Publications by authors named "Johannes Knitza"

25 Publications

  • Page 1 of 1

A Real-World Rheumatology Registry and Research Consortium: The German RheumaDatenRhePort (RHADAR) Registry.

J Med Internet Res 2021 May 20;23(5):e28164. Epub 2021 May 20.

see Acknowledgments, .

Real-world data are crucial to continuously improve the management of patients with rheumatic and musculoskeletal diseases (RMDs). The German RheumaDatenRhePort (RHADAR) registry encompasses a network of rheumatologists and researchers in Germany providing pseudonymized real-world patient data and allowing timely and continuous improvement in the care of RMD patients. The RHADAR modules allow automated anamnesis and adaptive coordination of appointments regarding individual urgency levels. Further modules focus on the collection and integration of electronic patient-reported outcomes in between consultations. The digital RHADAR modules ultimately allow a patient-centered adaptive approach to integrated medical care starting as early as possible in the disease course. Such a closed-loop system consisting of various modules along the whole patient pathway enables comprehensive and timely patient management in an unprecedented manner.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/28164DOI Listing
May 2021

A Virtual Reality-Based App to Educate Health Care Professionals and Medical Students About Inflammatory Arthritis: Feasibility Study.

JMIR Serious Games 2021 May 11;9(2):e23835. Epub 2021 May 11.

Department of Internal Medicine 3, Rheumatology and Immunology, Friedrich-Alexander University Erlangen-Nuremberg and Universitätsklinikum Erlangen, Erlangen, Germany.

Background: Inflammatory arthritides (IA) such as rheumatoid arthritis or psoriatic arthritis are disorders that can be difficult to comprehend for health professionals and students in terms of the heterogeneity of clinical symptoms and pathologies. New didactic approaches using innovative technologies such as virtual reality (VR) apps could be helpful to demonstrate disease manifestations as well as joint pathologies in a more comprehensive manner. However, the potential of using a VR education concept in IA has not yet been evaluated.

Objective: We evaluated the feasibility of a VR app to educate health care professionals and medical students about IA.

Methods: We developed a VR app using data from IA patients as well as 2D and 3D-visualized pathological joints from X-ray and computed tomography-generated images. This VR app (Rheumality) allows the user to interact with representative arthritic joint and bone pathologies of patients with IA. In a consensus meeting, an online questionnaire was designed to collect basic demographic data (age, sex); profession of the participants; and their feedback on the general impression, knowledge gain, and potential areas of application of the VR app. The VR app was subsequently tested and evaluated by health care professionals (physicians, researchers, and other professionals) and medical students at predefined events (two annual rheumatology conferences and academic teaching seminars at two sites in Germany). To explore associations between categorical variables, the χ or Fisher test was used as appropriate. Two-sided P values ≤.05 were regarded as significant.

Results: A total of 125 individuals participated in this study. Among them, 56% of the participants identified as female, 43% identified as male, and 1% identified as nonbinary; 59% of the participants were 18-30 years of age, 18% were 31-40 years old, 10% were 41-50 years old, 8% were 51-60 years old, and 5% were 61-70 years old. The participants (N=125) rated the VR app as excellent, with a mean rating of 9.0 (SD 1.2) out of 10, and many participants would recommend use of the app, with a mean recommendation score of 3.2 (SD 1.1) out of 4. A large majority (120/125, 96.0%) stated that the presentation of pathological bone formation improves understanding of the disease. We did not find any association between participant characteristics and evaluation of the VR experience or recommendation scores.

Conclusions: The data show that IA-targeting innovative teaching approaches based on VR technology are feasible.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/23835DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8150404PMC
May 2021

[Annual meeting of the German Society for Rheumatology going virtual-successfully defying the pandemic].

Z Rheumatol 2021 Jun 20;80(5):399-407. Epub 2021 Apr 20.

Klinik für Rheumatologie & Klinische Immunologie, Evangelisches Krankenhaus, Kliniken Essen-Mitte, Essen, Deutschland.

Background: In 2020 the COVID-19 pandemic led to the annual meeting of the German Society for Rheumatology (DGRh) being conducted as the virtual German Rheumatology Congress.

Aim: How is the virtual German Rheumatology Congress accepted and what are the possibilities of optimization for the future?

Material And Method: The registered participants were asked to take part in an online congress evaluation.

