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  • 1
    Online Resource
    Online Resource
    Biomechanical stress in the context of competitive sports training triggers enthesitis
    Springer Science and Business Media LLC ; 2021
    In:  Arthritis Research & Therapy Vol. 23, No. 1 ( 2021-12)
    Details
    In: Arthritis Research & Therapy, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2021-12)
    Abstract: To evaluate the influence of mechanical stress on the development of immediate enthesitis. Methods The BEAT study is an interventional study that assessed entheses in competitive badminton players before and immediately after a 60-min intensive training session. Power Doppler (PD) signal and Gray scale (GS) changes were assessed in the insertion sites of both Achilles tendon, patellar tendons, and lateral humeral epicondyles and quantified using a validated scoring system. Results Thirty-two badminton players were included. One hundred ninety-two entheseal sites were examined twice. The respective empirical total scores for PD examination were 0.1 (0.3) before and 0.5 (0.9) after training. Mean total GS scores were 2.9 (2.5) and 3.1 (2.5) before and after training, respectively. The mean total PD score difference of 0.4 between pre- and post-training was significant ( p = 0.0014), whereas no significant difference for the mean total GS score was observed. Overall, seven participants (22%) showed an increased empirical total PD score. A mixed effects model showed a significant increase of PD scores after training, with a mean increase per site of 0.06 (95% CI 0.01 to 0.12, p = 0.017). Conclusions Mechanical stress leads to rapid inflammatory responses in the entheseal structures of humans. These data support the concept of mechanoinflammation in diseases associated with enthesitis.
    Type of Medium: Online Resource
    ISSN: 1478-6362
    URL: Article
    DOI: 10.1186/s13075-021-02530-x
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2041668-4
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  • 2
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    Effect of disease-modifying anti-rheumatic drugs on bone structure and strength in psoriatic arthritis patients
    Springer Science and Business Media LLC ; 2019
    In:  Arthritis Research & Therapy Vol. 21, No. 1 ( 2019-12)
    Details
    In: Arthritis Research & Therapy, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2019-12)
    Type of Medium: Online Resource
    ISSN: 1478-6362
    URL: Article
    DOI: 10.1186/s13075-019-1938-3
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2041668-4
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  • 3
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    Advanced machine learning for predicting individual risk of flares in rheumatoid arthritis patients tapering biologic drugs
    Springer Science and Business Media LLC ; 2021
    In:  Arthritis Research & Therapy Vol. 23, No. 1 ( 2021-12)
    Details
    In: Arthritis Research & Therapy, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2021-12)
    Abstract: Biological disease-modifying anti-rheumatic drugs (bDMARDs) can be tapered in some rheumatoid arthritis (RA) patients in sustained remission. The purpose of this study was to assess the feasibility of building a model to estimate the individual flare probability in RA patients tapering bDMARDs using machine learning methods. Methods Longitudinal clinical data of RA patients on bDMARDs from a randomized controlled trial of treatment withdrawal (RETRO) were used to build a predictive model to estimate the probability of a flare. Four basic machine learning models were trained, and their predictions were additionally combined to train an ensemble learning method, a stacking meta-classifier model to predict the individual flare probability within 14 weeks after each visit. Prediction performance was estimated using nested cross-validation as the area under the receiver operating curve (AUROC). Predictor importance was estimated using the permutation importance approach. Results Data of 135 visits from 41 patients were included. A model selection approach based on nested cross-validation was implemented to find the most suitable modeling formalism for the flare prediction task as well as the optimal model hyper-parameters. Moreover, an approach based on stacking different classifiers was successfully applied to create a powerful and flexible prediction model with the final measured AUROC of 0.81 (95%CI 0.73–0.89). The percent dose change of bDMARDs, clinical disease activity (DAS-28 ESR), disease duration, and inflammatory markers were the most important predictors of a flare. Conclusion Machine learning methods were deemed feasible to predict flares after tapering bDMARDs in RA patients in sustained remission.
