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Abstract Background Outcome measures are crucial to support a treat-to-target approach to rheumatoid arthritis (RA) care, yet their integration into clinical practice remains inconsistent. We developed an Electronic Heath Record-integrated, patient-facing side-car application to display RA outcomes (disease activity, functional status, pain scores), medications, and lab results during clinical visits (“RA PRO Dashboard”). The study aimed to evaluate patient perceptions and attitudes towards the implementation of a novel patient-facing dashboard during clinical visits using a mixed-methods approach. Methods RA patients whose clinicians used the dashboard at least once during their clinical visit were invited to complete a survey regarding its usefulness in care. We also conducted semi-structured interviews with a subset of patients to assess their perceptions of the dashboard. The interviews were transcribed verbatim and analyzed thematically using deductive and inductive techniques. Emerging themes and subthemes were organized into four domains of the Ecological Model of Health. Results Out of 173 survey respondents, 79% were interested in seeing the dashboard again at a future visit, 71% felt it improved their understanding of their disease, and 65% believed it helped with decision-making about their RA care. Many patients reported that the dashboard helped them discuss their RA symptoms (76%) and medications (72%) with their clinician. Interviews with 29 RA patients revealed 10 key themes: the dashboard was perceived as a valuable visual tool that improved patients’ understanding of RA outcome measures, enhanced their involvement in care, and increased their trust in clinicians and the clinic. Common reported limitations included concerns about reliability of RA outcome questionnaires for some RA patients and inconsistent collection and explanation of these measures by clinicians. Conclusions In both the quantitative and qualitative components of the study, patients reported that the dashboard improved their understanding of their RA, enhanced patient-clinician communication, supported shared decision-making, and increased patient engagement in care. These findings support the use of dashboards or similar data visualization tools in RA care and can be used in future interventions to address challenges in data collection and patient education.

Objective Despite interest in optimizing the electronic health record (EHR) to facilitate chronic disease care for conditions like rheumatoid arthritis (RA), progress in this area has been slow. EHR sidecar applications offer one solution, but little guidance exists to facilitate their successful development, deployment, and maintenance in the healthcare setting. We aimed to provide a roadmap for how to develop and deploy an EHR sidecar application based on our experience building a new EHR-integrated, patient-facing visualization tool that displayed disease outcomes to RA patients during a clinical visit (the “RA PRO dashboard”) in a large academic health center. Methods We describe the technical design and implementation of the RA PRO dashboard; report clinic workflow adaptations to incorporate this new technology; and discuss the resources required and challenges encountered in maintaining this application. Results The RA PRO dashboard required extensive human-centered design work, regulatory approvals, software development, user testing, integration with Epic-based workflows, and maintenance. Key requirements were prioritized based on the anticipated effects on usefulness and ease of use. Implementation science strategies were used to improve use of the dashboard in clinic and included education for patients, staff, and clinicians; reports of actual use of the dashboard and data quality; and regular meetings between the research team and clinicians to discuss and address barriers to use. Conclusion Successful development and deployment of an EHR-integrated application are resource-intensive and require technical, operational, and educational innovations. The roadmap presented in this study can serve as a resource for future developers.

Objective This study aimed to validate claims-based algorithms for identifying SLE and lupus nephritis (LN) in Medicare data, enhancing the use of the Lupus Index for geospatial research on SLE prevalence and outcomes.Methods We retrospectively evaluated the performance of rule-based algorithms using the International Classification of Diseases, 10th Revision (ICD-10) codes to identify SLE and LN in a well-defined prospective longitudinal cohort of patients with and without SLE from a South Carolina registry and rheumatology outpatient clinics. The analysis included comparison of algorithms based on Medicare fee-for-service claims data to these rigorously phenotyped populations. The primary classification for SLE cases was based on the American College of Rheumatology and Systemic Lupus Erythematosus International Collaborating Clinics criteria for SLE and LN. Algorithms were based on the number of ICD-10 codes with and without a 30-day separation in the observation period, including all of 2016–2018.Results The algorithm using two ICD-10 codes for SLE, with or without a 30-day separation, showed the best overall performance. For LN, specific ICD-10 codes outperformed combinations of SLE and renal/proteinuria codes that were found in ICD-9.Conclusions The findings of this study highlight the performance of specific ICD-10 code algorithms in identifying SLE and LN cases within Medicare data, providing a valuable tool for informing use of the Lupus Index. This index allows for improved geographical targeting of clinical resources, health disparity studies and clinical trial site selection. The study underscores the importance of algorithm selection based on research objectives, recommending more specific algorithms for precise tasks like clinical trial site identification and less specific ones for broader applications such as health disparities research.

Abstract Background Improving shared decision-making using a treat-to-target approach, including the use of clinical outcome measures, is important to providing high quality care for rheumatoid arthritis (RA). We developed an Electronic Health Record (EHR) integrated, patient-facing sidecar dashboard application that displays RA outcomes, medications, and lab results for use during clinical visits (“RA PRO dashboard”). The purpose of this study was to assess clinician perceptions and experiences using the dashboard in a university rheumatology clinic. Methods We conducted focus group (FG) discussions with clinicians who had access to the dashboard as part of a randomized, stepped-wedge pragmatic trial. FGs explored clinician perceptions towards the usability, acceptability, and usefulness of the dashboard. FG data were analyzed thematically using deductive and inductive techniques; generated themes were categorized into the domains of the Technology Acceptance Model (TAM). Results 3 FG discussions were conducted with a total of 13 clinicians. Overall, clinicians were enthusiastic about the dashboard and expressed the usefulness of visualizing RA outcome trajectories in a graphical format for motivating patients, enhancing patient understanding of their RA outcomes, and improving communication about medications. Major themes that emerged from the FG analysis as barriers to using the dashboard included inconsistent collection of RA outcomes leading to sparse data in the dashboard and concerns about explaining RA outcomes, especially to patients with fibromyalgia. Other challenges included time constraints and technical difficulties refreshing the dashboard to display real-time data. Methods for integrating the dashboard into the visit varied: some clinicians used the dashboard at the beginning of the visit as they documented RA outcomes; others used it at the end to justify changes to therapy; and a few shared it only with stable patients. Conclusions The study provides valuable insights into clinicians’ perceptions and experiences with the RA PRO dashboard. The dashboard showed promise in enhancing patient-clinician communication, shared decision-making, and overall acceptance among clinicians. Addressing challenges related to data collection, education, and tailoring dashboard use to specific patient populations will be crucial for maximizing its potential impact on RA care. Further research and ongoing improvements in dashboard design and implementation are warranted to ensure its successful integration into routine clinical practice.