Results: Of 2566 congress attendees, 721 participated in the evaluation. The majority (80.2%) were (very) satisfied with the event overall. Compared to the traditional format collegial exchange was perceived as worse using the virtual approach. The technology platform was predominantly described as easy to use and easily accessible. The selected topics of the congress met the expectations of 89% of the participants. The presented contents were estimated to be relevant for their professional activities by 85.2% of the participants. The majority of participants (85.3%) would welcome the congress contents to be permanently available on demand.

Discussion: Overall, the participants appreciated the virtual format of the German Rheumatology Congress. Optimization aspects could be shown and these could be considered in the implementation of further (digital) congresses. The results of this work provide suggestions for improvement on how the DGRh can meet and exceed the needs of participants in organizing a virtual or hybrid conference in the future.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00393-021-00997-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055747PMC
June 2021

Accuracy, patient-perceived usability, and acceptance of two symptom checkers (Ada and Rheport) in rheumatology: interim results from a randomized controlled crossover trial.

Arthritis Res Ther 2021 04 13;23(1):112. Epub 2021 Apr 13.

RheumaDatenRhePort (rhadar), Planegg, Germany.

Background: Timely diagnosis and treatment are essential in the effective management of inflammatory rheumatic diseases (IRDs). Symptom checkers (SCs) promise to accelerate diagnosis, reduce misdiagnoses, and guide patients more effectively through the health care system. Although SCs are increasingly used, there exists little supporting evidence.

Objective: To assess the diagnostic accuracy, patient-perceived usability, and acceptance of two SCs: (1) Ada and (2) Rheport.

Methods: Patients newly presenting to a German secondary rheumatology outpatient clinic were randomly assigned in a 1:1 ratio to complete Ada or Rheport and consecutively the respective other SCs in a prospective non-blinded controlled randomized crossover trial. The primary outcome was the accuracy of the SCs regarding the diagnosis of an IRD compared to the physicians' diagnosis as the gold standard. The secondary outcomes were patient-perceived usability, acceptance, and time to complete the SC.

Results: In this interim analysis, the first 164 patients who completed the study were analyzed. 32.9% (54/164) of the study subjects were diagnosed with an IRD. Rheport showed a sensitivity of 53.7% and a specificity of 51.8% for IRDs. Ada's top 1 (D1) and top 5 disease suggestions (D5) showed a sensitivity of 42.6% and 53.7% and a specificity of 63.6% and 54.5% concerning IRDs, respectively. The correct diagnosis of the IRD patients was within the Ada D1 and D5 suggestions in 16.7% (9/54) and 25.9% (14/54), respectively. The median System Usability Scale (SUS) score of Ada and Rheport was 75.0/100 and 77.5/100, respectively. The median completion time for both Ada and Rheport was 7.0 and 8.5 min, respectively. Sixty-four percent and 67.1% would recommend using Ada and Rheport to friends and other patients, respectively.

Conclusions: While SCs are well accepted among patients, their diagnostic accuracy is limited to date.

Trial Registration: DRKS.de, DRKS00017642 . Registered on 23 July 2019.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13075-021-02498-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042673PMC
April 2021

Patient self-sampling: a cornerstone of future rheumatology care?

Rheumatol Int 2021 06 10;41(6):1187-1188. Epub 2021 Apr 10.

Department of Internal Medicine 3-Rheumatology and Immunology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00296-021-04853-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8035871PMC
June 2021

Digital Health Transition in Rheumatology: A Qualitative Study.

Int J Environ Res Public Health 2021 03 5;18(5). Epub 2021 Mar 5.

AGEIS, Faculty of Medicine, Université Grenoble Alpes, 38706 Grenoble, France.

The global COVID-19 pandemic has led to drastic changes in the management of patients with rheumatic diseases. Due to the imminent risk of infection, monitoring intervals of rheumatic patients have prolonged. The aim of this study is to present insights from patients, rheumatologists, and digital product developers on the ongoing digital health transition in rheumatology. A qualitative and participatory semi-structured fishbowl approach was conducted to gain detailed insights from a total of 476 participants. The main findings show that digital health and remote care are generally welcomed by the participants. Five key themes emerged from the qualitative content analysis: (1) digital rheumatology use cases, (2) user descriptions, (3) adaptation to different environments of rheumatology care, and (4) potentials of and (5) barriers to digital rheumatology implementation. Codes were scaled by positive and negative ratings as well as on micro, meso, and macro levels. A main recommendation resulting from the insights is that both patients and rheumatologists need more information and education to successfully implement digital health tools into clinical routine.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/ijerph18052636DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967307PMC
March 2021

Acceptance of Telerheumatology by Rheumatologists and General Practitioners in Germany: Nationwide Cross-sectional Survey Study.

