Symptom checkers are increasingly used to assess new symptoms and navigate the health care system. The aim of this study was to compare the accuracy of an artificial intelligence (AI)-based symptom checker (Ada) and physicians regarding the presence/absence of an inflammatory rheumatic disease (IRD). In this survey study, German-speaking physicians with prior rheumatology working experience were asked to determine IRD presence/absence and suggest diagnoses for 20 different real-world patient vignettes, which included only basic health and symptom-related medical history. IRD detection rate and suggested diagnoses of participants and Ada were compared to the gold standard, the final rheumatologists’ diagnosis, reported on the discharge summary report. A total of 132 vignettes were completed by 33 physicians (mean rheumatology working experience 8.8 (SD 7.1) years). Ada’s diagnostic accuracy (IRD) was significantly higher compared to physicians (70 vs 54%, p = 0.002) according to top diagnosis. Ada listed the correct diagnosis more often compared to physicians (54 vs 32%, p < 0.001) as top diagnosis as well as among the top 3 diagnoses (59 vs 42%, p < 0.001). Work experience was not related to suggesting the correct diagnosis or IRD status. Confined to basic health and symptom-related medical history, the diagnostic accuracy of physicians was lower compared to an AI-based symptom checker. These results highlight the potential of using symptom checkers early during the patient journey and importance of access to complete and sufficient patient information to establish a correct diagnosis.

Background: Psoriasis is a chronic inflammatory skin disease. The visibility of erythematous plaques on the skin as well as the pain and itchiness caused by the skin lesions frequently leads to psychological distress in patients. Smartphone apps are widespread and easily accessible. Earlier studies have shown that apps can effectively complement current management strategies for patients with psoriasis. However, no analysis of such apps has been published to date. Objective: The aim of this study is to systematically identify and objectively assess the quality of current publicly available German apps for patients with psoriasis using the Mobile Application Rating Scale (MARS) and compile brief ready-to-use app descriptions. Methods: We conducted a systematic search and assessment of German apps for patients with psoriasis available in the Google Play Store and Apple App Store. The identified apps were randomly assigned to 1 of 3 reviewers, who independently rated them using the German MARS (MARS-G). The MARS-G includes 15 items from 4 different sections (engagement, functionality, aesthetics, and information) to create an overall mean score for every app. Scores can range from 1 for the lowest-quality apps to 5 for the highest-quality apps. Apps were ranked according to their mean MARS-G rating, and the highest-ranked app was evaluated independently by 2 patients with psoriasis using the user version of the MARS-G (uMARS-G). Furthermore, app information, including origin, main function, and technical aspects, was compiled into a brief overview. Results: In total, we were able to identify 95 unique apps for psoriasis, of which 15 were available in both app stores. Of these apps, 5 were not specifically intended for patients with psoriasis, 1 was designed for clinical trials only, and 1 was no longer available at the time the evaluation process began. Consequently, the remaining 8 apps were included in the final evaluation. The mean MARS-G scores ranged from 3.51 to 4.18. The app with the highest mean MARS-G score was Psoriasis Helferin (4.18/5.00). When rated by patients, however, the app was rated lower in all subcategories, resulting in a mean uMARS-G score of 3.48. Most apps had a commercial background and a focus on symptom tracking. However, only a fraction of the apps assessed used validated instruments to measure the user’s disease activity. Conclusions: App quality was heterogeneous, and only a minority of the identified apps were available in both app stores. When evaluated by patients, app ratings were lower than when evaluated by health care professionals. This discrepancy highlights the importance of involving patients when developing and evaluating health-related apps as the factors that make an app appealing to users may differ between these 2 groups. Trial Registration: Deutsches Register Klinischer Studien DRKS00020963; https://tinyurl.com/ye98an5b

