validated self-administered questionnaires was performed in Yogyakarta province. A-two hour session of course and case discussion was delivered as method of intervention. Pharmacy customers attended Gema Cermat program were invited conveniently to complete both of pre- and post-educational questionnaires. Descriptive presentation was conducted to show scores on questions. Knowledge scores were categorized as poor, adequate and high. Of 268 respondents, 34.22% respondents had poor level of knowledge before receiving educational intervention, but this number decreased into 12.21% after post-interventional phase. Another 28.23% respondents had adequate level of knowledge before and then elevated into 38.28% after receiving education about appropriate use of antibiotics. Pre-education, 37.43% participants had a high level of knowledge about antibiotics use and resistance, whereas after education the number became slightly higher (49.25%). A vast majority of respondents (75.24%) became more aware about appropriate antibiotics practice after receiving educational inter- vention. Overall, didactic educational intervention imposed higher knowledge and better practice regarding antibiotics use (p < 0.05). This study showed that using didactical education intervention towards antibiotics use and resistance can be an initial strategy that led to substantial improvement of appropriate antibiotics use. Further systemic interventions to educate people should be performed and evaluated in order to promote the appropriate use of antibiotics.
Objectives: Injury to major white matter pathways during language-area associated glioma surgery often leads to permanent loss of neurological function. The aim was to establish standardized tractography of language pathways as a predictor of language outcome in clinical neurosurgery.
Methods: We prospectively analyzed 50 surgical cases of patients with left perisylvian, diffuse gliomas. Standardized preoperative Diffusion-Tensor-Imaging (DTI)-based tractography of the 5 main language tracts (Arcuate Fasciculus [AF], Frontal Aslant Tract [FAT], Inferior Fronto-Occipital Fasciculus [IFOF], Inferior Longitudinal Fasciculus [ILF], Uncinate Fasciculus [UF]) and spatial analysis of tumor and tracts was performed. Postoperative imaging and the resulting resection map were analyzed for potential surgical injury of tracts. The language status was assessed preoperatively, postoperatively and after 3 months using the Aachen Aphasia Test and Berlin Aphasia Score. Correlation analyses, two-step cluster analysis and binary logistic regression were used to analyze associations of tractography results with language outcome after surgery.
Results: In 14 out of 50 patients (28%), new aphasic symptoms were detected 3 months after surgery. The preoperative infiltration of the AF was associated with functional worsening (cc = 0.314; p = 0.019). Cluster analysis of tract injury profiles revealed two areas particularly related to aphasia: the temporo-parieto-occipital junction (TPO; temporo-parietal AF, middle IFOF, middle ILF) and the temporal stem/peri-insular white matter (middle IFOF, anterior ILF, temporal UF, temporal AF). Injury to these areas (TPO: OR: 23.04; CI: 4.11 – 129.06; temporal stem: OR: 21.96; CI: 2.93 – 164.41) was associated with a higher-risk of persisting aphasia.
Conclusions: Tractography of language pathways can help to determine the individual aphasia risk profile presurgically. The TPO and temporal stem/peri-insular white matter were confirmed as functional nodes particularly sensitive to surgical injuries.
Methods for standard meta-analysis of diagnostic test accuracy studies are well established and understood. For the more complex case in which studies report test accuracy across multiple thresholds, several approaches have recently been proposed. These are based on similar ideas, but make different assumptions. In this article, we apply four different approaches to data from a recent systematic review in the area of nephrology and compare the results. The four approaches use: a linear mixed effects model, a Bayesian multinomial random effects model, a time-to-event model and a nonparametric model, respectively. In the case study data, the accuracy of neutrophil gelatinase-associated lipocalin for the diagnosis of acute kidney injury was assessed in different scenarios, with sensitivity and specificity estimates available for three thresholds in each primary study. All approaches led to plausible and mostly similar summary results. However, we found considerable differences in results for some scenarios, for example, differences in the area under the receiver operating characteristic curve (AUC) of up to 0.13. The Bayesian approach tended to lead to the highest values of the AUC, and the nonparametric approach tended to produce the lowest values across the different scenarios. Though we recommend using these approaches, our findings motivate the need for a simulation study to explore optimal choice of method in various scenarios.
As noted by Roman poet Virgil already more than 2,000 years ago: “The greatest wealth is health.”. Without health, there is no happiness, no peace, and no success according to the Reflections Recovery Center from Arizona, United States (USA, U.S.). The goal of the Healthy People 2020-project (HP2020), which is led by the Office of Disease Prevention and Health Promotion (ODPHP), was to “promote quality life, healthy development, and health behaviors across all life stages” among the U.S. population. HP2020 measures progress by using so-called Leading Health Indicators (LHI), reliable data sources, baseline values as well as targets for LHI-individual improvements for every measurable objective to be achieved by 2020 and each following decade. In the further course, these values were compared to student populations from the U.S., Germany, and Poland. The goal of this master's thesis was to obtain more data on international health, particularly among student populations. For the statistical analysis, data were obtained from an online survey that was distributed to students in at least one university in each of the three countries. In total, data from 380 students were analyzed in terms of HP2020 goal attainment. To determine if statistically significant differences were present, the z-test was used. The biggest differences emerged on the following topics: access to healthcare, environmental quality, obesity as well as reproductive and sexual health.
Background: Mobile text reminder (SMS) system is considered a viable strategy for targeting/facilitating healthy behavioural change including adherence to prescribed physical exercises (PE) and medication (antiretroviral therapy-ART) which should improve the quality of life (Qol) in people living with HIV/AIDS(PLWHA). Thus, the literature was appraised for evidence of SMS effectiveness in improving ART and PE adherence behaviours and QoL in PLWHA.
