Citations

ObjectiveApproximately one third of individuals worldwide have not received a COVID‐19 vaccine. Although studies have investigated risk factors linked to severe COVID‐19 among unvaccinated people with rheumatic diseases (RDs), we know less about whether these factors changed as the pandemic progressed. We aimed to identify risk factors associated with severe COVID‐19 in unvaccinated individuals in different pandemic epochs corresponding to major variants of concern.MethodsPatients with RDs and COVID‐19 were entered into the COVID‐19 Global Rheumatology Alliance Registry between March 2020 and June 2022. An ordinal logistic regression model (not hospitalized, hospitalized, and death) was used with date of COVID‐19 diagnosis, age, sex, race and/or ethnicity, comorbidities, RD activity, medications, and the human development index (HDI) as covariates. The main analysis included all unvaccinated patients across COVID‐19 pandemic epochs; subanalyses stratified patients according to RD types.ResultsAmong 19,256 unvaccinated people with RDs and COVID‐19, those who were older, male, had more comorbidities, used glucocorticoids, had higher disease activity, or lived in lower HDI regions had worse outcomes across epochs. For those with rheumatoid arthritis, sulfasalazine and B‐cell–depleting therapy were associated with worse outcomes, and tumor necrosis factor inhibitors were associated with improved outcomes. In those with connective tissue disease or vasculitis, B‐cell–depleting therapy was associated with worse outcomes.ConclusionRisk factors for severe COVID‐19 outcomes were similar throughout pandemic epochs in unvaccinated people with RDs. Ongoing efforts, including vaccination, are needed to reduce COVID‐19 severity in this population, particularly in those with medical and social vulnerabilities identified in this study.

ObjectiveTo determine the association between race/ethnicity and COVID‐19 outcomes in individuals with systemic lupus erythematosus (SLE).MethodsIndividuals with SLE from the US with data entered into the COVID‐19 Global Rheumatology Alliance registry between March 24, 2020 and August 27, 2021 were included. Variables included age, sex, race, and ethnicity (White, Black, Hispanic, other), comorbidities, disease activity, pandemic time period, glucocorticoid dose, antimalarials, and immunosuppressive drug use. The ordinal outcome categories were: not hospitalized, hospitalized with no oxygenation, hospitalized with any ventilation or oxygenation, and death. We constructed ordinal logistic regression models evaluating the relationship between race/ethnicity and COVID‐19 severity, adjusting for possible confounders.ResultsWe included 523 patients; 473 (90.4%) were female and the mean ± SD age was 46.6 ± 14.0 years. A total of 358 patients (74.6%) were not hospitalized; 40 patients (8.3%) were hospitalized without oxygen, 64 patients (13.3%) were hospitalized with any oxygenation, and 18 (3.8%) died. In a multivariable model, Black (odds ratio [OR] 2.73 [95% confidence interval (95% CI) 1.36–5.53]) and Hispanic (OR 2.76 [95% CI 1.34–5.69]) individuals had higher odds of more severe outcomes than White individuals.ConclusionBlack and Hispanic individuals with SLE experienced more severe COVID‐19 outcomes, which is consistent with findings in the US general population. These results likely reflect socioeconomic and health disparities and suggest that more aggressive efforts are needed to prevent and treat infection in this population.

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.

ObjectiveTo describe people with gout who were diagnosed with coronavirus disease 2019 (COVID‐19) and hospitalized and to characterize their outcomes.MethodsData 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.ResultsOne 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.ConclusionThis 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.

ObjectiveSome 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.MethodsData 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.ResultsThe 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.ConclusionWe 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.

ObjectiveThe relative risk of SARS–CoV‐2 infection and COVID‐19 disease severity among people with rheumatic and musculoskeletal diseases (RMDs) compared to those without RMDs is unclear. This study was undertaken to quantify the risk of SARS–CoV‐2 infection in those with RMDs and describe clinical outcomes of COVID‐19 in these patients.MethodsWe conducted a systematic literature review using 14 databases from January 1, 2019 to February 13, 2021. We included observational studies and experimental trials in RMD patients that described comparative rates of SARS–CoV‐2 infection, hospitalization, oxygen supplementation/intensive care unit (ICU) admission/mechanical ventilation, or death attributed to COVID‐19. Methodologic quality was evaluated using the Joanna Briggs Institute critical appraisal tools or the Newcastle‐Ottawa scale. Risk ratios (RRs) and odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated, as applicable for each outcome, using the Mantel‐Haenszel formula with random effects models.ResultsOf the 5,799 abstracts screened, 100 studies met the criteria for inclusion in the systematic review, and 54 of 100 had a low risk of bias. Among the studies included in the meta‐analyses, we identified an increased prevalence of SARS–CoV‐2 infection in patients with an RMD (RR 1.53 [95% CI 1.16–2.01]) compared to the general population. The odds of hospitalization, ICU admission, and mechanical ventilation were similar in patients with and those without an RMD, whereas the mortality rate was increased in patients with RMDs (OR 1.74 [95% CI 1.08–2.80]). In a smaller number of studies, the adjusted risk of outcomes related to COVID‐19 was assessed, and the results varied; some studies demonstrated an increased risk while other studies showed no difference in risk in patients with an RMD compared to those without an RMD.ConclusionPatients with RMDs have higher rates of SARS–CoV‐2 infection and an increased mortality rate.