J Med Internet Res 2021 03 29;23(3):e23742. Epub 2021 Mar 29.

Medizinisches Versorgungszentrum für Rheumatologie Dr M Welcker GmbH, Planegg, Germany.

Background: The worldwide burden of musculoskeletal diseases is increasing. The number of newly registered rheumatologists has stagnated. Primary care, which takes up a key role in early detection of rheumatic disease, is working at full capacity. COVID-19 and its containment impede rheumatological treatment. Telemedicine in rheumatology (telerheumatology) could support rheumatologists and general practitioners.

Objective: The goal of this study was to investigate acceptance and preferences related to the use of telerheumatology care among German rheumatologists and general practitioners.

Methods: A nationwide, cross-sectional, self-completed, paper-based survey on telerheumatology care was conducted among outpatient rheumatologists and general practitioners during the pre-COVID-19 period.

Results: A total of 73.3% (349/476) of survey participants rated their knowledge of telemedicine as unsatisfactory, poor, or very poor. The majority of survey participants (358/480, 74.6%) answered that they do not currently use telemedicine, although 62.3% (291/467) would like to. Barriers to the implementation of telemedicine include the purchase of technology equipment (182/292, 62.3%), administration (181/292, 62.0%), and poor reimbursement (156/292, 53.4%). A total of 69.6% (117/168) of the surveyed physicians reckoned that telemedicine could be used in rheumatology. Surveyed physicians would prefer to use telemedicine to communicate directly with other physicians (370/455, 81.3%) than to communicate with patients (213/455, 46.8%). Among treatment phases, 64.4% (291/452) of participants would choose to use telemedicine during follow-up. Half of the participants would choose telecounseling as a specific approach to improve rheumatology care (91/170, 53.5%).

Conclusions: Before COVID-19 appeared, our results indicated generally low use but high acceptance of the implementation of telerheumatology among physicians. Participants indicated that the lack of a structural framework was a barrier to the effective implementation of telerheumatology. Training courses should be introduced to address the limited knowledge on the part of physicians in the use of telemedicine. More research into telerheumatology is required. This includes large-scale randomized controlled trials, economic analyses, and the exploration of user preferences.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/23742DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042540PMC
March 2021

Advanced machine learning for predicting individual risk of flares in rheumatoid arthritis patients tapering biologic drugs.

Arthritis Res Ther 2021 02 27;23(1):67. Epub 2021 Feb 27.

Department of Internal Medicine 3 - Rheumatology and Immunology, Friedrich-Alexander University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, 91054, Erlangen, Germany.

Background: 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13075-021-02439-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7913400PMC
February 2021

Digital rheumatology in the era of COVID-19: results of a national patient and physician survey.

RMD Open 2021 02;7(1)

Working Group Young Rheumatology, German Society for Rheumatology, Berlin, Germany

Objective: To analyse the impact of the COVID-19 pandemic on rheumatic patients' and rheumatologists' usage, preferences and perception of digital health applications (DHAs).

Methods: A web-based national survey was developed by the Working Group Young Rheumatology of the German Society for Rheumatology and the German League against Rheumatism. The prospective survey was distributed via social media (Twitter, Instagram and Facebook), QR code and email. Descriptive statistics were calculated, and regression analyses were performed to show correlations.

Results: We analysed the responses of 299 patients and 129 rheumatologists. Most patients (74%) and rheumatologists (76%) believed that DHAs are useful in the management of rheumatic and musculoskeletal diseases (RMDs) and felt confident in their own usage thereof (90%; 86%). 38% of patients and 71% of rheumatologists reported that their attitude had changed positively towards DHAs and that their usage had increased due to COVID-19 (29%; 48%). The majority in both groups agreed on implementing virtual visits for follow-up appointments in stable disease conditions. The most reported advantages of DHAs were usage independent of time and place (76.6%; 77.5%). The main barriers were a lack of information on suitable, available DHAs (58.5%; 41.9%), poor usability (42.1% of patients) and a lack of evidence supporting the effectiveness of DHAs (23.2% of rheumatologists). Only a minority (<10% in both groups) believed that digitalisation has a negative impact on the patient-doctor relationship.