    Type of Medium: Online Resource
    ISSN: 1478-6362
    URL: Article
    DOI: 10.1186/s13075-021-02439-5
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2041668-4
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  • 4
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    Accuracy and usability of a diagnostic decision support system in the diagnosis of three representative rheumatic diseases: a randomized controlled trial among medical students
    Springer Science and Business Media LLC ; 2021
    In:  Arthritis Research & Therapy Vol. 23, No. 1 ( 2021-12)
    Details
    In: Arthritis Research & Therapy, Springer Science and Business Media LLC, Vol. 23, No. 1 ( 2021-12)
    Abstract: An increasing number of diagnostic decision support systems (DDSS) exist to support patients and physicians in establishing the correct diagnosis as early as possible. However, little evidence exists that supports the effectiveness of these DDSS. The objectives were to compare the diagnostic accuracy of medical students, with and without the use of a DDSS, and the diagnostic accuracy of the DDSS system itself, regarding the typical rheumatic diseases and to analyze the user experience. Methods A total of 102 medical students were openly recruited from a university hospital and randomized (unblinded) to a control group (CG) and an intervention group (IG) that used a DDSS (Ada – Your Health Guide) to create an ordered diagnostic hypotheses list for three rheumatic case vignettes. Diagnostic accuracy, measured as the presence of the correct diagnosis first or at all on the hypothesis list, was the main outcome measure and evaluated for CG, IG, and DDSS. Results The correct diagnosis was ranked first (or was present at all) in CG, IG, and DDSS in 37% (40%), 47% (55%), and 29% (43%) for the first case; 87% (94%), 84% (100%), and 51% (98%) in the second case; and 35% (59%), 20% (51%), and 4% (51%) in the third case, respectively. No significant benefit of using the DDDS could be observed. In a substantial number of situations, the mean probabilities reported by the DDSS for incorrect diagnoses were actually higher than for correct diagnoses, and students accepted false DDSS diagnostic suggestions. DDSS symptom entry greatly varied and was often incomplete or false. No significant correlation between the number of symptoms extracted and diagnostic accuracy was seen. It took on average 7 min longer to solve a case using the DDSS. In IG, 61% of students compared to 90% in CG stated that they could imagine using the DDSS in their future clinical work life. Conclusions The diagnostic accuracy of medical students was superior to the DDSS, and its usage did not significantly improve students’ diagnostic accuracy. DDSS usage was time-consuming and may be misleading due to prompting wrong diagnoses and probabilities. Trial registration DRKS.de, DRKS00024433 . Retrospectively registered on February 5, 2021.
    Type of Medium: Online Resource
    ISSN: 1478-6362
    URL: Article
    DOI: 10.1186/s13075-021-02616-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2041668-4
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  • 5
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    Accuracy and tolerability of self-sampling of capillary blood for analysis of inflammation and autoantibodies in rheumatoid arthritis patients—results from a randomized controlled trial
    Springer Science and Business Media LLC ; 2022
    In:  Arthritis Research & Therapy Vol. 24, No. 1 ( 2022-12)
    Details
    In: Arthritis Research & Therapy, Springer Science and Business Media LLC, Vol. 24, No. 1 ( 2022-12)