Methods: Eight databases–AMED, CINAHL, Cochrane Library, EMBASE, EMCARE, Ovid MEDLINE, PsycINFO, and PubMed-were searched up to December 2020, using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocol.This review included only randomised control trials (RCTs) investigating the effectiveness of SMS in improving QoL or PE or ART adherence behaviour or a combination of these variables in PLWHA >18 years.
Two independent reviewers determined the eligibility of the studies. Data were extracted and the quality of the study was assessed with the Physiotherapy Evidence Database (PEDro) tool. The primary outcomes were ART and PE adherence behaviours while the secondary outcome was QoL.
Result: A pooled estimate of effect was not calculated due to the heterogeneity of methods and outcome measures.
Therefore, a narrative synthesis of ten studies that met the inclusion criteria (n = 1621 participants at study completion) comprising males/females, aged ≥ 18 years, was done. There was a significant improvement in ART adherence behaviour except in three underpowered studies. Only the SMS interventions that were developed using the Starks 3-steps Adherence model was associated with positive outcome. The only study that evaluated QoL was underpowered and reported no significant change while there were no RCTs on PE.
Conclusion: Effects of SMS intervention trends towards a significant improvement in ART adherence behaviour in PLWHA. It is plausible that SMS reminders developed using the broader framework of the interpersonal health behaviour theory(ies) may have positive outcome. Nevertheless, the observed heterogeneity in the methods/outcome measures warrants a cautious interpretation of the findings. There is a lack/paucity of RCTs and therefore no evidence in support of the effectiveness of SMS intervention in improving PE adherence and QoL.
In order to ensure validity in legal texts like contracts and case law, lawyers rely on standardised formulations that are written carefully but also represent a kind of code with a meaning and function known to all legal experts. Using directed (acyclic) graphs to represent standardized text fragments, we are able to capture variations concerning time specifications, slight rephrasings, names, places and also OCR errors. We show how we can find such text fragments by sentence clustering, pattern detection and clustering patterns. To test the proposed methods, we use two corpora of German contracts and court decisions, specially compiled for this purpose. However, the entire process for representing standardised text fragments is language-agnostic. We analyze and compare both corpora and give an quantitative and qualitative analysis of the text fragments found and present a number of examples from both corpora.
Introduction: Piper crocatum Ruiz & Pav (P. crocatum) has been reported to accelerate the diabetic wound healing process empirically. Some studies showed the benefits of P. crocatum in treating various diseases but its mechanisms in diabetic wound healing have never been reported. In the present study we investigated the diabetic wound healing activity of the active fraction of P. crocatum on wounded hyperglycemia fibroblasts (wHFs).
Methods: Bioassay-guided fractionation was performed to get the most active fraction. The selected active fraction was applied to wHFs within 72 h incubation. Mimicking a diabetic condition was done using basal glucose media containing an additional 17 mMol/L D-glucose. A wound was simulated via the scratch assay. The collagen deposition was measured using Picro-Sirius Red and wound closure was measured using scratch wound assay. Underlying mechanisms through p53, aSMA, SOD1 and Ecadherin were measured using western blotting.
Results: We reported that FIV is the most active fraction of P. crocatum. We confirmed that FIV\(7.81 mg/ml, 15.62 mg/ml, 31.25 mg/ml, 62.5 mg/ml, and 125 mg/ml) induced the collagen deposition and wound closure of wHFs. Furthermore, FIV treatment (7.81 mg/ml, 15.62 mg/ml, 31.25 mg/ml) down-regulated the protein expression level of p53 and up-regulated the protein expression levels of aSMA, E-cadherin, and SOD1.
Discussion/conclusions: Our findings suggest that ameliorating collagen deposition and wound closure through protein regulation of p53, aSMA, E-cadherin, and SOD1 are some of the mechanisms by which FIV of P. crocatum is involved in diabetic wound healing therapy.
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.
Introduction: Renal cell carcinoma (RCC), an immunogenic tumor, is the most common form of kidney cancer worldwide. Immune checkpoint inhibitors (ICIs) play an important role in the treatment of metastatic RCC. Programmed death-ligand (PD-L1) has already been proposed as a possible prognosticator for ICIs effectiveness. To elucidate the feasible role of ICIs in neoadjuvant settings, we have assessed the most common PD-L1 expression modalities [tumor proportion score (TPS), combined positivity score (CPS) and inflammatory cell (IC) score] in primary tumors (PTs) and venous tumor thrombi (VTT) in first diagnosed, previously untreated RCC patients with accompanying
VTT.
Methods: Between January 1999 and December 2016, 71 patients with a first diagnosed, untreated, locally advanced RCC (aRCC) (≥ pT3a) underwent surgery in Hanover Medical School (MHH). PD-L1 expression was examined separately in PTs and VTT using the CPS, IC score and TPS. We also considered the age at the time of the initial surgery and gender as probable influencing factors. By using a cutoff value of 1 (1%), PD-L1 expression levels in PTs and VTT were assessed to enable the determination of any frequency differences.
Results: Positive scores for PTs were shown by 54 (CPS), 53 (IC score) and 34 (TPS) patients, whereas in VTT, positive scores were evaluated
for a total of 50 (CPS), 47 (IC-score) and 36 (TPS) patients. No statistically significant differences were obtained between the PD-L1 expression immunoscores for PTs and VTT. The covariates age at the time of the initial surgery and gender could not be statistically proven to influence the differences in PD-L1 expression between the
VTT and PTs.
Conclusion: To the best of our knowledge, this research is the largest study to investigate PD-L1 expression in PTs and VTT in 71 cases. It could have relevance for the future development of neoadjuvant immunotherapy options, particularly in aRCC with VTT.