Objective Trauma history is associated with SLE onset and worse patient-reported outcomes; perceived stress is associated with greater SLE disease activity. Stress perceptions vary in response to life events and may be influenced by psychosocial factors. In an SLE cohort, we examined whether stressful events associated with perceived stress, whether psychosocial factors affected perceived stress, and whether these relationships varied by prior trauma exposure.Methods This is a cross-sectional analysis of data from the California Lupus Epidemiology Study, an adult SLE cohort. Multivariable linear regression analyses controlling for age, gender, educational attainment, income, SLE damage, comorbid conditions, glucocorticoids ≥7.5 mg/day and depression examined associations of recent stressful events (Life Events Inventory) and positive (resilience, self-efficacy, emotional support) and negative (social isolation) psychosocial factors with perceived stress. Analyses were stratified by lifetime trauma history (Brief Trauma Questionnaire (BTQ)) and by adverse childhood experiences (ACEs) in a subset.Results Among 242 individuals with SLE, a greater number of recent stressful events was associated with greater perceived stress (beta (95% CI)=0.20 (0.07 to 0.33), p=0.003). Positive psychosocial factor score representing resilience, self-efficacy and emotional support was associated with lower perceived stress when accounting for number of stressful events (−0.67 (−0.94 to –0.40), p

Objective Cognitive impairment is a common complaint in SLE, but approaches to measuring cognitive performance objectively vary. Leveraging data collected in a population-based cohort of individuals with validated SLE, we compared performance and potential impairment across multiple measures of cognition.Methods During a single study visit (October 2019–May 2022), times to complete the Trail Making Test B (TMTB; N=423) were recorded; potential impairment was defined as an age-corrected and education-corrected T-score 1.5 SD longer than the normative time). A clock drawing assessment (CLOX; N=435) with two parts (free clock draw (CLOX1) and copy (CLOX2)) was also performed (score range: 0–15; higher scores=better performance); potential impairment was defined as CLOX1 1.5 SD lower the normative score).Results Participants (mean age 46 years; 92% female; 82% black) had a median (IQR) TMTB time of 96 (76–130) s; median (IQR) CLOX1 and CLOX2 scores of 12 (10–13) and 14 (13–15); and a mean (SD) fluid cognition standard score of 87.2 (15.6). TMTB time and fluid cognition score (ρ=−0.53, p

Abstract Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of Asian-Ancestry (AsA) disproportionately experience more severe SLE compared to individuals of European-Ancestry (EA), including increased renal involvement and tissue damage. However, the mechanisms underlying elevated severity in the AsA population remain unclear. Here, we utilized available gene expression data and genotype data based on all non-HLA SNP associations in EA and AsA SLE patients detected using the Immunochip genotyping array. We identified 2778 ancestry-specific and 327 trans-ancestry SLE-risk polymorphisms. Genetic associations were examined using connectivity mapping and gene signatures based on predicted biological pathways and were used to interrogate gene expression datasets. SLE-associated pathways in AsA patients included elevated oxidative stress, altered metabolism and mitochondrial dysfunction, whereas SLE-associated pathways in EA patients included a robust interferon response (type I and II) related to enhanced cytosolic nucleic acid sensing and signaling. An independent dataset derived from summary genome-wide association data in an AsA cohort was interrogated and identified similar molecular pathways. Finally, gene expression data from AsA SLE patients corroborated the molecular pathways predicted by SNP associations. Identifying ancestry-related molecular pathways predicted by genetic SLE risk may help to disentangle the population differences in clinical severity that impact AsA and EA individuals with SLE.

Summary: Background: Due to geographic isolation and border controls Aotearoa New Zealand (AoNZ) attained high levels of population coronavirus disease-19 (COVID-19) vaccination before widespread transmission of COVID-19. We describe outcomes of SARS-CoV-2 infection (Omicron variant) in people with inflammatory rheumatic diseases in this unique setting. Methods: This observational study included people with inflammatory rheumatic disease and SARS-CoV-2 infection in AoNZ between 1 February and 30 April 2022. Data were collected via the Global Rheumatology Alliance Registry including demographic and rheumatic disease characteristics, and COVID-19 vaccination status and outcomes. Multivariable logistic regression was used to explore associations of demographic and clinical factors with COVID-19 hospitalisation and death. Findings: Of the 1599 cases included, 96% were from three hospitals that systematically identified people with inflammatory rheumatic disease and COVID-19. At time of COVID-19, 1513 cases (94.6%) had received at least two COVID-19 vaccinations. Hospitalisation occurred for 104 (6.5%) cases and 10 (0.6%) patients died. Lower frequency of hospitalisation was seen in cases who had received at least two vaccinations (5.9%), compared to the unvaccinated (20.6%) or those with a single vaccine dose (10.7%). In multivariable adjusted models, people with gout or connective tissue diseases (CTD) had increased risk of the combined outcome of hospitalisation/death, compared to people with inflammatory arthritis. Glucocorticoid and rituximab use were associated with increased rates of hospitalisation/death. All patients who died had three or more co-morbidities or were over 60 years old. Interpretation: In this cohort with inflammatory rheumatic diseases and high vaccination rates, severe outcomes from SARS-CoV-2 Omicron variant were relatively infrequent. The outcome of Omicron variant infection among vaccinated but SARS-CoV-2 infection-naive people with inflammatory rheumatic disease without other known risk factors were favourable. Funding: Financial support from the American College of Rheumatology (ACR) and European Alliance of Associations for Rheumatology (EULAR) included management of COVID-19 Global Rheumatology Alliance funds.