    Abstract: Rheumatoid arthritis (RA) requires early diagnosis and tight surveillance of disease activity. Remote self-collection of blood for the analysis of inflammation markers and autoantibodies could improve the monitoring of RA and facilitate the identification of individuals at-risk for RA. Objective Randomized, controlled trial to evaluate the accuracy, feasibility, and acceptability of an upper arm self-sampling device (UA) and finger prick-test (FP) to measure capillary blood from RA patients for C-reactive protein (CRP) levels and the presence of IgM rheumatoid factor (RF IgM) and anti-cyclic citrullinated protein antibodies (anti-CCP IgG). Methods RA patients were randomly assigned in a 1:1 ratio to self-collection of capillary blood via UA or FP. Venous blood sampling (VBS) was performed as a gold standard in both groups to assess the concordance of CRP levels as well as RF IgM and CCP IgG. General acceptability and pain during sampling were measured and compared between UA, FP, and VBS. The number of attempts for successful sampling, requests for assistance, volume, and duration of sample collection were also assessed. Results Fifty seropositive RA patients were included. 49/50 (98%) patients were able to successfully collect capillary blood. The overall agreement between capillary and venous analyses for CRP (0.992), CCP IgG (0.984), and RF IgM (0.994) were good. In both groups, 4/25 (16%) needed a second attempt and 8/25 (32%) in the UA and 7/25 (28%) in the FP group requested assistance. Mean pain scores for capillary self-sampling (1.7/10 ± 1.1 (UA) and 1.9/10 ± 1.9 (FP)) were significantly lower on a numeric rating scale compared to venous blood collection (UA: 2.8/10 ± 1.7; FP: 2.1 ± 2.0) ( p =0.003). UA patients were more likely to promote the use of capillary blood sampling (net promoter score: +28% vs. −20% for FP) and were more willing to perform blood collection at home (60% vs. 32% for FP). Conclusions These data show that self-sampling is accurate and feasible within one attempt by the majority of patients without assistance, allowing tight monitoring of RA disease activity as well as identifying individuals at-risk for RA. RA patients seem to prefer upper arm-based self-sampling to traditional finger pricking. Trial registration DRKS.de Identifier: DRKS00023526 . Registered on November 6, 2020.
    Type of Medium: Online Resource
    ISSN: 1478-6362
    URL: Article
    DOI: 10.1186/s13075-022-02809-7
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 2041668-4
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  • 6
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    Comparison of physician and artificial intelligence-based symptom checker diagnostic accuracy
    Springer Science and Business Media LLC ; 2022
    In:  Rheumatology International Vol. 42, No. 12 ( 2022-09-10), p. 2167-2176
    Details
    In: Rheumatology International, Springer Science and Business Media LLC, Vol. 42, No. 12 ( 2022-09-10), p. 2167-2176
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 1437-160X
    URL: Article
    DOI: 10.1007/s00296-022-05202-4
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 1464208-6
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  • 7
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    Image_1.PNG
    Frontiers Media SA ; 2021
    In:  Frontiers in Medicine Vol. 8 ( 2021-7-22)
    Details
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 8 ( 2021-7-22)
    Abstract: Introduction: Mobile applications promise to improve current health care. However, current mobile app quality ratings are mostly physician-based. The aim of this study was (1) to assess the quality of the self-management app Rheuma Auszeit using the validated uMARS (User Version of the Mobile App Rating Scale) app quality assessment tool and (2) to evaluate the association between uMARS scores and patients' characteristics. Materials and Methods: Consecutive patients with rheumatoid arthritis, psoriatic arthritis and spondyloarthritis were seen at the rheumatology clinic at university hospital Erlangen, Germany. They were asked to test Rheuma Auszeit, evaluate its quality using uMARS and complete a paper-based survey evaluating the individual preferences, attitudes and ehealth literacy. The association between uMARS scores and patients' characteristics was further explored. Results: Between December 2018 and January 2019, a total of 126 patients evaluated Rheuma Auszeit using uMARS and filled out the paper-based survey. The median uMARS score was 3.9, IQR 0.7. Functionality was the domain with the highest rating (median 4.8, IQR 0.8), followed by aesthetics (median 4.0, IQR 0.7), information (median 3.5, IQR 0.8), and engagement (median 3.2, IQR 1.0). Subjective quality was average (median 