Conclusion: The COVID-19 pandemic instigated an increase in patients' and rheumatologists' acceptance and usage of DHAs, possibly introducing a permanent paradigm shift in the management of RMDs.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/rmdopen-2020-001548DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907631PMC
February 2021

Train to target - How we might learn in the future.

Joint Bone Spine 2021 07 23;88(4):105126. Epub 2020 Dec 23.

Department of Rheumatology and Clinical Immunology, Charité- Universitätsmedizin, Berlin, Germany.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jbspin.2020.105126DOI Listing
July 2021

Reduced Muscle Strength Is Associated With Insulin Resistance in Type 2 Diabetes Patients With Osteoarthritis.

J Clin Endocrinol Metab 2021 Mar;106(4):1062-1073

Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.

Context: Type 2 diabetes is associated with a greater risk for musculoskeletal disorders, yet its impact on joint function remains unclear.

Objective: We hypothesized that patients with type 2 diabetes and osteoarthritis would exhibit musculoskeletal impairment, which would associate with insulin resistance and distinct microRNA profiles.

Methods: Participants of the German Diabetes Study with type 2 diabetes (T2D, n = 39) or normal glucose tolerance (CON, n = 27), both with (+OA) or without osteoarthritis (-OA) underwent intravenous glucose tolerance and hyperinsulinemic-euglycemic clamp tests. Musculoskeletal function was assessed by isometric knee extension strength (KES), grip strength, range of motion (ROM), and balance skills, while neural function was measured by nerve conductance velocity (NCV). Arthritis-related symptoms were quantified using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) questionnaire, serum arthritis-related microRNA using quantitative polymerase chain reaction.

Results: Insulin sensitivity was lower in T2D+OA vs T2D-OA (4.4 ± 2.0 vs 5.7 ± 3.0 mg* kg-1*min-1) and in CON+OA vs CON-OA (8.1 ± 2.0 vs 12.0 ± 2.6 mg*kg-1,*min-1, both P < .05). In T2D+OA, KES and ROM were 60% and 22% lower than in CON+OA, respectively (both P < .05). Insulin sensitivity correlated positively with KES (r = 0.41, P < .05) among T2D, and negatively with symptom severity in CON and T2D (r = -0.60 and r = -0.46, respectively, P < .05). CON+OA and T2D+OA had inferior balance skills than CON-OA, whereas NCV was comparable in T2D+OA and T2D-OA. Expression of arthritis-related microRNAs was upregulated in T2D compared to CON, but downregulated in CON+OA compared to CON-OA (P < .05), and did not differ between T2D+OA and T2D-OA.

Conclusion: Musculoskeletal impairment and osteoarthritis-related symptoms are associated with insulin resistance. Type 2 diabetes can mask changes in arthritis-related microRNA profiles.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1210/clinem/dgaa912DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7993587PMC
March 2021

The virtual fishbowl: bringing back dynamic debates to medical conferences.

Ann Rheum Dis 2020 Dec 15. Epub 2020 Dec 15.

Department of Internal Medicine 3, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Germany.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/annrheumdis-2020-219552DOI Listing
December 2020

Machine Learning Electronic Health Record Identification of Patients with Rheumatoid Arthritis: Algorithm Pipeline Development and Validation Study.

JMIR Med Inform 2020 Nov 30;8(11):e23930. Epub 2020 Nov 30.

Department of Rheumatology, Leiden University Medical Center, Leiden, Netherlands.

Background: Financial codes are often used to extract diagnoses from electronic health records. This approach is prone to false positives. Alternatively, queries are constructed, but these are highly center and language specific. A tantalizing alternative is the automatic identification of patients by employing machine learning on format-free text entries.

Objective: The aim of this study was to develop an easily implementable workflow that builds a machine learning algorithm capable of accurately identifying patients with rheumatoid arthritis from format-free text fields in electronic health records.

