Pathogenetic mechanisms and therapeutic approaches of acute-to-chronic liver failure.

Liver cirrhosis is the end stage of all chronic liver diseases and contributes significantly to overall mortality of 2% globally. The age-standardized mortality from liver cirrhosis in Europe is between 10 and 20% and can be explained by not only the development of liver cancer but also the acute deterioration in the patient's overall condition. The development of complications including accumulation of fluid in the abdomen (ascites), bleeding in the gastrointestinal tract (variceal bleeding), bacterial infections, or a decrease in brain function (hepatic encephalopathy) define an acute decompensation that requires therapy and often leads to acute-on-chronic liver failure (ACLF) by different precipitating events. However, due to its complexity and organ-spanning nature, the pathogenesis of ACLF is poorly understood, and the common underlying mechanisms leading to the development of organ dysfunction or failure in ACLF are still elusive. Apart from general intensive care interventions, there are no specific therapy options for ACLF. Liver transplantation is often not possible in these patients due to contraindications and a lack of prioritization. In this review, we describe the framework of the ACLF-I project consortium funded by the Hessian Ministry of Higher Education, Research and the Arts (HMWK) based on existing findings and will provide answers to these open questions.

[Healthcare networks for people with rare diseases: integrating data and expertise]. / Versorgernetzwerke für Menschen mit Seltenen Erkrankungen: Daten und Expertise bündeln.

In the European Union (EU), rare diseases (RDs) are diseases that affect no more than 5 in 10,000 people. Due to their rarity, clinical expertise and quality-assured care structures are scarce, and research is more difficult compared to other diseases. However, these problems can be overcome by means of national and transnational RD care networks. Data and expertise are pooled in these networks.In the EU, the European Reference Networks (ERNs) for Rare and Complex Diseases cooperate across borders. Important services provided by ERNs using health data include diagnostic coding of RDs, conducting virtual cross-border case conferences, and establishing European registries that are used to measure and improve the quality of care. In ERNs, local data generation and documentation combine with network-wide data infrastructures. This paper describes the data-based services in and for RD healthcare networks: (1) diagnostic coding, (2) cross-border case conferences, and (3) ERN registries for RD patient care. The final section discusses the integration of the networks into national healthcare systems.In order to achieve the best possible benefit for SE patients, ERN activities and structures need to be better integrated into national healthcare systems. In Germany, the Medical Informatics Initiative and the German Reference Networks play a central role in this regard.

Evaluation of a clinical decision support system for rare diseases: a qualitative study.

BACKGROUND: Rare Diseases (RDs) are difficult to diagnose. Clinical Decision Support Systems (CDSS) could support the diagnosis for RDs. The Medical Informatics in Research and Medicine (MIRACUM) consortium developed a CDSS for RDs based on distributed clinical data from eight German university hospitals. To support the diagnosis for difficult patient cases, the CDSS uses data from the different hospitals to perform a patient similarity analysis to obtain an indication of a diagnosis. To optimize our CDSS, we conducted a qualitative study to investigate usability and functionality of our designed CDSS. METHODS: We performed a Thinking Aloud Test (TA-Test) with RDs experts working in Rare Diseases Centers (RDCs) at MIRACUM locations which are specialized in diagnosis and treatment of RDs. An instruction sheet with tasks was prepared that the participants should perform with the CDSS during the study. The TA-Test was recorded on audio and video, whereas the resulting transcripts were analysed with a qualitative content analysis, as a ruled-guided fixed procedure to analyse text-based data. Furthermore, a questionnaire was handed out at the end of the study including the System Usability Scale (SUS). RESULTS: A total of eight experts from eight MIRACUM locations with an established RDC were included in the study. Results indicate that more detailed information about patients, such as descriptive attributes or findings, can help the system perform better. The system was rated positively in terms of functionality, such as functions that enable the user to obtain an overview of similar patients or medical history of a patient. However, there is a lack of transparency in the results of the CDSS patient similarity analysis. The study participants often stated that the system should present the user with an overview of exact symptoms, diagnosis, and other characteristics that define two patients as similar. In the usability section, the CDSS received a score of 73.21 points, which is ranked as good usability. CONCLUSIONS: This qualitative study investigated the usability and functionality of a CDSS of RDs. Despite positive feedback about functionality of system, the CDSS still requires some revisions and improvement in transparency of the patient similarity analysis.