3.0, IQR 1.0). The lowest scoring individual item was customization with a median of 2.5/5. Lower functionality scores were reported among older female rheumatic patients ( P & lt; 0.004). Older male rheumatic patients reported a higher subjective quality score ( P & lt; 0.024). Perceived disease activity and disease duration did not significantly correlate with any uMARS subdomain scores. eHealth literacy significantly correlated with functionality uMARS subdomain ratings (Rho = 0.18; P & lt; 0.042). Preferred time of app usage significantly correlated with engagement (Rho = 0.20; P & lt; 0.024), functionality (Rho = 0.19; P & lt; 0.029), total uMARS score (Rho = 0.21; P & lt; 0.017) and subjective quality score (Rho = 0.21; P & lt; 0.017). The vast majority of rheumatic patients would consider recommending Rheuma Auszeit to other patients (117/126; 92.9%). Conclusion: Rheuma Auszeit was well-accepted by German patients suffering from rheumatoid arthritis, psoriatic arthritis and ankylosing spondyloarthritis. Lacking customization could lead to low app compliance and should be improved. Lower functionality scores among older female rheumatic patients highlight the need for patient education. The study underlines the potential and feasibility of therapeutic complementary digital solutions in rheumatology.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    URL: Article
    URL: Article
    DOI: 10.3389/fmed.2021.715345
    DOI: 10.3389/fmed.2021.715345.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2775999-4
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  • 8
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    Data_Sheet_1.PDF
    Frontiers Media SA ; 2022
    In:  Frontiers in Public Health Vol. 10 ( 2022-10-14)
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    In: Frontiers in Public Health, Frontiers Media SA, Vol. 10 ( 2022-10-14)
    Abstract: Being able to independently determine vaccine induced antibody responses by minimal-invasive methods is of great interest to enable a flexible and effective vaccination strategy. This study aimed to evaluate (1) the accuracy, feasibility, usability and acceptability of capillary blood and saliva self-sampling to determine SARS-CoV-2 antibody responses in patients with immune-mediated inflammatory diseases (IMIDs) and health professionals (HP). Methods IMID patients and HP having received two doses of SARS-CoV-2 vaccines, self-collected capillary blood (Tasso+) and saliva samples. Capillary samples were considered interchangeable with venous blood if three criteria were met: Spearman's correlation coefficient (r) & gt; 0.8, non-significant Wilcoxon signed-rank test (i.e., p & gt; 0.05), and a small bias or 95% of tests within 10% difference through Bland-Altman. Participants completed a survey to investigate self-sampling usability (system usability scale; SUS) and acceptability (net promoter score; NPS). Study personnel monitored correct self-sampling completion and recorded protocol deviations. Results 60 participants (30 IMID patients and 30 HP) were analyzed. We observed interchangeability for capillary samples with an accuracy of 98.3/100% for Anti-SARS-CoV-2 IgG/IgA antibodies, respectively. Fifty-eight capillary blood samples and all 60 saliva samples were successfully collected within the first attempt. Usability of both self-sampling procedures was rated as excellent, with significantly higher saliva ratings ( p & lt; 0.001). Capillary self-sampling was perceived as significantly ( p & lt; 0.001) less painful compared to traditional venous blood collection. Participants reported a NPS for capillary and saliva self-sampling of +68% and +63%, respectively. The majority of both groups (73%) preferred capillary self-sampling over professional venous blood collection. Conclusion Our results indicate that capillary self-sampling is accurate, feasible and preferred over conventional venous blood collection. Implementation could enable easy access, flexible vaccination monitoring, potentially leading to a better protection of vulnerable patient groups. Self-collection of saliva is feasible and safe however more work is needed to determine its application in clinical practice.