Objective To describe people with gout who were diagnosed with coronavirus disease 2019 (COVID‐19) and hospitalized and to characterize their outcomes. Methods Data on patients with gout hospitalized for COVID‐19 between March 12, 2020, and October 25, 2021, were extracted from the COVID‐19 Global Rheumatology Alliance registry. Descriptive statistics were used to describe the demographics, comorbidities, medication exposures, and COVID‐19 outcomes including oxygenation or ventilation support and death. Results One hundred sixty‐three patients with gout who developed COVID‐19 and were hospitalized were included. The mean age was 63 years, and 85% were male. The majority of the group lived in the Western Pacific Region (35%) and North America (18%). Nearly half (46%) had two or more comorbidities, with hypertension (56%), cardiovascular disease (28%), diabetes mellitus (26%), chronic kidney disease (25%), and obesity (23%) being the most common. Glucocorticoids and colchicine were used pre‐COVID‐19 in 11% and 12% of the cohort, respectively. Over two thirds (68%) of the cohort required supplemental oxygen or ventilatory support during hospitalization. COVID‐19‐related death was reported in 16% of the overall cohort, with 73% of deaths documented in people with two or more comorbidities. Conclusion This cohort of people with gout and COVID‐19 who were hospitalized had high frequencies of ventilatory support and death. This suggests that patients with gout who were hospitalized for COVID‐19 may be at risk of poor outcomes, perhaps related to known risk factors for poor outcomes, such as age and presence of comorbidity.

Objective Some patients with rheumatic diseases might be at higher risk for coronavirus disease 2019 (COVID‐19) acute respiratory distress syndrome (ARDS). We aimed to develop a prediction model for COVID‐19 ARDS in this population and to create a simple risk score calculator for use in clinical settings. Methods Data were derived from the COVID‐19 Global Rheumatology Alliance Registry from March 24, 2020, to May 12, 2021. Seven machine learning classifiers were trained on ARDS outcomes using 83 variables obtained at COVID‐19 diagnosis. Predictive performance was assessed in a US test set and was validated in patients from four countries with independent registries using area under the curve (AUC), accuracy, sensitivity, and specificity. A simple risk score calculator was developed using a regression model incorporating the most influential predictors from the best performing classifier. Results The study included 8633 patients from 74 countries, of whom 523 (6%) had ARDS. Gradient boosting had the highest mean AUC (0.78; 95% confidence interval [CI]: 0.67‐0.88) and was considered the top performing classifier. Ten predictors were identified as key risk factors and were included in a regression model. The regression model that predicted ARDS with 71% (95% CI: 61%‐83%) sensitivity in the test set, and with sensitivities ranging from 61% to 80% in countries with independent registries, was used to develop the risk score calculator. Conclusion We were able to predict ARDS with good sensitivity using information readily available at COVID‐19 diagnosis. The proposed risk score calculator has the potential to guide risk stratification for treatments, such as monoclonal antibodies, that have potential to reduce COVID‐19 disease progression.

Objective Glucocorticoids are part of standard therapy for systemic lupus erythematosus (SLE), despite adverse effects associated with long‐term treatment. Belimumab improved clinical manifestations of SLE and reduced glucocorticoid doses in clinical trials and clinical practice; however, associations have not been examined using multi‐institutional electronic health record (EHR) data. Using the Rheumatology Informatics System for Effectiveness registry, we examined glucocorticoid use patterns among belimumab‐treated adults with SLE. Methods This retrospective analysis (GSK Study 209267) used EHR prescription records of patients with SLE managed by rheumatologists. Eligible patients had an index date (first belimumab prescription) between January 2014 and June 2018. The primary analysis compared patients' mean daily oral glucocorticoid (prednisone equivalent) dose over the 6 months preindex versus 6 months post index. An exploratory analysis assessed glucocorticoid doses at 12 and 24 months post index for patients with extended follow‐up. Results Of the 1987 patients receiving their first belimumab prescription, 767 had available glucocorticoid prescribing data, whereas 204 (primary analysis population) had glucocorticoids prescribed in the 6 months preindex and received belimumab according to the prescribing information for the first 8 weeks post index. The mean (SD) glucocorticoid dose was 12.5 (13.5) mg/day 3 months preindex, reducing to 10.3 (10.6) mg/day over the 6 months post index, and 8.7 (9.4) and 9.0 (9.3) mg/day at 12 and 24 months post index. Conclusion This study showed reductions in mean daily glucocorticoid dose after belimumab initiation. Several limitations of EHRs for real‐world effectiveness research were identified, which limited interpretation of results and may inform future study designs.

