Increase in axial spondyloarthritis diagnoses after the introduction of the ASAS criteria: a systematic review.

To explore the proportion of axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA) diagnoses within all newly referred patients visiting rheumatology outpatient clinics. And more specifically, to analyze whether there is an effect of the introduction of the ASAS and CASPAR classification criteria for axSpA and PsA. We systematically searched Embase, Medline Ovid, Cochrane Central and Web of Science from database inception to November 2022. Articles that investigated new onsets of axSpA and PsA in adults from rheumatology clinics were included. In total, 170 out of 7139 studies were found eligible for full-text review, after which 33 unique studies were included. Seventeen studies reported new onsets of axSpA, and 20 studies of PsA. The pooled proportion of axSpA within all newly referred patients was 19% (95% CI 15-23%) and 18% (95% CI 14-22%) for PsA. The proportion of axSpA before 2009 was 3% (95% CI 0-6%) and increased up to 21% (95% CI 14-28%) after 2009. For PsA, limited data were available in order to analyze the proportions of PsA before 2006. Overall, heterogeneity was high (I2 > 95%, p < 0.001) that was most likely caused by geographical area, study design, setting and use of different referral strategies. The pooled proportion of axSpA and PsA among patients referred to the rheumatology outpatient clinic was 19 and 18%, respectively. Although the proportion of diagnosed axSpA patients seemed to increase after the introduction of the ASAS criteria, due to the large heterogeneity our findings should be interpreted with caution.

Barriers and facilitators for implementation of a digital referral algorithm for inflammatory arthritis - a qualitative assessment in patients and caregivers.

PURPOSE: Difficulty to recognize inflammatory rheumatic diseases (IRD) in a primary care setting leads to late referral to secondary care. An evidence-based digital referral algorithm can support early referral, yet implementation in daily practice only succeeds with support of end users. We aim to understand the context of implementing a digital referral algorithm and explore the potential barriers and facilitators to implementation. METHODS: This qualitative study comprised focus groups and an online survey. Focus groups were performed with patients from outpatient rheumatology clinics. Surveys were sent out to general practitioners and rheumatologists distributed over The Netherlands. The presented digital referral algorithm originates from the JOINT referral study. Thematic analysis was used with inductive and deductive approaches. RESULTS: In total 26 patients participated distributed over three focus groups, and 215 caregivers (104 rheumatologists, 111 general practitioners) filled out the survey. Both patients and caregivers endorse the need for early referral, and recognize the perceived benefit of the digital algorithm. Potential barriers include the complexity of currently included questions, and the outcome lacking information on what to do with no risk of IRD. In order for implementation to be successful, the inclusivity, accessibility, content and outcome of the algorithm are considered important themes. CONCLUSION: Successful implementation of a digital referral algorithm needs a systematic multi-facetted approach, considering the barriers and facilitators for implementation as discussed. Since the majority of identified barriers and facilitators was overlapping between all stakeholders, findings from this study can reliably inform further decision strategies for successful implementation.

Diagnostic Performance and Clinical Utility of Referral Rules to Identify Primary Care Patients at Risk of an Inflammatory Rheumatic Disease.

OBJECTIVE: To determine the diagnostic performance and clinical utility of the Rotterdam Early Arthritis Cohort (REACH) and the Clinical Arthritis Rule (CARE) referral rules in an independent population of unselected patients from primary care. METHODS: This study consisted of adults who were suspected of the need for referral to a rheumatologist by their general practitioner. Diagnostic accuracy measures and a net benefit approach were used to compare both rules to usual care for recognizing inflammatory arthritis and inflammatory rheumatic diseases (IRDs). Using the least absolute shrinkage and selection operator method and cross-validation we created an optimal prediction rule for IRD. RESULTS: This study consisted of 250 patients, of whom 42 (17%) were diagnosed with inflammatory arthritis and 55 (22%) with an IRD 3 months after referral. Considering inflammatory arthritis, the area under the receiver operating characteristic curve (AUC) was 0.72 (95% confidence interval [95% CI] 0.64-0.80) for REACH and 0.82 (95% CI 0.75-0.88) for CARE. Considering IRD, the AUC was 0.66 (95% CI 0.58-0.74) for REACH and 0.76 (95% CI 0.69-0.83) for CARE. CARE was of highest clinical value when compared to usual care. The composite referral rule for IRD of 10 parameters included sex, age, joint features, acute onset of symptoms, physical limitations, and duration of symptoms (AUC 0.82 [95% CI 0.75-0.88]). CONCLUSION: Both validated rules have a net benefit in recognizing inflammatory arthritis as well as IRD compared to usual care, but CARE shows superiority over REACH. Although the composite referral rule indicates a greater diagnostic performance, external validation is needed.