    Type of Medium: Online Resource
    ISSN: 2296-2565
    URL: Article
    URL: Article
    DOI: 10.3389/fpubh.2022.994770
    DOI: 10.3389/fpubh.2022.994770.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2711781-9
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  • 9
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    Table_1.DOCX
    Frontiers Media SA ; 2022
    In:  Frontiers in Medicine Vol. 9 ( 2022-7-22)
    Details
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 9 ( 2022-7-22)
    Abstract: Rheport is an online rheumatology referral system allowing automatic appointment triaging of new rheumatology patient referrals according to the respective probability of an inflammatory rheumatic disease (IRD). Previous research reported that Rheport was well accepted among IRD patients. Its accuracy was, however, limited, currently being based on an expert-based weighted sum score. This study aimed to evaluate whether machine learning (ML) models could improve this limited accuracy. Materials and methods Data from a national rheumatology registry (RHADAR) was used to train and test nine different ML models to correctly classify IRD patients. Diagnostic performance was compared of ML models and the current algorithm was compared using the area under the receiver operating curve (AUROC). Feature importance was investigated using shapley additive explanation (SHAP). Results A complete data set of 2265 patients was used to train and test ML models. 30.5% of patients were diagnosed with an IRD, 69.3% were female. The diagnostic accuracy of the current Rheport algorithm (AUROC of 0.534) could be improved with all ML models, (AUROC ranging between 0.630 and 0.737). Targeting a sensitivity of 90%, the logistic regression model could double current specificity (17% vs. 33%). Finger joint pain, inflammatory marker levels, psoriasis, symptom duration and female sex were the five most important features of the best performing logistic regression model for IRD classification. Conclusion In summary, ML could improve the accuracy of a currently used rheumatology online referral system. Including further laboratory parameters and enabling individual feature importance adaption could increase accuracy and lead to broader usage.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    URL: Article
    URL: Article
    DOI: 10.3389/fmed.2022.954056
    DOI: 10.3389/fmed.2022.954056.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2775999-4
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  • 10
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    Early Changes of the Cortical Micro‐Channel System in the Bare Area of the Joints of Patients With Rheumatoid Arthritis
    Wiley ; 2017
    In:  Arthritis & Rheumatology Vol. 69, No. 8 ( 2017-08), p. 1580-1587
    Details
    In: Arthritis & Rheumatology, Wiley, Vol. 69, No. 8 ( 2017-08), p. 1580-1587
    Abstract: To characterize the specific structural properties of the erosion‐prone bare area of the human joint, and to search for early microstructural changes in this region during rheumatoid arthritis (RA). Methods In the initial part of the study, human cadaveric hand joints were examined for exact localization of the bare area of the metacarpal heads, followed by detection of cortical micro‐channels (CoMiCs) in this region by high‐resolution peripheral quantitative computed tomography (HR‐pQCT) and, after anatomic dissection, validation of the presence of CoMiCs by micro–computed tomography (micro‐CT). In the second part of the study, the number and distribution of CoMiCs were analyzed in 107 RA patients compared to 105 healthy individuals of similar age and sex distribution. Results Investigation by HR‐pQCT combined with adaptive thresholding allowed the detection of CoMiCs in the bare area of human cadaveric joints. The existence of CoMiCs in the bare area was additionally validated by micro‐CT. In healthy individuals, the number of CoMiCs increased with age. RA patients showed significantly more CoMiCs compared to healthy individuals (mean ± SD 112.9 ± 54.7/joint versus 75.2 ± 41.9/joint; P   〈  0.001), with 20–49‐year‐old RA patients exhibiting similar numbers of CoMiCs as observed in healthy individuals older than age 65 years. Importantly, CoMiCs were already found in RA patients very early in their disease course, with enrichment in the erosion‐prone radial side of the joint. Conclusion CoMiCs represent a new form of structural change in the joints of patients with RA. Although the number of CoMiCs increases with age, RA patients develop CoMiCs much earlier in life, and such changes can even occur at the onset of the disease. CoMiCs therefore represent an interesting new opportunity to assess structural changes in RA.
    Type of Medium: Online Resource
    ISSN: 2326-5191 , 2326-5205
    URL: Issue
    URL: Article
    DOI: 10.1002/art.v69.8
    DOI: 10.1002/art.40148
    RVK:
    XA 10000
    RVK:
    XA 30325
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2754614-7
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