[se-atlas.de-Medical care atlas for people with rare diseases]. / se-atlas.de ­ Versorgungsatlas für Menschen mit Seltenen Erkrankungen.

In the European Union a disease is classified as rare if it affects no more than 5 out of 10,000 people. Currently, there are more than 6000 rare diseases, consisting of a large and heterogeneous number of different diseases that are complex in their symptomatology, multidimensional and therefore difficult to classify in everyday medical practice. This complicates the diagnosis and treatment as well as finding a suitable contact person, as there are only a few experts for each individual rare disease. The medical care atlas for rare diseases www.se-atlas.de enables the search for care facilities and patient organizations for specific rare diseases by disease name and presents the search results geographically. It also provides an overview of all German centers for rare diseases, which are a contact point for patients with an unclear diagnosis. The se-atlas serves as a compass through the heterogeneous amount of information on care facilities for rare diseases and provides low-threshold information for a broad user group, from affected persons to members of the medical care team.

Interviews with experts in rare diseases for the development of clinical decision support system software - a qualitative study.

BACKGROUND: Patients with rare diseases (RDs) are often diagnosed too late or not at all. Clinical decision support systems (CDSSs) could support the diagnosis in RDs. The MIRACUM (Medical Informatics in Research and Medicine) consortium, which is one of four funded consortia in the German Medical Informatics Initiative, will develop a CDSS for RDs based on distributed clinical data from ten university hospitals. This qualitative study aims to investigate (1) the relevant organizational conditions for the operation of a CDSS for RDs when diagnose patients (e.g. the diagnosis workflow), (2) which data is necessary for decision support, and (3) the appropriate user group for such a CDSS. METHODS: Interviews were carried out with RDs experts. Participants were recruited from staff physicians at the Rare Disease Centers (RDCs) at the MIRACUM locations, which offer diagnosis and treatment of RDs. An interview guide was developed with a category-guided deductive approach. The interviews were recorded on an audio device and then transcribed into written form. We continued data collection until all interviews were completed. Afterwards, data analysis was performed using Mayring's qualitative content analysis approach. RESULTS: A total of seven experts were included in the study. The results show that medical center guides and physicians from RDC B-centers (with a focus on different RDs) are involved in the diagnostic process. Furthermore, interdisciplinary case discussions between physicians are conducted. The experts explained that RDs exist which cannot be fully differentiated, but rather described only by their overall symptoms or findings: diagnosis is dependent on the disease or disease group. At the end of the diagnostic process, most centers prepare a summary of the patient case. Furthermore, the experts considered both physicians and experts from the B-centers to be potential users of a CDSS. The experts also have different experiences with CDSS for RDs. CONCLUSIONS: This qualitative study is a first step towards establishing the requirements for the development of a CDSS for RDs. Further research is necessary to create solutions by also including the experts on RDs.

[Patient registries for rare diseases in Germany: concept paper of the NAMSE strategy group]. / Patientenregister für Seltene Erkrankungen in Deutschland: Konzeptpapier der Strategiegruppe "Register" des Nationalen Aktionsbündnisses für Menschen mit Seltenen Erkrankungen (NAMSE).

The National Action Plan for People with Rare Diseases contains 52 concrete actions, including in the fields of care, research, diagnosis, and information management. With the aim of improving the quality and interoperability of national registries in the long term, action 28 proposed the establishment of a "Rare Diseases Registry" strategy group. The strategy group began its work in 2016. In this report, the group takes into account developments at the national and international level in order to develop recommendations for national initiatives.In addition to this, the group reports on consent and implementation as well as on the adaptation of a minimal dataset for use in rare disease registries and mapping the used data elements and schemata in a metadata repository. This position paper was created by the strategy group together with additional authors. The paper reached a consensus within the strategy group and can be seen as a concept paper of the Rare Diseases Registry strategy group.

Telephone health services in the field of rare diseases: a qualitative interview study examining the needs of patients, relatives, and health care professionals in Germany.