Methods: Two electronic health record data sets were employed: Leiden (n=3000) and Erlangen (n=4771). Using a portion of the Leiden data (n=2000), we compared 6 different machine learning methods and a naïve word-matching algorithm using 10-fold cross-validation. Performances were compared using the area under the receiver operating characteristic curve (AUROC) and the area under the precision recall curve (AUPRC), and F1 score was used as the primary criterion for selecting the best method to build a classifying algorithm. We selected the optimal threshold of positive predictive value for case identification based on the output of the best method in the training data. This validation workflow was subsequently applied to a portion of the Erlangen data (n=4293). For testing, the best performing methods were applied to remaining data (Leiden n=1000; Erlangen n=478) for an unbiased evaluation.

Results: For the Leiden data set, the word-matching algorithm demonstrated mixed performance (AUROC 0.90; AUPRC 0.33; F1 score 0.55), and 4 methods significantly outperformed word-matching, with support vector machines performing best (AUROC 0.98; AUPRC 0.88; F1 score 0.83). Applying this support vector machine classifier to the test data resulted in a similarly high performance (F1 score 0.81; positive predictive value [PPV] 0.94), and with this method, we could identify 2873 patients with rheumatoid arthritis in less than 7 seconds out of the complete collection of 23,300 patients in the Leiden electronic health record system. For the Erlangen data set, gradient boosting performed best (AUROC 0.94; AUPRC 0.85; F1 score 0.82) in the training set, and applied to the test data, resulted once again in good results (F1 score 0.67; PPV 0.97).

Conclusions: We demonstrate that machine learning methods can extract the records of patients with rheumatoid arthritis from electronic health record data with high precision, allowing research on very large populations for limited costs. Our approach is language and center independent and could be applied to any type of diagnosis. We have developed our pipeline into a universally applicable and easy-to-implement workflow to equip centers with their own high-performing algorithm. This allows the creation of observational studies of unprecedented size covering different countries for low cost from already available data in electronic health record systems.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/23930DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735897PMC
November 2020

Validation of the Mobile Application Rating Scale (MARS).

PLoS One 2020 2;15(11):e0241480. Epub 2020 Nov 2.

Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University Ulm, Ulm, Germany.

Background: Mobile health apps (MHA) have the potential to improve health care. The commercial MHA market is rapidly growing, but the content and quality of available MHA are unknown. Instruments for the assessment of the quality and content of MHA are highly needed. The Mobile Application Rating Scale (MARS) is one of the most widely used tools to evaluate the quality of MHA. Only few validation studies investigated its metric quality. No study has evaluated the construct validity and concurrent validity.

Objective: This study evaluates the construct validity, concurrent validity, reliability, and objectivity, of the MARS.

Methods: Data was pooled from 15 international app quality reviews to evaluate the metric properties of the MARS. The MARS measures app quality across four dimensions: engagement, functionality, aesthetics and information quality. Construct validity was evaluated by assessing related competing confirmatory models by confirmatory factor analysis (CFA). Non-centrality (RMSEA), incremental (CFI, TLI) and residual (SRMR) fit indices were used to evaluate the goodness of fit. As a measure of concurrent validity, the correlations to another quality assessment tool (ENLIGHT) were investigated. Reliability was determined using Omega. Objectivity was assessed by intra-class correlation.

Results: In total, MARS ratings from 1,299 MHA covering 15 different health domains were included. Confirmatory factor analysis confirmed a bifactor model with a general factor and a factor for each dimension (RMSEA = 0.074, TLI = 0.922, CFI = 0.940, SRMR = 0.059). Reliability was good to excellent (Omega 0.79 to 0.93). Objectivity was high (ICC = 0.82). MARS correlated with ENLIGHT (ps<.05).

Conclusion: The metric evaluation of the MARS demonstrated its suitability for the quality assessment. As such, the MARS could be used to make the quality of MHA transparent to health care stakeholders and patients. Future studies could extend the present findings by investigating the re-test reliability and predictive validity of the MARS.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0241480PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7605637PMC
December 2020

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

Rheumatol Int 2020 12 29;40(12):2031-2037. Epub 2020 Sep 29.

Department of Rheumatology and Clinical Immunology, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00296-020-04710-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523492PMC
December 2020

Mobile Health Usage, Preferences, Barriers, and eHealth Literacy in Rheumatology: Patient Survey Study.