Objectives Type I interferon (IFN) plays a role in the pathogenesis of systemic lupus erythematosus (SLE), but insufficient attention has been directed to the differences in IFN responses between ancestral populations. Here, we explored the expression of the interferon gene signatures (IGSs) in SLE patients of European ancestry (EA) and Asian ancestry (AsA).Methods We used gene set variation analysis with multiple IGS encompassing the response to both type 1 and type 2 IFN in isolated CD14+ monocytes, CD19+B cells, CD4+T cells and Natural Killer (NK) cells from patients with SLE stratified by self-identified ancestry. The expression of genes upstream of the IGS and influenced by lupus-associated risk alleles was also examined. Lastly, we employed machine learning (ML) models to assess the most important features classifying patients by disease activity.Results AsA patients with SLE exhibited greater enrichment in the IFN core and IFNA2 IGS compared with EA patients in all cell types examined and, in the presence and absence of autoantibodies. Overall, AsA patients with SLE demonstrated higher expression of genes upstream of the IGS than EA counterparts. ML with feature importance analysis indicated that IGS expression in NK cells, anti-dsDNA, complement levels and AsA status contributed to disease activity.Conclusions AsA patients with SLE exhibited higher IGS than EA patients in all cell types regardless of autoantibody status, with enhanced expression of genetically associated genes upstream of the IGS potentially contributing. AsA, along with the IGS in NK cells, anti-dsDNA and complement, independently influenced SLE disease activity.

Objectives Patients with systemic lupus erythematosus (SLE) have a high risk of cardiovascular disease that could potentially increase postoperative major adverse cardiac events (MACE). We determined the rate of MACE in patients with SLE undergoing noncardiac surgery using national claims‐based data. Methods This was a retrospective cohort study using Optum Clinformatics Data Mart from 2007 to 2020. We identified a cohort of patients with SLE who had undergone noncardiac surgeries using Current Procedural Terminology codes. We also identified two control cohorts without SLE, one with diabetes mellitus (DM) and one without DM. After matching cases and controls by age and sex, the odds of MACE were estimated using multivariable logistic regression models also including race and the Revised Cardiac Risk Index (RCRI) scores. We also examined use of preoperative cardiac testing. Results We identified 4750 patients with SLE, 496,381 DM controls, and 1,484,986 non‐DM controls. After matching, the odds ratio (OR) for MACE in patients with SLE versus non‐DM controls was 1.51 (95% confidence interval 1.09‐2.08), which decreased after adjustment for RCRI score (OR: 0.97, 95% confidence interval 0.7‐1.36). No significant differences were observed in the incidence of MACE between patients with SLE and DM controls (0.82 vs 1.04, P = 0.16). High‐risk patients with SLE (RCRI score of ≥3) were less likely to receive preoperative cardiac testing than non‐DM controls (42.7% vs 35.1%, P

Objective To evaluate the impact of telemedicine use during the coronavirus disease 2019 (COVID‐19) pandemic on rheumatology trainees. Methods A voluntary, anonymous, web‐based survey was administered in English, Spanish, or French from August 19 to October 5, 2020. Adult and pediatric rheumatology trainees were invited to participate via social media and email. Using multiple‐choice questions and Likert scales, the survey assessed prior and current telemedicine use, impact on training, and supervision after COVID‐19 prompted rapid telemedicine implementation. Results Surveys were received from 302 trainees from 33 countries, with 83% in adult rheumatology training programs. Reported telemedicine use increased from 13% before the pandemic to 82% during the pandemic. United States trainees predominantly used video visits, whereas outside the United States telemedicine was predominantly audio only. Most (65%) evaluated new patients using telemedicine. More respondents were comfortable using telemedicine for follow‐up patients (69%) than for new patients (25%). Only 39% of respondents reported receiving telemedicine‐focused training, including instruction on software, clinical skills, and billing, whereas more than half of United States trainees (59%) had training. Postconsultation verbal discussion was the most frequent form of supervision; 24% reported no supervision. Trainees found that telemedicine negatively impacted supervision (50%) and the quality of clinical teaching received (70%), with only 9% reporting a positive impact. Conclusions Despite widespread uptake of telemedicine, a low proportion of trainees received telemedicine training, and many lacked comfort in evaluating patients, particularly new patients. Inadequate supervision and clinical teaching were areas of concern. If telemedicine remains in widespread use, ensuring appropriate trainee supervision and teaching should be prioritized.

Experts have noted a concerning gap between clinical natural language processing (NLP) research and real-world applications, such as clinical decision support. To help address this gap, in this viewpoint, we enumerate a set of practical considerations for developing an NLP system to support real-world clinical needs and improve health outcomes. They include determining (1) the readiness of the data and compute resources for NLP, (2) the organizational incentives to use and maintain the NLP systems, and (3) the feasibility of implementation and continued monitoring. These considerations are intended to benefit the design of future clinical NLP projects and can be applied across a variety of settings, including large health systems or smaller clinical practices that have adopted electronic medical records in the United States and globally.