BACKGROUND: Rare diseases are, by definition, very serious and chronic diseases with a high negative impact on quality of life. Approximately 350 million people worldwide live with rare diseases. The resulting high disease burden triggers health information search, but helpful, high-quality, and up-to-date information is often hard to find. Therefore, the improvement of health information provision has been integrated in many national plans for rare diseases, discussing the telephone as one access option. In this context, this study examines the need for a telephone service offering information for people affected by rare diseases, their relatives, and physicians. METHODS: In total, 107 individuals participated in a qualitative interview study conducted in Germany. Sixty-eight individuals suffering from a rare disease or related to somebody with rare diseases and 39 health care professionals took part. Individual interviews were conducted using a standardized semi-structured questionnaire. Interviews were analysed using the qualitative content analysis, triangulating patients, relatives, and health care professionals. The fulfilment of qualitative data processing standards has been controlled for. RESULTS: Out of 68 patients and relatives and 39 physicians, 52 and 18, respectively, advocated for the establishment of a rare diseases telephone service. Interviewees expected a helpline to include expert staffing, personal contact, good availability, low technical barriers, medical and psychosocial topics of counselling, guidance in reducing information chaos, and referrals. Health care professionals highlighted the importance of medical topics of counselling-in particular, differential diagnostics-and referrals. CONCLUSIONS: Therefore, the need for a national rare diseases helpline was confirmed in this study. Due to limited financial resources, existing offers should be adapted in a stepwise procedure in accordance with the identified attributes.

Rare Diseases on the Internet: An Assessment of the Quality of Online Information.

BACKGROUND: The importance of the Internet as a medium for publishing and sharing health and medical information has increased considerably during the last decade. Nonetheless, comprehensive knowledge and information are scarce and difficult to find, especially for rare diseases. Additionally, the quality of health or medical information about rare diseases is frequently difficult to assess for the patients and their family members. OBJECTIVE: The aim of this study is to assess the quality of information on the Internet about rare diseases. Additionally, the study aims to evaluate if the quality of information on rare diseases varies between different information supplier categories. METHODS: A total of 13 quality criteria for websites providing medical information about rare diseases were transferred to a self-disclosure questionnaire. Identified providers of information on the Internet about rare diseases were invited to fill out the questionnaire. The questionnaire contained questions about the information provider in general (eg, supplier category, information category, language, use of quality certificates, and target group) and about quality aspects that reflect the 13 quality criteria. Differences in subgroup analyses were performed using t tests. RESULTS: We identified 693 websites containing information about rare diseases. A total of 123 questionnaires (17.7%) were completely filled out by the information suppliers. For the remaining identified suppliers (570/693, 82.3%), the questionnaires were filled out by the authors based on the information available on their website. In many cases, the quality of websites was proportionally low. Furthermore, subgroup analysis showed no statistically significant differences between the quality of information provided by support group/patient organization compared to medical institution (P=.19). The quality of information by individuals (patient/relative) was significantly lower compared to information provided by support group/patient organization (P=.001), medical institution (P=.009), and other associations and sponsoring bodies (P=.001) as well. CONCLUSIONS: Overall, the quality of information on the Internet about rare diseases is low. Quality certificates are rarely used and important quality criteria are often not fulfilled completely. Additionally, some information categories are underrepresented (eg, information about psychosocial counseling, social-legal advice, and family planning). Nevertheless, due to the high amount of information provided by support groups, this study shows that these are extremely valuable sources of information for patients suffering from a rare disease and their relatives.

[se-atlas - the health service information platform for people with rare diseases : Supporting research on medical care institutions and support groups]. / se-atlas ­ Versorgungsatlas für Menschen mit seltenen Erkrankungen : Unterstützung bei der Recherche nach Versorgungseinrichtungen und Selbsthilfeorganisationen.

se-atlas - the health service information platform for rare diseases - is part of the German National Action Plan for People with Rare Diseases and is funded by the German Federal Ministry of Health. The objective of se-atlas as a web-based platform is to illustrate those medical care institutions that are linked to rare diseases, in a transparent and user-friendly way. The website provides an overview of medical care institutions and support groups focusing on rare diseases in Germany. The primary target groups of se-atlas are affected patients, their relatives and physicians but can also include non-medical professionals and the general public. In order to make it easier to look up medical care institutions or support groups and optimize the search results displayed, various strategies are being developed and evaluated. Hence, the allocation of diseases to appropriate medical care institutions and support groups is currently a main focus. Since its launch in 2015, se-atlas has grown continuously and now incorporates five times more entries than were included 20 months prior. Among this data are the current rare diseases centres in Germany, which play a major role in providing patient-centred healthcare by acting as primary contact points for people with rare diseases. Further expansion and maintenance of the data base raises several organisational and software-related challenges. For one, the data should be completed by adding more high-quality information, while not neglecting the existing entries and maintaining their high level of quality in the long term.