EULAR highlighted the essential role of digital health in increasing self-management and improving clinical outcomes in patients with arthritis. The objective of this study was to evaluate the efficacy and safety of the digital health application (DHA) in patients with inflammatory arthritis. We assessed demographic parameters, treatment regimen, disease activity, and other patient-reported outcomes at baseline and after 4 weeks of DHA use added to standard care treatment. Of 17 patients, who completed the study, 7 (41.2%) patients were male, ranging from 19 to 63 (40.5 ± 12.2) years. No significant change in antirheumatic treatment was observed during the study. Statistically significant improvements (p < 0.05) were noted for health-related quality of life (increase in Physical Component Summary of Short Form-36 (SF-36) by 23.6%) and disease activity (decrease of Clinical Disease Activity Index and Simple Disease Activity Index by 38.4% and 39.9%, respectively). Clinically significant improvement was demonstrated for SF-36 Total Score (+ 14.4%), disease activity (Rheumatoid Arthritis Disease Activity Index− 5 to 15.9%), and depression (Patient Health Questionnaire− 9 to 13.5%). None of the efficacy parameters showed negative trends. No adverse events were reported throughout the study. The usability level was high i.e., the mean mHealth Application Usability Questionnaire Score of 5.96 (max.: 7.0) demonstrated a high level of application usability. This suggests that using a personalized disease management program based on DHA significantly improves several measures of patient-reported outcomes and disease activity in patients with inflammatory arthritis in a timely manner. These findings highlight the potential of complementary digital therapy in patients with inflammatory arthritis.

Idiopathic inflammatory myopathies (IIMs), or myositis, are rare diseases marked by immune-driven muscle damage and complications like skin lesions and interstitial lung disease (ILD). Despite advances, challenges in diagnosis and treatment persist, particularly in inclusion body myositis (IBM), where no effective therapy exists. Recent breakthroughs, including transcriptomics and insights into antibody-mediated immunity and interferon (IFN) signaling, have clarified IIM pathophysiology and spurred the development of new therapies, such as chimeric antigen receptor (CAR) T cells and Janus kinase (JAK) inhibitors. We explore the latest findings on the mechanisms underlying adult-onset IIMs, emphasizing IBM pathobiology and its unique immune and degenerative pathways, such as a selective type 2 myofiber damage and severe cell stress. Finally, we highlight the recent advances in transcriptomics, single-cell analysis, and machine learning in transforming IIM research by improving diagnostic accuracy, uncovering therapeutic targets, and supporting the development of personalized treatment strategies.

Background: Mobile applications (apps) are a resource for information on lifestyle and nutrition which are associated to improved outcomes in inflammatory arthritis. Objective: The aim of this study was to explore whether targeted lifestyle counselling via an app improves disease activity in arthritis patients. Methods: Patients with rheumatoid arthritis (RA), spondyloarthritis (SpA), psoriatic arthritis (PsA) were randomized to 12 weeks of lifestyle counselling via an app (Mida, Midaia GmbH, Germany) pertaining to a healthy Mediterranean Diet, physical activity, and mental health. Disease activity was measured with specific instruments by a blinded physician and categorized (remission, low, moderate, high). Dietary adherence was assessed by the Mediterranean Diet Adherence Screener (MEDAS). Mixed effects logistic regression adjusted to baseline disease activity, age, and sex were calculated. Results: Of 158 patients included (73% female, 53.3 ± 11.7 years), 74 were in the active counselling group (ACG). All showed improvement in low disease activity or remission. ACG patients had an odds ratio (OR) of 2.8 (95%-CI 1.1–7.2, p = 0.035), while OR in the control group was not significant OR = 2.1 (0.9–5.0, p = 0.097). The control group was less likely to reach a MEDAS >= 4 (OR = 0.16 (0.03–0.77), p = 0.02), while this was not seen in the ACG (OR = 0.54 (0.06–4.63), p = 0.6). Patients in the ACG showed a tendency towards improved adhesion to a Mediterranean Diet (MEDAS) (β = 0.35 (−0.05–0.74), p = 0.086). This tendency was not observed in the control group (β = 0.09 (−0.29–0.46), p = 0.64). Conclusions: Individualized lifestyle and dietary counselling via app may help to improve disease control in inflammatory arthritis patients.