Objectives We compared the outcomes of patients with or without systemic lupus erythematosus (SLE) who were diagnosed with coronavirus disease 19 (COVID-19) and evaluated factors within patients with SLE associated with severe outcomes.Methods This retrospective cohort study used the deidentified Optum COVID-19 electronic health record dataset to identify patients with COVID-19 from 1/1/2020 to 31/12/2020. Cases with SLE were matched with general controls at a ratio of 1:10 by age, sex, race and ethnicity and COVID-19 diagnosis date. Outcomes included 30-day mortality, mechanical ventilation, hospitalisation and intensive care unit admission. We evaluated the relationship between COVID-19-related outcomes and SLE using multivariable logistic regression. In addition, within SLE cases, we examined factors associated with COVID-19 related outcomes, including disease activity and SLE therapy.Results We included 687 patients matched with 6870 controls. Unadjusted rates of outcomes for patients with SLE were significantly worse than for matched controls including mortality (3.6% vs 1.8%), mechanical ventilation (6% vs 2.5%) and hospitalisation (31% vs 17.7%) (all p

Objective Individuals with autoimmune rheumatic disease (RD) are considered to be at increased risk for infection. However, few US population‐based studies have assessed whether these patients are at increased risk of hospitalization or death due to COVID‐19 compared with those without RD. Methods We performed a retrospective cohort study using national Veterans Affairs Health Care System data for individuals who tested positive for SARS‐CoV‐2. Outcomes of interest were hospitalization or death due to any cause within 30 days of COVID‐19 diagnosis. Outcomes were compared among veterans with RD and those without RD by using propensity score matching (PSM) and mixed‐effects multivariate logistic regression. Results Of 26,116 veterans with COVID‐19, 501 (1.9%) had an underlying RD. Prior to matching, patients with RD were more likely to have poor outcomes compared with controls (37.7% vs. 28.5% hospitalized; 6.4% vs. 4.5% died). In the PSM analysis, RD was not a significant predictor for poor outcomes; however, patients with prescriptions for glucocorticoids had increased odds of poor outcomes in a dose‐dependent manner (odds ratio [95% confidence interval] for hospitalization or death: 1.33 [1.20‐1.48] for doses >0 and ≤10 mg/day; 1.29 [1.09‐1.52] for doses >10 mg/day). Conclusion Among US veterans with COVID‐19, we did not find a significant association between RD and hospitalization or death. Poor outcomes appear to be mostly driven by age and other comorbidities, similar to the general veteran population. However, we observed an increased risk for poor outcomes among patients who received glucocorticoids, even at daily doses less than or equal to 10 mg.

Objective Patient‐reported outcomes (PROs) are an integral part of treat‐to‐target approaches in managing rheumatoid arthritis (RA). In clinical practice, however, routine collection, documentation, and discussion of PROs with patients are highly variable. The RISE LC (Rheumatology Informatics System for Effectiveness Learning Collaborative) was established to develop and share best practices in PRO collection and use across adult rheumatology practices in the United States Methods The goals of the RISE LC were developed through site surveys and in‐person meetings. Participants completed a baseline survey on PRO collection and use in their practices. RISE LC learning sessions focused on improving communication around PROs with patients and enhancing shared decision‐making in treatment plans. During the coronavirus disease 2019 (COVID‐19) pandemic, the RISE LC pivoted to adapt PRO tools for telehealth. Results At baseline, all responding sites (n = 15) had established workflows for collecting PROs. Most sites used paper forms alone. PRO documentation in electronic health records was variable, with only half of the sites using structured data fields. To standardize and improve the use of PROs, participants iteratively developed a Clinical Disease Activity Index–based RA Disease Activity Communication Tool to solicit treatment goals and improve shared decision‐making across sites. The COVID‐19 pandemic necessitated developing a tool to gauge PROs via telehealth. Conclusion The RISE LC is a continuous, structured method for implementing strategies to improve PRO collection and use in rheumatological care, initially adapting from the Learning Collaborative model and extending to include features of a learning network. Future directions include measuring the impact of standardized PRO collection and discussion on shared decision‐making and RA outcomes.

Objectives To investigate factors associated with severe COVID-19 in people with idiopathic inflammatory myopathy (IIM).Methods Demographic data, clinical characteristics and COVID-19 outcome severity of adults with IIM were obtained from the COVID-19 Global Rheumatology Alliance physician-reported registry. A 3-point ordinal COVID-19 severity scale was defined: (1) no hospitalisation, (2) hospitalisation (and no death) and (3) death. ORs were estimated using multivariable ordinal logistic regression. Sensitivity analyses were performed using a 4-point ordinal scale: (1) no hospitalisation, (2) hospitalisation with no oxygen (and no death), (3) hospitalisation with oxygen/ventilation (and no death) and 4) death.Results Of 348 patients, 48% were not hospitalised, 39% were hospitalised (and did not die) and 13% died. Older age (OR=1.59/decade, 95% CI 1.31 to 1.91), high disease activity (OR=3.50, 95% CI 1.25 to 9.83; vs remission), ≥2 comorbidities (OR=2.63, 95% CI 1.39 to 4.98; vs none), prednisolone-equivalent dose >7.5 mg/day (OR=2.40, 95% CI 1.09 to 5.28; vs no intake) and exposure to rituximab (OR=2.71, 95% CI 1.28 to 5.72; vs conventional synthetic disease-modifying antirheumatic drugs only) were independently associated with severe COVID-19. In addition to these variables, in the sensitivity analyses, male sex (OR range: 1.65–1.83; vs female) was also significantly associated with severe outcomes, while COVID-19 diagnosis after 1 October 2020 (OR range: 0.51–0.59; vs on/before 15 June 2020) was significantly associated with less severe outcomes, but these associations were not significant in the main model (OR=1.57, 95% CI 0.95 to 2.59; and OR=0.61, 95% CI 0.37 to 1.00; respectively).Conclusions This is the first large registry data on outcomes of COVID-19 in people with IIM. Older age, male sex, higher comorbidity burden, high disease activity, prednisolone-equivalent dose >7.5 mg/day and rituximab exposure were associated with severe COVID-19. These findings will enable risk stratification and inform management decisions for patients with IIM.