JMIR Mhealth Uhealth 2020 08 12;8(8):e19661. Epub 2020 Aug 12.

Department of Internal Medicine 3 - Rheumatology and Immunology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany.

Background: Mobile health (mHealth) defines the support and practice of health care using mobile devices and promises to improve the current treatment situation of patients with chronic diseases. Little is known about mHealth usage and digital preferences of patients with chronic rheumatic diseases.

Objective: The aim of the study was to explore mHealth usage, preferences, barriers, and eHealth literacy reported by German patients with rheumatic diseases.

Methods: Between December 2018 and January 2019, patients (recruited consecutively) with rheumatoid arthritis, psoriatic arthritis, and axial spondyloarthritis were asked to complete a paper-based survey. The survey included questions on sociodemographics, health characteristics, mHealth usage, eHealth literacy using eHealth Literacy Scale (eHEALS), and communication and information preferences.

Results: Of the patients (N=193) who completed the survey, 176 patients (91.2%) regularly used a smartphone, and 89 patients (46.1%) regularly used social media. Patients (132/193, 68.4%) believed that using medical apps could be beneficial for their own health. Out of 193 patients, only 8 (4.1%) were currently using medical apps, and only 22 patients (11.4%) stated that they knew useful rheumatology websites/mobile apps. Nearly all patients (188/193, 97.4%) would agree to share their mobile app data for research purposes. Out of 193 patients, 129 (66.8%) would regularly enter data using an app, and 146 patients (75.6%) would welcome official mobile app recommendations from the national rheumatology society. The preferred duration for data entry was not more than 15 minutes (110/193, 57.0%), and the preferred frequency was weekly (59/193, 30.6%). Medication information was the most desired app feature (150/193, 77.7%). Internet was the most frequently utilized source of information (144/193, 74.6%). The mean eHealth literacy was low (26.3/40) and was positively correlated with younger age, app use, belief in benefit of using medical apps, and current internet use to obtain health information.

Conclusions: Patients with rheumatic diseases are very eager to use mHealth technologies to better understand their chronic diseases. This open-mindedness is counterbalanced by low mHealth usage and competency. Personalized mHealth solutions and clear implementation recommendations are needed to realize the full potential of mHealth in rheumatology.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/19661DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7450373PMC
August 2020

Digital crowdsourcing: unleashing its power in rheumatology.

Ann Rheum Dis 2020 09 11;79(9):1139-1140. Epub 2020 Jun 11.

Department of Internal Medicine 3, Friedrich-Alexander-Universitat Erlangen-Nurnberg, Erlangen, Germany.

The COVID-19 pandemic forces the whole rheumatic and musculoskeletal diseases community to reassemble established treatment and research standards. Digital crowdsourcing is a key tool in this pandemic to create and distil desperately needed clinical evidence and exchange of knowledge for patients and physicians alike. This viewpoint explains the concept of digital crowdsourcing and discusses examples and opportunities in rheumatology. First experiences of digital crowdsourcing in rheumatology show transparent, accessible, accelerated research results empowering patients and rheumatologists.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/annrheumdis-2020-217697DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456558PMC
September 2020

Acceptance, Usage, and Barriers of Electronic Patient-Reported Outcomes Among German Rheumatologists: Survey Study.

JMIR Mhealth Uhealth 2020 07 20;8(7):e18117. Epub 2020 Jul 20.

Working Group Young Rheumatology, German Society for Rheumatology, Berlin, Germany.

Background: The use of patient-reported outcomes (PROs) allows for patient-centered, measurable, and transparent care. Electronic PROs (ePROs) have many benefits and hold great potential to improve current usage of PROs, yet limited evidence exists regarding their acceptance, usage, and barriers among rheumatologists.

Objective: This study aims to evaluate the current level of acceptance, usage, and barriers among German rheumatologists regarding the use of ePROs. The importance of different ePRO features for rheumatologists was investigated. Additionally, the most frequently used PROs for patients with rheumatoid arthritis (RA) were identified.

Methods: Data were collected via an online survey consisting of 18 questions. The survey was completed by members of the Working Group Young Rheumatology of the German Society for Rheumatology (Arbeitsgemeinschaft Junge Rheumatologie der Deutschen Gesellschaft für Rheumatologie [DGRh]) at the 2019 annual DGRh conference. Only members currently working in clinical adult rheumatology were eligible to complete the survey.