ObjectiveAntirheumatic disease therapies have been used to treat coronavirus disease 2019 (COVID‐19) and its complications. We conducted a systematic review and meta‐analysis to describe the current evidence.MethodsA search of published and preprint databases in all languages was performed. Included studies described ≥1 relevant clinical outcome for ≥5 patients who were infected with severe acute respiratory syndrome coronavirus 2 and were treated with antirheumatic disease therapy between January 1, 2019 and May 29, 2020. Pairs of reviewers screened articles, extracted data, and assessed risk of bias. A meta‐analysis of effect sizes using random‐effects models was performed when possible.ResultsThe search identified 3,935 articles, of which 45 were included (4 randomized controlled trials, 29 cohort studies, and 12 case series). All studies evaluated hospitalized patients, and 29 of the 45 studies had been published in a peer‐reviewed journal. In a meta‐analysis of 3 cohort studies with a low risk of bias, hydroxychloroquine use was not significantly associated with mortality (pooled hazard ratio [HR] 1.41 [95% confidence interval (95% CI) 0.83, 2.42]). In a meta‐analysis of 2 cohort studies with some concerns/higher risk of bias, anakinra use was associated with lower mortality (pooled HR 0.25 [95% CI 0.12, 0.52]). Evidence was inconclusive with regard to other antirheumatic disease therapies, and the majority of other studies had a high risk of bias.ConclusionIn this systematic review and meta‐analysis, hydroxychloroquine use was not associated with benefit or harm regarding COVID‐19 mortality. The evidence supporting the effect of other antirheumatic disease therapies in COVID‐19 is currently inconclusive.

Objective IgG4‐related disease (IgG4‐ RD ) can cause fibroinflammatory lesions in nearly any organ. Correlation among clinical, serologic, radiologic, and pathologic data is required for diagnosis. This work was undertaken to develop and validate an international set of classification criteria for IgG4‐ RD . Methods An international multispecialty group of 86 physicians was assembled by the American College of Rheumatology ( ACR ) and the European League Against Rheumatism ( EULAR ). Investigators used consensus exercises, existing literature, derivation and validation cohorts of 1,879 subjects (1,086 cases, 793 mimickers), and multicriterion decision analysis to identify, weight, and test potential classification criteria. Two independent validation cohorts were included. Results A 3‐step classification process was developed. First, it must be demonstrated that a potential IgG4‐ RD case has involvement of at least 1 of 11 possible organs in a manner consistent with IgG4‐ RD . Second, exclusion criteria consisting of a total of 32 clinical, serologic, radiologic, and pathologic items must be applied; the presence of any of these criteria eliminates the patient from IgG4‐ RD classification. Third, 8 weighted inclusion criteria domains, addressing clinical findings, serologic results, radiology assessments, and pathology interpretations, are applied. In the first validation cohort, a threshold of 20 points had a specificity of 99.2% (95% confidence interval [95% CI ] 97.2–99.8%) and a sensitivity of 85.5% (95% CI 81.9–88.5%). In the second, the specificity was 97.8% (95% CI 93.7–99.2%) and the sensitivity was 82.0% (95% CI 77.0–86.1%). The criteria were shown to have robust test characteristics over a wide range of thresholds. Conclusion ACR / EULAR classification criteria for IgG4‐ RD have been developed and validated in a large cohort of patients. These criteria demonstrate excellent test performance and should contribute substantially to future clinical, epidemiologic, and basic science investigations.

ObjectivePatients with antineutrophil cytoplasmic antibody (ANCA)–associated vasculitis (AAV) have an elevated risk of cardiovascular disease (CVD). This study was undertaken to develop a clearer understanding of the association between changes in disease activity and lipid levels in AAV, which may inform CVD risk stratification in this population.MethodsLipid levels were assessed in stored serum samples (obtained at baseline and month 6) from the Rituximab for ANCA‐Associated Vasculitis (RAVE) trial, which randomized patients to receive either rituximab or cyclophosphamide followed by azathioprine. Paired t‐tests and multivariable linear regression were used to assess changes in lipid levels.ResultsOf the 142 patients with serum samples available, the mean ± SD age was 52.3 ± 14.7 years, 72 (51%) were male, 95 (67%) were proteinase 3 (PR3)–ANCA positive, 72 (51%) had received a new diagnosis of AAV, and 75 (53%) were treated with rituximab. Several lipid levels increased between baseline and month 6, including total cholesterol (+12.4 mg/dl [95% confidence interval (95% CI) +7.1, +21.0]), low‐density lipoprotein (+10.3 mg/dl [95% CI +6.1, +17.1]), and apolipoprotein B (+3.5 mg/dl [95% CI +1.0, +8.3]). These changes were observed among newly diagnosed and PR3‐ANCA–positive patients but not among those with relapsing disease or myeloperoxidase‐ANCA–positive patients. There was no difference in change in lipid levels between rituximab‐treated patients and cyclophosphamide‐treated patients. Changes in lipid levels correlated with changes in erythrocyte sedimentation rate but not with other inflammatory markers or glucocorticoid exposure.ConclusionLipid levels increased during remission induction among patients with newly diagnosed AAV and those who were PR3‐ANCA positive. Disease activity and ANCA type should be considered when assessing lipid profiles to stratify CVD risk in patients with AAV.