Objective We investigated prolonged COVID-19 symptom duration, defined as lasting 28 days or longer, among people with systemic autoimmune rheumatic diseases (SARDs).Methods We analysed data from the COVID-19 Global Rheumatology Alliance Vaccine Survey (2 April 2021–15 October 2021) to identify people with SARDs reporting test-confirmed COVID-19. Participants reported COVID-19 severity and symptom duration, sociodemographics and clinical characteristics. We reported the proportion experiencing prolonged symptom duration and investigated associations with baseline characteristics using logistic regression.Results We identified 441 respondents with SARDs and COVID-19 (mean age 48.2 years, 83.7% female, 39.5% rheumatoid arthritis). The median COVID-19 symptom duration was 15 days (IQR 7, 25). Overall, 107 (24.2%) respondents had prolonged symptom duration (≥28 days); 42/429 (9.8%) reported symptoms lasting ≥90 days. Factors associated with higher odds of prolonged symptom duration included: hospitalisation for COVID-19 vs not hospitalised and mild acute symptoms (age-adjusted OR (aOR) 6.49, 95% CI 3.03 to 14.1), comorbidity count (aOR 1.11 per comorbidity, 95% CI 1.02 to 1.21) and osteoarthritis (aOR 2.11, 95% CI 1.01 to 4.27). COVID-19 onset in 2021 vs June 2020 or earlier was associated with lower odds of prolonged symptom duration (aOR 0.42, 95% CI 0.21 to 0.81).Conclusion Most people with SARDs had complete symptom resolution by day 15 after COVID-19 onset. However, about 1 in 4 experienced COVID-19 symptom duration 28 days or longer; 1 in 10 experienced symptoms 90 days or longer. Future studies are needed to investigate the possible relationships between immunomodulating medications, SARD type/flare, vaccine doses and novel viral variants with prolonged COVID-19 symptoms and other postacute sequelae of COVID-19 among people with SARDs.

Abstract Background Behçet’s disease (BD), a chronic systemic vasculitis, has distinct geographical and ethnic variation. Data regarding the epidemiology of patients with BD in the U.S. are limited; therefore, we sought to describe BD patient characteristics and medication use in the U.S., and compared them with data from patients from endemic regions. Methods We conducted a cross-sectional study using data from the RISE registry (2014–2018). Patients aged ≥ 18 years with BD were included. Sociodemographic and treatment information was extracted. We compared patients from the RISE registry to data from other published studies of patients with BD from endemic areas. Results One thousand three hundred twenty-three subjects with BD from the RISE registry were included. Mean age was 48.7 ± 16.3 years, female to male ratio was 3.8:1, and 66.7% were White. The most frequently used medications included glucocorticoids (67.6%) and colchicine (55.0%). Infliximab and adalimumab were the most used biologics (14.5% and 14.1%, respectively); 3.2% of patients used apremilast. The RISE registry had more women (79.3%), and patients were older compared to previously published BD studies from endemic areas. Methotrexate and TNFi were more commonly reported in RISE (21.8% and 29.4%) compared to studies from Egypt and Turkey. Colchicine, cyclosporine, and cyclophosphamide were more commonly used in cohorts from Egypt, Turkey, and Iran. Conclusions Findings from the largest BD dataset in the U.S. suggest that BD patients are predominantly female. Further research is needed to explore the reasons for the higher prevalence of BD among women in the U.S. and its possible impact on disease severity and management.

Gaia Andreoletti et al. leverage cell-sorted RNA-seq data and machine learning to investigate gene expression patterns in immune cell subtypes purified from Asian and White patients with a medical diagnosis of systemic lupus erythematosus (SLE). They report distinct clinical subtypes of SLE and identify ethnicity- and disease-specific gene clusters, potentially contributing toward the future development of personalized therapeutic strategies for patients with SLE.

Abstract Background Poor patient‐clinician communication around patient‐reported outcomes (PROs) is a barrier to the effective management of rheumatoid arthritis (RA). We aimed to develop an RA ‘dashboard’ that could facilitate conversations about PROs and that would be acceptable to a wide range of patients, including English and Spanish speakers and patients with adequate or limited health literacy. Methods A diverse group of RA patients along with clinicians from two academic rheumatology clinics joined separate focus groups. We solicited feedback and made iterative changes to mock‐ups of an RA dashboard that visualized PROs using a human‐centred design process. We used the thematic analysis method to identify and characterize themes from the focus groups and used these insights to refine the dashboard. Results We conducted six focus groups involving 25 RA patients and three groups with 11 clinicians. Patients and clinicians agreed that the dashboard could enhance communication about PROs and RA disease activity and could promote patient self‐management. Patients varied in their (a) comprehension, (b) preferences for the display and features of the dashboard, and (c) desired uses for the dashboard. Clinicians expressed significant concerns about the logistics of using the dashboard in clinical practice. Conclusion Using principles of human‐centred design, we created an RA dashboard that was well‐accepted among patients and clinicians. The ability to customize the data display is important for tailoring the dashboard to patients with diverse needs and preferences. Special attention should be given to feasibility concerns voiced by clinicians.

Abstract There is a great and growing need to ascertain what exactly is the state of a patient, in terms of disease progression, actual care practices, pathology, adverse events, and much more, beyond the paucity of data available in structured medical record data. Ascertaining these harder-to-reach data elements is now critical for the accurate phenotyping of complex traits, detection of adverse outcomes, efficacy of off-label drug use, and longitudinal patient surveillance. Clinical notes often contain the most detailed and relevant digital information about individual patients, the nuances of their diseases, the treatment strategies selected by physicians, and the resulting outcomes. However, notes remain largely unused for research because they contain Protected Health Information (PHI), which is synonymous with individually identifying data. Previous clinical note de-identification approaches have been rigid and still too inaccurate to see any substantial real-world use, primarily because they have been trained with too small medical text corpora. To build a new de-identification tool, we created the largest manually annotated clinical note corpus for PHI and develop a customizable open-source de-identification software called Philter (“Protected Health Information filter”). Here we describe the design and evaluation of Philter, and show how it offers substantial real-world improvements over prior methods.