Results: A total of 119 rheumatologists completed the survey, of which 107 (89.9%) reported collecting PROs in routine practice and 28 (25.5%) already used ePROs. Additionally, 44% (43/97) were planning to switch to ePROs in the near future. The most commonly cited reason for not switching was the unawareness of suitable software solutions. Respondents were asked to rate the features of ePROs on a scale of 0 to 100 (0=unimportant, 100=important). The most important features were automatic score calculation and display (mean 77.50) and simple data transfer to medical reports (mean 76.90). When asked about PROs in RA, the respondents listed pain, morning stiffness, and patient global assessment as the most frequently used PROs.

Conclusions: The potential of ePROs is widely seen and there is great interest in them. Despite this, only a minority of physicians use ePROs, and the main reason for not implementing them was cited as the unawareness of suitable software solutions. Developers, patients, and rheumatologists should work closely together to help realize the full potential of ePROs and ensure a seamless integration into clinical practice.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/18117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400039PMC
July 2020

Toward Earlier Diagnosis Using Combined eHealth Tools in Rheumatology: The Joint Pain Assessment Scoring Tool (JPAST) Project.

JMIR Mhealth Uhealth 2020 05 15;8(5):e17507. Epub 2020 May 15.

Division of Rheumatology, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.

Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment, and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. Diagnostic delay remains a major challenge for all stakeholders. The combination of electronic health (eHealth) and serologic and genetic markers holds great promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program, is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate these goals while at the same time, reducing cost for society and patients.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/17507DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7260666PMC
May 2020

Influence of Antisynthetase Antibodies Specificities on Antisynthetase Syndrome Clinical Spectrum Time Course.

J Clin Med 2019 Nov 18;8(11). Epub 2019 Nov 18.

Department of Rheumatology, S. Maria Hospital-IRCCS, 42123 Reggio Emilia, Italy.

Antisynthetase syndrome (ASSD) is a rare clinical condition that is characterized by the occurrence of a classic clinical triad, encompassing myositis, arthritis, and interstitial lung disease (ILD), along with specific autoantibodies that are addressed to different aminoacyl tRNA synthetases (ARS). Until now, it has been unknown whether the presence of a different ARS might affect the clinical presentation, evolution, and outcome of ASSD. In this study, we retrospectively recorded the time of onset, characteristics, clustering of triad findings, and survival of 828 ASSD patients (593 anti-Jo1, 95 anti-PL7, 84 anti-PL12, 38 anti-EJ, and 18 anti-OJ), referring to AENEAS (American and European NEtwork of Antisynthetase Syndrome) collaborative group's cohort. Comparisons were performed first between all ARS cases and then, in the case of significance, while using anti-Jo1 positive patients as the reference group. The characteristics of triad findings were similar and the onset mainly began with a single triad finding in all groups despite some differences in overall prevalence. The "ex-novo" occurrence of triad findings was only reduced in the anti-PL12-positive cohort, however, it occurred in a clinically relevant percentage of patients (30%). Moreover, survival was not influenced by the underlying anti-aminoacyl tRNA synthetase antibodies' positivity, which confirmed that antisynthetase syndrome is a heterogeneous condition and that antibody specificity only partially influences the clinical presentation and evolution of this condition.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.3390/jcm8112013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6912490PMC
November 2019

Response to Letter to the Editor.

Ultraschall Med 2019 12 8;40(6):772. Epub 2019 Nov 8.

Clinic of Internal Medicine 3, University Hospital Erlangen, Germany.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1055/a-0967-5282DOI Listing
December 2019

German Mobile Apps in Rheumatology: Review and Analysis Using the Mobile Application Rating Scale (MARS).

JMIR Mhealth Uhealth 2019 08 5;7(8):e14991. Epub 2019 Aug 5.

Working Group Young Rheumatology, German Society for Rheumatology, Berlin, Germany.

Background: Chronic rheumatic diseases need long-term treatment and professional supervision. Mobile apps promise to improve the lives of patients and physicians. In routine practice, however, rheumatology apps are largely unknown and little is known about their quality and safety.

Objective: The aim of this study was to provide an overview of mobile rheumatology apps currently available in German app stores, evaluate app quality using the Mobile Application Rating Scale (MARS), and compile brief, ready-to-use descriptions for patients and rheumatologists.