[Registries for rare diseases : OSSE - An open-source framework for technical implementation]. / Register für seltene Erkrankungen : OSSE ­ ein Open-Source-Framework für die technische Umsetzung.

Meager amounts of data stored locally, a small number of experts, and a broad spectrum of technological solutions incompatible with each other characterize the landscape of registries for rare diseases in Germany. Hence, the free software Open Source Registry for Rare Diseases (OSSE) was created to unify and streamline the process of establishing specific rare disease patient registries. The data to be collected is specified based on metadata descriptions within the registry framework's so-called metadata repository (MDR), which was developed according to the ISO/IEC 11179 standard. The use of a central MDR allows for sharing the same data elements across any number of registries, thus providing a technical prerequisite for making data comparable and mergeable between registries and promoting interoperability.With OSSE, the foundation is laid to operate linked patient registries while respecting strong data protection regulations. Using the federated search feature, data for clinical studies can be identified across registries. Data integrity, however, remains intact since no actual data leaves the premises without the owner's consent. Additionally, registry solutions other than OSSE can participate via the OSSE bridgehead, which acts as a translator between OSSE registry networks and non-OSSE registries. The pseudonymization service Mainzelliste adds further data protection.Currently, more than 10 installations are under construction in clinical environments (including university hospitals in Frankfurt, Hamburg, Freiburg and Münster). The feedback given by the users will influence further development of OSSE. As an example, the installation process of the registry for undiagnosed patients at University Hospital Frankfurt is described in more detail.

[Central information portal on rare diseases : Implementation of quality- and needs-oriented information management]. / Zentrales Informationsportal über seltene Erkrankungen : Umsetzung eines qualitäts- und bedarfsorientierten Informationsmanagements.

BACKGROUND: A central information portal on rare diseases (ZIPSE) has been conceptualized and implemented that allows patients, relatives and health care professionals to access quality-assured information. For this purpose, quality criteria have been developed specifically for rare diseases. At the same time, the information basis should take into account the specific needs of those interested. OBJECTIVES: The needs of patients and relatives regarding online-based information are analyzed. Based on this, we examined to what extent the information basis, which is available according to the ZIPSE quality criteria, can cover these needs. If necessary, measures have to be developed to ensure quality- as well as needs-oriented information management. MATERIALS AND METHODS: Qualitative interviews with patients and relatives were conducted, which were then evaluated using content analysis. Subsequently, a quantitative evaluation of the information on rare diseases in the portal was made. The research addresses how many websites do not fulfil the quality criteria, from which group of provider these websites originate and which criteria are not fulfilled. This is followed by a comparison of the quantitative and qualitative results. RESULTS AND CONCLUSIONS: When looking for information on the Internet, the websites of self-help groups represent a significant source. These are perceived as very trustworthy and in the later course of the disease, offer detailed information on important information areas. Information websites from self-help groups, however, often do not meet quality requirements. Therefore, a transparent representation is made regarding the quality of the ZIPSE information pages. Pages that are not quality-assured can be actively requested, but will be clearly identified.

Rare Diseases in Citizen Science - Preliminary Experiences in Developing a Personal Health App.

SelEe is a German citizen science project aiming to develop a smartphone app for a patient-managed record. The goal is to study rare diseases with the support of interested citizens and people affected by rare diseases. We established a core research team, including professional researchers (leading the project) and citizens. Citizens have the opportunity to discuss the progress, make suggestions regarding the app's design and data entry and contribute to the dissemination of the project. To gather feedback and experiences from the core research team, we performed an online questionnaire regarding the topics "influence and communication", "improvements and learning effect", and "satisfaction". Finally, 9 citizens of the core research team participated. The results show that the citizens are very satisfied with the design of the app, their participation opportunities and the communication in the project.

Editing Physicians' Responses Using GPT-4 for Academic Research.