Objective Examinations of Patient‐Reported Outcomes Measurement Information System (PROMIS) measures in adult systemic lupus erythematosus (SLE) have provided support for their cross‐sectional validity in SLE. We estimated responsiveness to change, meaningful changes (minimally important differences [MIDs]), and the patient acceptable symptom state (PASS) for five PROMIS short forms to facilitate longitudinal use and interpretation of PROMIS scales in SLE. Methods Data from five administrations of PROMIS short forms in the FORWARD SLE cohorts were used. Pearson correlation coefficients were used to assess associations between changes in PROMIS measures and changes in anchor measures for responsiveness analyses. Worse, same, or better groups were defined for each anchor. Differences in PROMIS scores were calculated for each consecutive PROMIS administration; mean changes in PROMIS scores of individuals in the worse, same, and better groups were calculated. Both anchor‐based and distribution‐based methods were used to estimate MIDs. PASS was defined as the 75th‐percentile positive score among those who considered their health to be acceptable or who were somewhat or very satisfied with their health. Results All PROMIS short forms showed adequate responsiveness to changes in related patient‐reported outcomes. However, only the fatigue and pain interference scales were responsive to self‐reported SLE activity. Taking into account all methods, we estimated MIDs for each scale to be approximately two points. All PASS values were better than the population mean T‐score of 50. Conclusion These results support use and further study of PROMIS short forms in SLE and should facilitate interpretation of PROMIS scores and changes.

BackgroundRoutine collection of disease activity (DA) and patient-reported outcomes (PROs) in rheumatoid arthritis (RA) are nationally endorsed quality measures and critical components of a treat-to-target approach. However, little is known about the role electronic health record (EHR) systems play in facilitating performance on these measures. ObjectiveUsing the American College Rheumatology’s (ACR’s) RISE registry, we analyzed the relationship between EHR system and performance on DA and functional status (FS) quality measures. MethodsWe analyzed data collected in 2018 from practices enrolled in RISE. We assessed practice-level performance on quality measures that require DA and FS documentation. Multivariable linear regression and zero-inflated negative binomial models were used to examine the independent effect of EHR system on practice-level quality measure performance, adjusting for practice characteristics and patient case-mix. ResultsIn total, 220 included practices cared for 314,793 patients with RA. NextGen was the most commonly used EHR system (34.1%). We found wide variation in performance on DA and FS quality measures by EHR system (median 30.1, IQR 0-74.8, and median 9.0, IQR 0-74.2), respectively). Even after adjustment, NextGen practices performed significantly better than Allscripts on the DA measure (51.4% vs 5.0%; P

Systemic lupus erythematosus (SLE) is an autoimmune disease of substantial phenotypic heterogeneity in different ethnic groups. Here, using data from a multi-ethnic cohort, the authors describe an approach based on clinical and molecular data to subtype SLE patients into three clusters of severity.

ABSTRACT Objective Research using electronic health records (EHRs) may offer advantages over observational prospective cohort studies, including lower costs and a more generalizable patient population; however, EHR data may be more biased because of the high prevalence of missing data. We took advantage of a unique clinical setting in which all patients with rheumatoid arthritis (RA) were asked to participate in a longitudinal cohort study that would examine potential biases of EHR vs. prospective cohort designs in assessment of disease outcomes, but only some chose to participate. Methods For individuals both participating in the cohort (“cohort,” n = 187) and not participating (“noncohort,” n = 190), we retrieved data regarding RA disease activity and other sociodemographic and clinical factors from data recorded in the EHR between 2013 and 2017. We compared the prevalence of missing data between groups and studied differences in disease activity measures over time. Results Disease activity measures were less likely to be missing for cohort participants compared with noncohort participants (0.2%‐13% vs. 2%‐22%, respectively). No significant differences were present at baseline with respect to race/ethnicity or disease activity measures between groups. However, black, non‐Hispanic race/ethnicity was associated with worse longitudinal disease activity compared with white, non‐Hispanic individuals in noncohort participants (β = 6.47, P =0.03) but not in cohort participants (β = −0.10, P = 0.97) (P interaction = 0.09). Conclusion Findings suggest that data derived from the EHR were comparable to a cohort across some variables but captured racial/ethnic disparities in long‐term outcomes not observed in the cohort study. Research utilizing EHR data in conjunction with cohort studies may provide new opportunities for studying health disparities.

Objective To evaluate the risk of stroke and myocardial infarction (MI) in adult patients with systemic lupus erythematosus (SLE) through a systematic review and meta-analysis.Methods We searched MEDLINE and EMBASE from inception to May 2020 to identify observational studies (cohort and cross-sectional) that evaluated risk of stroke and MI in adult patients with SLE compared with the general population or healthy controls. Studies were included if they reported effect-size estimates that could be used for calculating pooled-effect estimates. Random-effects models were used to calculate pooled risk ratios (RRs) and 95% CIs for stroke and MI. Heterogeneity quantified by the I2 test and sensitivity analyses assessed bias.Results In total, 26 studies were included in this meta-analysis: 14, 5 and 7 studies on stroke, MI and both stroke and MI, respectively. The pooled RR for ischaemic stroke was 2.18 (95% CI 1.78 to 2.67; I2 75%), intracerebral haemorrhage 1.84 (95% CI 1.16 to 2.90; I2 67%), subarachnoid haemorrhage 1.95 (95% CI 0.69 to 5.52; I2 94%), composite stroke 2.13 (95% CI 1.73 to 2.61; I2 88%) and MI 2.99 (95% CI 2.34 to 3.82; I2 85%). There was no evidence for publication bias, and sensitivity analyses confirmed the robustness of the results.Conclusions Overall, patients with SLE were identified to have a twofold to threefold higher risk of stroke and MI. Future research on the interaction between known SLE-specific modifiable risk factors and risk of stroke and MI to support development of prevention and treatment strategies are needed.PROSPERO registration number CRD42018098690.