Methods: The German App Store and Google Play store were systematically searched to identify German rheumatology mobile apps for patient and physician use. MARS was used to independently assess app quality by 8 physicians, 4 using Android and 4 using iOS smartphones. Apps were randomly assigned so that 4 apps were rated by all raters and the remaining apps were rated by two Android and two iOS users. Furthermore, brief app descriptions including app developers, app categories, and features were compiled to inform potential users and developers.

Results: In total, 128 and 63 apps were identified in the German Google Play and App Store, respectively. After removing duplicates and only including apps that were available in both stores, 28 apps remained. Sixteen apps met the inclusion criteria, which were (1) German language, (2) availability in both app stores, (3) targeting patients or physicians as users, and (4) clearly including rheumatology or rheumatic diseases as subject matter. Exclusion criteria were (1) congress apps and (2) company apps with advertisements. Nine apps addressed patients and 7 apps addressed physicians. No clinical studies to support the effectiveness and safety of apps could be found. Pharmaceutical companies were the main developers of two apps. Rheuma Auszeit was the only app mainly developed by a patient organization. This app had the highest overall MARS score (4.19/5). Three out of 9 patient apps featured validated questionnaires. The median overall MARS score was 3.85/5, ranging from 2.81/5 to 4.19/5. One patient-targeted and one physician-targeted app had MARS scores >4/5. No significant rater gender or platform (iOS/Android) differences could be observed. The overall correlation between app store ratings and MARS scores was low and inconsistent between platforms.

Conclusions: To our knowledge, this is the first study that systematically identified and evaluated mobile apps in rheumatology for patients and physicians available in German app stores. We found a lack of supporting clinical studies, use of validated questionnaires, and involvement of academic developers. Overall app quality was heterogeneous. To create high-quality apps, closer cooperation led by patients and physicians is vital.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2196/14991DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6699116PMC
August 2019

Calcium pyrophosphate deposition disease induced inflammatory back pain.

Rheumatology (Oxford) 2020 02;59(2):456

Department of Internal Medicine 3, Rheumatology and Immunology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/rheumatology/kez225DOI Listing
February 2020

Comment on: 'Idiopathic inflammatory myopathies and antisynthetase syndrome: contribution of antisynthetase antibodies to improve current classification criteria' by Greco .

Ann Rheum Dis 2020 07 17;79(7):e85. Epub 2019 Apr 17.

Department of Internal Medicine 3, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/annrheumdis-2019-215484DOI Listing
July 2020

Comparison of Current Swiss Fetal Biometry Reference Charts with Reference Charts from 1999. Are Fetuses Getting Bigger?

Ultraschall Med 2020 Aug 24;41(4):410-417. Epub 2018 May 24.

Clinic of Obstetrics, University Hospital Zurich, Switzerland.

Purpose:  To create current fetal biometry reference ranges and to compare them with references published in 1999, from the same local area in order to generate data for secular trend in fetal size.

Materials And Methods:  Applying the same methodology as previously published, we calculated reference ranges for biparietal diameter (BPD), occipitofrontal diameter (OFD), head circumference (HC), abdominal circumference (AC) and femur length (FL) in 7863 patients examined at the obstetric clinics in a cross-sectional, prospective study in a university setting from January 2008 to December 2014. In order to compare the new reference ranges with our previously published data, we used Z-Scores and displayed the pick-up of fetal biometry data below the 5 and above the 95 percentile using the previously published reference charts.

Results:  The comparison of the charts showed a minimal but clinically relevant increase in mean fetal body measures (BPD, HC, AC). Applying the 1999 charts to the new dataset, we would classify only 162 of 339 fetuses (47.8 %) to be correctly below the 5 percentile for AC and only 134 of 349 (38.4 %) fetuses were correctly below the 5 percentile for HC. On the other hand, the 1999 charts classified 426 instead of 332 fetuses to be above the 95 percentile for AC, which means an overestimation of 28.3 %.

Conclusion:  Applying a similar methodology, study collective and clinical setting, our new charts showed clinically relevant differences compared to the 1999 charts. The data suggest that within one generation fetuses are getting bigger and regular updates of fetal reference charts are needed.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1055/a-0591-3206DOI Listing
August 2020