The integration of Artificial Intelligence (AI) into digital healthcare, particularly in the anonymisation and processing of health information, holds considerable potential. OBJECTIVES: To develop a methodology using Generative Pre-trained Transformer (GPT) models to preserve the essence of medical advice in doctors' responses, while editing them for use in scientific studies. METHODS: German and English responses from EXABO, a rare respiratory disease platform, were processed using iterative refinement and other prompt engineering techniques, with a focus on removing identifiable and irrelevant content. RESULTS: Of 40 responses tested, 31 were accurately modified according to the developed guidelines. Challenges included misclassification and incomplete removal, with incremental prompting proving more accurate than combined prompting. CONCLUSION: GPT-4 models show promise in medical response editing, but face challenges in accuracy and consistency. Precision in prompt engineering is essential in medical contexts to minimise bias and retain relevant information.

Translation of Ontological Concepts from English into German Using Commercial Translation Software and Expert Evaluation.

Medical ontologies are mostly available in English. This presents a language barrier that is a limitation in research and automated processing of patient data. The manual translation of ontologies is complex and time-consuming. However, there are commercial translation tools that have shown promising results in the field of medical terminology translation. The aim of this study is to translate selected terms of the Human Phenotype Ontology (HPO) from English into German using commercial translators. Six medical experts evaluated the translation candidates in an iterative process. The results show commercial translators, with DeepL in the lead, provide translations that are positively evaluated by experts. With a broader study scope and additional optimization techniques, commercial translators could support and facilitate the process of translating medical ontologies.

Initial User-Centred Design of an AI-Based Clinical Decision Support System for Primary Care.

A clinical decision support system based on different methods of artificial intelligence (AI) can support the diagnosis of patients with unclear diseases by providing tentative diagnoses as well as proposals for further steps. In a user-centred-design process, we aim to find out how general practitioners envision the user interface of an AI-based clinical decision support system for primary care. A first user-interface prototype was developed using the task model based on user requirements from preliminary work. Five general practitioners evaluated the prototype in two workshops. The discussion of the prototype resulted in categorized suggestions with key messages for further development of the AI-based clinical decision support system, such as the integration of intelligent parameter requests. The early inclusion of different user feedback facilitated the implementation of a user interface for a user-friendly decision support system.

Exploring patient-centered design solutions of a telehealth app for HIV - A qualitative study.

BACKGROUND: The Communication and Tracing App HIV (COMTRAC-HIV) project is developing a mobile health (mHealth) app for integrated care of HIV patients in Germany. The complexity of HIV treatment and continuous care necessitates the need for tailored mHealth solutions. This qualitative study explores design solutions and a prototype to enhance the app's functionality and effectiveness. METHODS: A total of eight HIV patients and pre-exposure prophylaxis (PrEP) users, recruited at the HIV Center Frankfurt, participated in focus groups and thinking-aloud tests (TA test). In the focus groups, design solutions were discussed for user-interface clarity, leading to the development of an interactive prototype, the usability of which was evaluated with a TA test. Data collection involved video/audio recordings. Qualitative analysis was conducted using a deductive category system, and focused on app design and usage in focus groups, and layout, navigation, interaction, terminology, comprehension, feedback, and level of satisfaction in TA tests. RESULTS: The app was commended for its simple, clear design, especially its medication reminders and health tracking features. Opinions on the symptom diary varied however, respondents noting it more suitable for HIV users than PrEP users. Privacy concerns suggest avoiding display of HIV-specific information. Suggested improvements include e.g. image uploads, drug interaction checks and prescription tracking. A total of 25 usability issues were identified in the TA test, with most found in the layout (n = 6), navigation (n = 5), interaction (n = 5), and terminology (n = 5) categories. Two examples are non-intuitive controls and illogical button placement. Despite these disadvantages, participants noted positive impressions (n = 5) in the satisfaction category. CONCLUSION: The study emphasizes the need for patient-centered design in mobile HIV care solutions, highlighting to the app's user-friendliness and potential to enhance care. Further research is necessary to refine the app's functionality and to align it with clinical and patients' privacy needs.

DistSNE: Distributed computing and online visualization of DNA methylation-based central nervous system tumor classification.

