The ability of rheumatologists blinded to prior workup to diagnose rheumatoid arthritis only by clinical assessment: a cross-sectional study

Diagnostic delays in systemic vasculitides

Systemic vasculitides are among the less common disorders encountered in routine rheumatology practice. The low incidence and heterogeneous presentation at onset can potentially lead to delayed diagnosis. Not recognizing these in the early phase may prove detrimental, as some vasculitis may progress to a catastrophic course with major morbidity or mortality. The causes of diagnostic delay may vary among different types of vasculitis and may also be disease-, patient-, or physician-related. Disease-related factors include the myriad presentations with diverse and non-specific symptoms, mimicking other conditions like infections. In addition, some forms have prolonged prodromal phases before evident organ damage. Limited awareness among healthcare professionals, particularly outside rheumatology, and a lack of readily available diagnostic tools contribute to missed diagnoses. Delays in seeking care due to non-specific symptoms or lack of access to specialist care can worsen outcomes. The economic burden also increases with delayed diagnosis and damage accrual when the disease remains unrecognized or untreated for prolonged periods. Although the causes of vasculitis are numerous, including secondary causes, in this review, we focus on diagnostic delays in primary vasculitides and suggest potential steps to identify and treat these diseases early. These include educating both healthcare professionals and the public about the signs and symptoms of vasculitis; expanding the rheumatology workforce and facilitating timely referrals; implementing readily available and reliable tests for early detection; and streamlining care and diagnostic pathways. Such measures have the potential to improve the overall outcomes of the disease, with prolonged remission, minimal damage accrual, and improved quality of life.

Stepwise asynchronous telehealth assessment of patients with suspected axial spondyloarthritis: results from a pilot study

Patients with axial spondyloarthritis (axSpA) suffer from one of the longest diagnostic delays among all rheumatic diseases. Telemedicine (TM) may reduce this diagnostic delay by providing easy access to care. Diagnostic rheumatology telehealth studies are scarce and largely limited to traditional synchronous approaches such as resource-intensive video and telephone consultations. The aim of this study was to investigate a stepwise asynchronous telemedicine-based diagnostic approach in patients with suspected axSpA. Patients with suspected axSpA completed a fully automated digital symptom assessment using two symptom checkers (SC) (bechterew-check and Ada). Secondly, a hybrid stepwise asynchronous TM approach was investigated. Three physicians and two medical students were given sequential access to SC symptom reports, laboratory and imaging results. After each step, participants had to state if axSpA was present or not (yes/no) and had to rate their perceived decision confidence. Results were compared to the final diagnosis of the treating rheumatologist. 17 (47.2%) of 36 included patients were diagnosed with axSpA. Diagnostic accuracy of bechterew-check, Ada, TM students and TM physicians was 47.2%, 58.3%, 76.4% and 88.9% respectively. Access to imaging results significantly increased sensitivity of TM-physicians (p < 0.05). Mean diagnostic confidence of false axSpA classification was not significantly lower compared to correct axSpA classification for both students and physicians. This study underpins the potential of asynchronous physician-based telemedicine for patients with suspected axSpA. Similarly, the results highlight the need for sufficient information, especially imaging results to ensure a correct diagnosis. Further studies are needed to investigate other rheumatic diseases and telediagnostic approaches.

Student-led clinics and ePROs to accelerate diagnosis and treatment of patients with axial spondyloarthritis: results from a prospective pilot study

We aimed to investigate (1) student-led clinics and (2) electronic patient-reported outcomes (ePROs) to accelerate diagnosis and treatment of patients with axial spondyloarthritis (axSpA). Patients with suspected axSpA completed an initial student-led clinic visit (T-1) prior to their planned actual rheumatologist visit (T0). Acceleration of patient appointment and NSAID therapy start, availability of diagnostic findings, and treatment response at T0 were evaluated. Beginning at T-1, patients completed electronic BASDAI questionnaires every 2 weeks. Concordance of paper-based and electronic BASDAI was evaluated. Patient acceptance of ePRO reporting and student-led clinics was measured using the net promoter score (NPS). 17/36 (47.2%) included patients were diagnosed with axSpA. Student-led clinics (T-1) significantly accelerated patient appointments by more than 2 months (T0, T-1, p < 0.0001) and axSpA guideline-conform NSAID treatment (p < 0.0001). At T0, diagnostic workup was completed for all patients and 7/17 (41.2%) axSpA patients presented with a clinically important improvement or were in remission. 34/36 (94.4%) patients completed at least 80% of the ePROs between T-1 and T0. Electronic and paper-administered BASDAI correlated well (r = 0.8 p < 0.0001). Student-led clinics and ePROs were well accepted by patients with NPS scores of + 62.0% (mean ± SD 9.2/10.0 ± 0.9) and + 30.5% (mean ± SD 8.0/10.0 ± 1.7), respectively. In conclusion, student-led clinics and ePRO monitoring were well accepted, accelerated diagnostic workup and treatment in patients with axSpA.

Comparison of physician and artificial intelligence-based symptom checker diagnostic accuracy

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.

Remote self-collection of capillary blood using upper arm devices for autoantibody analysis in patients with immune-mediated inflammatory rheumatic diseases

Objectives

To evaluate the feasibility, accuracy, usability and acceptability of two upper arm self-sampling devices for measurement of autoantibodies and C reactive protein (CRP) levels in patients with immune-mediated rheumatic diseases (IMRDs).

