#Covid4Rheum: an analytical twitter study in the time of the COVID-19 pandemic

Social media services, such as Twitter, offer great potential for a better understanding of rheumatic and musculoskeletal disorders (RMDs) and improved care in the field of rheumatology. This study examined the content and stakeholders associated with the Twitter hashtag #Covid4Rheum during the COVID-19 pandemic. The content analysis shows that Twitter connects stakeholders of the rheumatology community on a global level, reaching millions of users. Specifically, the use of hashtags on Twitter assists digital crowdsourcing projects and scientific collaboration, as exemplified by the COVID-19 Global Rheumatology Alliance registry. Moreover, Twitter facilitates the distribution of scientific content, such as guidelines or publications. Finally, digital data mining enables the identification of hot topics within the field of rheumatology

Reply to the comment on “Accuracy and usability of a diagnostic decision support system in the diagnosis of three representative rheumatic diseases: a randomized controlled trial among medical students”

With great interest, we read the comment by Gilbert and Wicks on our recent publication [1] testing the accuracy and usability of Ada’s symptom checker among medical students

#Covid4Rheum: an analytical twitter study in the time of the COVID-19 pandemic

Social media services, such as Twitter, offer great potential for a better understanding of rheumatic and musculoskeletal disorders (RMDs) and improved care in the field of rheumatology. This study examined the content and stakeholders associated with the Twitter hashtag #Covid4Rheum during the COVID-19 pandemic. The content analysis shows that Twitter connects stakeholders of the rheumatology community on a global level, reaching millions of users. Specifically, the use of hashtags on Twitter assists digital crowdsourcing projects and scientific collaboration, as exemplified by the COVID-19 Global Rheumatology Alliance registry. Moreover, Twitter facilitates the distribution of scientific content, such as guidelines or publications. Finally, digital data mining enables the identification of hot topics within the field of rheumatology

Social media in myositis care - an exploratory mixed-methods study among myositis patients (SociMyo)

Myositis is a rare autoimmune disease primarily affecting muscles, with potential involvement of the skin, heart, and lungs. Patients often experience delays in diagnosis, lack of adequate information, and limited support for disease management. Social media has emerged as a valuable tool to address these gaps by facilitating information exchange, peer support, and community building. However, its role in myositis care is not yet well understood. This study aims to explore how myositis patients use social media, focusing on shared content, perceived benefits and challenges, and the overall impact on disease management and emotional well-being. A mixed-methods approach was applied, including semi-structured interviews with 11 patients and a netnographic analysis of social media group dedicated to myositis care. Data were analyzed using Kuckartz's structured qualitative content analysis, with coding performed inductively, to identify key themes. Four key themes emerged: (I) Social media as a global platform for sharing experiential knowledge, particularly on symptom management, medication side effects, and coping strategies. (II) Peer support fostering a sense of belonging, emotional exchange, and mutual encouragement through structured discussions and community-driven moderation. (III) Perceived benefits, such as real-time access to patient-driven insights, shared decision-making support, and enhanced communication with healthcare providers. (IV) Perceived drawbacks, including misinformation, privacy concerns, and the absence of professional medical input. Participants emphasized the need for expert involvement to improve content reliability, while also valuing the autonomy and emotional support within these communities. Social media platforms, particularly closed groups, provide a complementary avenue to traditional care by offering support and knowledge exchange. To maximize their potential, privacy concerns and the integration of professional guidance must be addressed.</p

Apps und ihre Anwendungsgebiete in der Rheumatologie

Zusammenfassung Mit der steigenden Verwendung von Smartphones einhergehend, nimmt auch die Nutzung von mobilen Applikationen (Apps) rapide zu. Im medizinischen Kontext könnten chronisch kranke Patienten von dem Einsatz dauerhaft profitieren. Verstärkt wird diese Entwicklung durch das Digitale-Versorgung-Gesetz (DVG), wonach Patienten ab Q4/2020 einen Rechtsanspruch auf bestimmte Apps, sog. digitale Gesundheitsanwendungen (DiGAs), haben, die von den gesetzlichen Krankenkassen erstattet werden. Besonders im Bereich der Rheumatologie bieten sich für das Management chronischer Erkrankungen und ihrer Komorbiditäten verschiedene Anknüpfungspunkte. Nicht nur unter rheumatologischen Patienten ist das Interesse an App-Angeboten groß, sondern auch unter deutschen Rheumatologen zeigt sich eine steigende Bereitschaft, Apps im Berufsalltag anzuwenden und Patienten zu empfehlen. Dieser Artikel will einen Überblick über die Entwicklung der App-Landschaft in der deutschsprachigen Rheumatologie vermitteln

Diagnostic accuracy of a large language model in rheumatology: comparison of physician and ChatGPT-4