The current state-of-the-art analysis of central nervous system (CNS) tumors through DNA methylation profiling relies on the tumor classifier developed by Capper and colleagues, which centrally harnesses DNA methylation data provided by users. Here, we present a distributed-computing-based approach for CNS tumor classification that achieves a comparable performance to centralized systems while safeguarding privacy. We utilize the t-distributed neighborhood embedding (t-SNE) model for dimensionality reduction and visualization of tumor classification results in two-dimensional graphs in a distributed approach across multiple sites (DistSNE). DistSNE provides an intuitive web interface (https://gin-tsne.med.uni-giessen.de) for user-friendly local data management and federated methylome-based tumor classification calculations for multiple collaborators in a DataSHIELD environment. The freely accessible web interface supports convenient data upload, result review, and summary report generation. Importantly, increasing sample size as achieved through distributed access to additional datasets allows DistSNE to improve cluster analysis and enhance predictive power. Collectively, DistSNE enables a simple and fast classification of CNS tumors using large-scale methylation data from distributed sources, while maintaining the privacy and allowing easy and flexible network expansion to other institutes. This approach holds great potential for advancing human brain tumor classification and fostering collaborative precision medicine in neuro-oncology.

From rare events to systematic data collection: the RESCUED registry for sudden cardiac death in the young in Germany.

BACKGROUND: Approximately one-third of sudden cardiac deaths in the young (SCDY) occur due to a structural cardiac disease. Forty to fifty percent of SCDY cases remain unexplained after autopsy (including microscopic and forensic-toxicological analyses), suggesting arrhythmia syndromes as a possible cause of death. Due to the possible inheritability of these diseases, blood relatives of the deceased may equally be carriers of the causative genetic variations and therefore may have an increased cardiac risk profile. A better understanding of the forensic, clinical, and genetic data might help identify a subset of the general population that is at increased risk of sudden cardiac death. STUDY DESIGN: The German registry RESCUED (REgistry for Sudden Cardiac and UnExpected Death) comprises information about SCDY fatalities and clinical and genetic data of both the deceased and their biological relatives. The datasets collected in the RESCUED registry will allow for the identification of leading causes of SCDY in Germany and offer unique possibilities of scientific analyses with the aim of detecting unrecognized trends, risk factors, and clinical warning signs of SCDY. In a pilot phase of 24 months, approximately 180 SCDY cases (< 50 years of age) and 500 family members and clinical patients will be included. CONCLUSION: RESCUED is the first registry in Germany collecting comprehensive data of SCDY cases and clinical data of the biological relatives reviewed by cardiac experts. RESCUED aims to improve individual risk assessment and public health approaches by directing resources towards early diagnosis and evidence-based, personalized therapy and prevention in affected families. Trial registration number (TRN): DRKS00033543.

Diagnosis Support for Rare Diseases Using Phenotypic Profiles.

The common occurrence of characteristic symptoms can be used to infer diagnoses. The aim of this study is to show how syndrome similarity analysis using given phenotypic profiles can help in the diagnosis of rare diseases. HPO was used to map syndromes and phenotypic profiles. The system architecture described is planned to be implemented in a clinical decision support system for unclear diseases.

Machine translation of standardised medical terminology using natural language processing: A scoping review.

Standardised medical terminologies are used to ensure accurate and consistent communication of information and to facilitate data exchange. Currently, many terminologies are only available in English, which hinders international research and automated processing of medical data. Natural language processing (NLP) and Machine Translation (MT) methods can be used to automatically translate these terms. This scoping review examines the research on automated translation of standardised medical terminology. A search was performed in PubMed and Web of Science and results were screened for eligibility by title and abstract as well as full text screening. In addition to bibliographic data, the following data items were considered: 'terminology considered', 'terms considered', 'source language', 'target language', 'translation type', 'NLP technique', 'NLP system', 'machine translation system', 'data source' and 'translation quality'. The results showed that the most frequently translated terminology is SNOMED CT (39.1%), followed by MeSH (13%), ICD (13%) and UMLS (8.7%). The most common source language is English (55.9%), and the most common target language is German (41.2%). Translation methods are often based on Statistical Machine Translation (SMT) (41.7%) and, more recently, Neural Machine Translation (NMT) (30.6%), but can also be combined with various MT methods. Commercial translators such as Google Translate (36.4%) and automatic validation methods such as BLEU (22.2%) are frequently used tools for translation and subsequent validation.