Methods

70 consecutive patients with IMRD with previously documented autoantibodies were assigned to supervised and unsupervised self-collection of capillary blood with the Tasso+ or TAP II device. Interchangeability of 17 biomarkers with standard venesection was assessed by: concordance, correlation, paired sample hypothesis testing and Bland-Altman plots. Patients completed an evaluation questionnaire, including the System Usability Scale (SUS) and Net Promoter Score (NPS).

Results

While 80.0% and 77.0% were able to safely and successfully collect capillary blood using the Tasso+ and TAP II within the first attempt, 69 of 70 (98.6%) patients were successful in collecting capillary blood within two attempts. Concordance between venous and capillary samples was high; 94.7% and 99.5% for positive and negative samples, respectively. For connective tissue disease screen, anti-Ro52 and anti-proteinase 3 autoantibody levels, no significant differences were observed. Self-sampling was less painful than standard venesection for the majority of patients (Tasso+: 71%; TAP II: 63%). Both devices were well accepted (NPS; both: +28%), usability was perceived as excellent (SUS; Tasso+: 88.6 of 100; TAP II: 86.0 of 100) and 48.6 %/62.9% of patients would prefer to use the Tasso+/TAP II, respectively, instead of a traditional venous blood collection.

Conclusions

Remote self-collection of capillary blood using upper arm-based devices for autoantibody and CRP analysis in patients with autoimmune rheumatic diseases is feasible, accurate and well accepted among patients.

Trial registration number

WHO International Clinical Trials Registry (DRKS00024925).

Machine learning-based improvement of an online rheumatology referral and triage system

Introduction

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.

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

BACKGROUND

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.

Accuracy and usability of a diagnostic decision support system in the diagnosis of three representative rheumatic diseases: a randomized controlled trial among medical students

BACKGROUND

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.

Ultrasound assessment of hands and feet for synovitis at time of first clinical visit markedly reduces time to diagnosis in routine care

OBJECTIVES

The role of musculoskeletal ultrasound (MSUS) in routine care for diagnosing arthritis is not fully elucidated, but US is more sensitive than clinical joint examination for detecting synovitis. Therefore, the use of US may facilitate diagnosis of arthritis. The aim of the study was to assess if MSUS examination of hands and feet in relation to the first clinical visit had an impact on the time to reach a final diagnosis and the number of clinical follow-up visits needed after first consultation.

METHODS

Two cohorts referred to the outpatient arthritis clinic with suspected arthritis were compared with each other, 1. MSUS (October 2017 to June 2018) of hands and feet performed prior to the first clinical visit and 2. MSUS (November 2016 to June 2017) was performed Ad hoc, for following aspects: time to clinical diagnosis, number of clinical visits needed, and number of ultrasound examinations.

RESULTS

In total, 163 and 109 patients were included in the MSUS and comparative cohorts, respectively. Adding MSUS to the first clinical visit reduced the time to diagnosis from mean 31(SD ± 32.2) days to 12(±17.3) days(p< 0.01). The number of clinical visits needed was reduced from mean 2.8(±1.1)-2.1(±1.3),(p< 0.01) corresponding to a reduction of 114 visits in the MSUS cohort. A final diagnosis with inflammatory arthritis was found in 76(47%) of patients in the MSUS cohort vs 29(27%) in the comparative cohort(p< 0.01).

CONCLUSION

In patients referred for suspected arthritis, routine MSUS in relation to the first clinical visit significantly reduces time to diagnosis and number of clinical visits needed to reach a final diagnosis.

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

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.

Ankle arthritis - an important signpost in rheumatologic practice

Ankle arthritis is a useful clinical signpost to differential diagnosis in rheumatic disease. Biomechanical features and differences in cartilage physiology compared with the knee may confer protection of the ankle joint from factors predisposing to certain arthritides. The prevalence of ankle OA is low, and usually secondary to trauma. Primary OA of the ankle should be investigated for underlying causes, especially haemochromatosis. New presentations of inflammatory mono/oligo arthritis involving the ankle are more likely due to undifferentiated arthritis or spondyloarthritis than RA, and gout over CPPD. The ankle is often involved in bacterial and viral causes of septic arthritis, especially bacterial, chikungunya and HIV infection, but rarely tuberculosis. Periarticular hind foot swelling can be confused with ankle arthritis, exemplified by Lofgren’s syndrome and hypertrophic osteoarthropathy where swelling is due to subcutaneous oedema and osteitis respectively, and the ankle joint is rarely involved.

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

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.

Evaluation of Diagnostic Tests

As technology advances, diagnostic tests continue to improve and each year, we are presented with new alternatives to standard procedures. Given the plethora of diagnostic alternatives, diagnostic tests must be evaluated to determine their place in the diagnostic armamentarium. The first step involves determining the accuracy of the test, including the sensitivity and specificity, positive and negative predictive values, likelihood ratios for positive and negative tests, and receiver operating characteristic (ROC) curves. The role of the test in a diagnostic pathway has then to be determined, following which the effect on patient outcome should be examined.

Rheumatologische paraneoplastische Syndrome

Rheumatologische paraneoplastische Syndrome sind selten, stellten jedoch eine wichtige Differenzialdiagnose zu klassischen rheumatologischen Krankheitsbildern dar. Durch das Erkennen der eindrücklichen Syndrome mit typischen Labor- und Untersuchungsbefunden ist oftmals eine beschleunigte Diagnose der zugrundeliegenden Malignität und kurative Therapie möglich. In dieser Übersichtsarbeit werden die Charakteristika rheumatologischer paraneoplastischer Syndrome vorgestellt.

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

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.