Pre-clinical studies suggest that large language models (i.e., ChatGPT) could be used in the diagnostic process to distinguish inflammatory rheumatic (IRD) from other diseases. We therefore aimed to assess the diagnostic accuracy of ChatGPT-4 in comparison to rheumatologists. For the analysis, the data set of Gräf et al. (2022) was used. Previous patient assessments were analyzed using ChatGPT-4 and compared to rheumatologists’ assessments. ChatGPT-4 listed the correct diagnosis comparable often to rheumatologists as the top diagnosis 35% vs 39% ( p  = 0.30); as well as among the top 3 diagnoses, 60% vs 55%, ( p  = 0.38). In IRD-positive cases, ChatGPT-4 provided the top diagnosis in 71% vs 62% in the rheumatologists’ analysis. Correct diagnosis was among the top 3 in 86% (ChatGPT-4) vs 74% (rheumatologists). In non-IRD cases, ChatGPT-4 provided the correct top diagnosis in 15% vs 27% in the rheumatologists’ analysis. Correct diagnosis was among the top 3 in non-IRD cases in 46% of the ChatGPT-4 group vs 45% in the rheumatologists group. If only the first suggestion for diagnosis was considered, ChatGPT-4 correctly classified 58% of cases as IRD compared to 56% of the rheumatologists ( p  = 0.52). ChatGPT-4 showed a slightly higher accuracy for the top 3 overall diagnoses compared to rheumatologist’s assessment. ChatGPT-4 was able to provide the correct differential diagnosis in a relevant number of cases and achieved better sensitivity to detect IRDs than rheumatologist, at the cost of lower specificity. The pilot results highlight the potential of this new technology as a triage tool for the diagnosis of IRD.Open Access funding enabled and organized by Projekt DEAL.Universitätsklinikum Hamburg-Eppendorf (UKE) (5411

Telemedizin in der Rheumatologie

Zusammenfassung Der Ausbruch der COVID-19-Pandemie geht mit tief greifenden Einschnitten im Alltag und im Berufsleben einher – sowohl gesamtgesellschaftlich als auch speziell im Gesundheitswesen. Im Fokus der Pandemieeindämmung haben sich vielerorts rheumatologische Routineabläufe verändert. Um den entsprechenden Infektionsschutz der Patienten und des medizinischen Personals gewährleisten zu können, wurde hier verstärkt Telemedizin (insbesondere Telefon- und Videosprechstunde) eingesetzt. Weiterhin stehen durch die Digitale-Gesundheitsanwendungen-Verordnung (DiGAV) voraussichtlich in den kommenden Monaten neue, abrechnungsfähige telemedizinische Anwendungsmöglichkeiten wie Apps und Wearables zur Verfügung. Der Artikel soll einen Überblick über telemedizinische Versorgungsmöglichkeiten in der Rheumatologie (mit besonderem Fokus auf die Videosprechstunde) geben. Weiterhin wird Bezug auf die vorhandene Evidenzlage sowie Chancen und Limitation der Telemedizin im Fachgebiet genommen

Toward digitally supported self-assessment of patients with idiopathic inflammatory myopathies

BACKGROUND: Manual muscle testing (MMT8), the current gold standard for assessing muscle function in patients with idiopathic inflammatory myopathies (IIM), has notable limitations. This study had three aims (1) to compare MMT8 with inertial sensor-based gait analysis, (2) to evaluate patient-performed functional tests guided by shared decision-making (SDM), and (3) to investigate adherence to electronic patient-reported outcomes (ePROs).METHODS: Gold standard muscle function assessment (MMT8) was performed at baseline (T0) and three months (T1). Additionally, inertial-sensor-based gait analysis was completed at T0 and two standardized upper extremity (Modified Barré test; 10-time arm lift test) and two lower extremity muscle endurance tests (60-second Sit-to-Stand (STS) test; Mingazzini test) were presented to patients to choose from. Through shared decision-making, each patient selected one test for lower and upper extremities and opted to record weekly results on paper or through a medical app. Correlations between gait parameters, functional tests, and MMT8 were analyzed, while agreement between patient- and healthcare professional (HCP)-recorded results at T0 and T1 was assessed. Responsiveness to change was also evaluated.RESULTS: A total of 28 IIM patients (67.9% female; mean age 57.4 ± 12.9 years) were enrolled. Moderate correlations were observed between gait parameters and MMT8, such as walking speed (r = 0.545, p = 0.004) and stride length (r = 0.580, p = 0.002). All patients selected the Modified Barré test for assessing upper extremity function and 60.7% of patients chose the Mingazzini test for lower extremity function. Agreement between patient- and HCP-recorded functional test results was excellent at baseline and after three months (ICC 0.99-1.00). Functional tests demonstrated strong correlations with MMT8, particularly for the Mingazzini test (r = 0.762, p = 0.002). Patients preferred app-based recording (82.1%) over paper-based methods and weekly ePROs were completed on average 6.9 out of 12 weeks (57.5%).CONCLUSION: Patient-performed functional tests are reliable, scalable alternatives to MMT8, with gait analysis providing complementary insights. Digitally supported self-assessments can enhance clinical workflows, remote monitoring, and treat-to-target strategies, empowering patients and improving disease management.</p