Abstract Background To compare final height to mid-parental target height among adults with childhood-onset systemic lupus erythematosus (cSLE) versus adult-onset SLE (aSLE), and to evaluate the impact of age at SLE onset on final height. Methods Data derived from the Lupus Outcomes Study, a longitudinal cohort of adults with SLE, was used for this cross-sectional analysis (N = 728). Participants aged 18–63 years with complete height data were included (N = 566) and were classified as cSLE if age at diagnosis was 2 SD below target height. Separate analyses were conducted for females and males to account for differences in timing of the pubertal growth spurt for each sex. Results Participants with cSLE were, on average, 2.4 cm shorter than their target height (95% CI -4, − 0.7). The adjusted odds ratio (OR) for substantially reduced final height was 3.9 (95% CI + 2.0, + 7.2, p

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

BackgroundTreatment decision-making regarding immunosuppressive therapy is challenging for individuals with lupus. We assessed the effectiveness of a decision aid for immunosuppressive therapy in lupus nephritis.Methods and findingsIn a United States multicenter, open-label, randomized controlled trial (RCT), adult women with lupus nephritis, mostly from racial/ethnic minority backgrounds with low socioeconomic status (SES), seen in in- or outpatient settings, were randomized to an individualized, culturally tailored, computerized decision aid versus American College of Rheumatology (ACR) lupus pamphlet (1:1 ratio), using computer-generated randomization. We hypothesized that the co-primary outcomes of decisional conflict and informed choice regarding immunosuppressive medications would improve more in the decision aid group. Of 301 randomized women, 298 were analyzed; 47% were African-American, 26% Hispanic, and 15% white. Mean age (standard deviation [SD]) was 37 (12) years, 57% had annual income of ConclusionsAn individualized decision aid was more effective than usual care in reducing decisional conflict for choice of immunosuppressive medications in women with lupus nephritis.Trial registrationClinicaltrials.gov, NCT02319525.

OBJECTIVE:Infection is a leading cause of morbidity and mortality in systemic lupus erythematosus (SLE). Therapeutic practices have evolved over the past 15 years, but effects on infectious complications of SLE are unknown. We evaluated trends in hospitalizations for severe and opportunistic infections in a population-based SLE study. METHODS:Data derive from the 2000 to 2011 United States National Inpatient Sample, including individuals who met a validated administrative definition of SLE. Primary outcomes were diagnoses of bacteremia, pneumonia, opportunistic fungal infection, herpes zoster, cytomegalovirus, or pneumocystis pneumonia (PCP). We used Poisson regression to determine whether infection rates were changing in SLE hospitalizations and used predictive marginals to generate annual adjusted rates of specific infections. RESULTS:We identified 361,337 SLE hospitalizations from 2000 to 2011 meeting study inclusion criteria. Compared to non-SLE hospitalizations, SLE patients were younger (51 vs. 62 years), predominantly female (89% vs. 54%), and more likely to be racial/ethnic minorities. SLE diagnosis was significantly associated with all measured severe and opportunistic infections. From 2000 to 2011, adjusted SLE hospitalization rates for herpes zoster increased more than non-SLE rates: 54 to 79 per 10,000 SLE hospitalizations compared with 24 to 29 per 10,000 non-SLE hospitalizations. Conversely, SLE hospitalizations for PCP disproportionately decreased: 5.1 to 2.5 per 10,000 SLE hospitalizations compared with 0.9 to 1.3 per 10,000 non-SLE hospitalizations. CONCLUSIONS:Among patients with SLE, herpes zoster hospitalizations are rising while PCP hospitalizations are declining. These trends likely reflect evolving SLE treatment strategies. Further research is needed to identify patients at greatest risk for infectious complications.

Co-prescription of folic acid in patients receiving low dose oral methotrexate is recommended because it reduces adverse events and prolongs the use of methotrexate (MTX). However, little is known about how often new users of methotrexate are co-prescribed folic acid, and what factors are associated with its use. We aimed to determine the prevalence, predictors of, and persistence of folic acid use in a population-based cohort of MTX users with rheumatic diseases.Using a national, administrative database of patients seen through the Veterans Health Administration (VHA) that included pharmacy and laboratory data, we performed an observational cohort study of veterans over 65 years old who were new users of MTX. We used log-binomial regression to identify independent predictors of folic acid use and Kaplan Meyer survival analysis to examine persistence of folic acid over time.We studied 2467 incident users of MTX. 27% of patients were not prescribed folic acid through the VHA pharmacy within 30 days of MTX initiation. Patients who did not see a rheumatologist were 23% less likely to receive folic acid compared to patients who did have a rheumatologist visit during the baseline period (RR (95% CI) 0.77 (0.72, 0.82). These results remained unchanged even after adjusting for demographic, clinical, and other factors (adjusted RR (95% CI) 0.78 (0.74, 0.85)). After 20 months, only 50% of patients continued to receive folic acid.In a nationwide VHA cohort of new users of oral MTX, many patients did not receive folic acid or discontinued it over time. Rheumatologists were more likely to prescribe folic acid than other providers. These data highlight the need to improve patient safety for users of methotrexate by standardizing workflows for folic acid supplementation.