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Introduction: The COVID-19 vaccination campaign was implemented in Sibu, Malaysia in February 2021. We assessed the effectiveness of the CoronaVac vaccine against severe acute respiratory infections (SARI) hospitalisation associated with laboratory-confirmed SARS-CoV-2 by time since vaccination. Method(s): A test-negative case-control design was employed using a web-based national information system for PCR results of SARS-CoV-2 infection and COVID-19 vaccination, and the hospitalisation dataset in Sibu Hospital. Eligible SARI cases with SARS-CoV-2 RT-PCR positive were matched to those SARI cases with negative RT-PCR tests by age and workplace. Vaccine effectiveness was measured by conditional logistic regression with adjustment for gender, comorbidity, smoking and education level. Result(s): Between 15 March and 30 September 2021, in the dominance of lineages B.1.466.2 and B.1.617.2 (Delta variant), a total of 838 eligible SARI patients were identified. Vaccine effectiveness was 42.4% (95% confidence interval [CI]: -28.3, 74.1), and 76.5% (95% CI: 45.6, 89.8) for partial vaccination (after the first dose through 14 days after the second dose) and complete vaccination (at 15 days or more after receipt of the second dose), respectively. Sensitivity analysis using propensity score matching yielded a conservative estimate of 57.4% (95% CI: 9.2, 80.1) for complete vaccination. Conclusion(s): Primary immunisation with two doses of CoronaVac vaccine provided satisfactory protection against SARI caused by SARS-CoV-2 in the short term. However, the duration of protection, incremental effectiveness induced by boosting, as well as performance against new variants need to be studied continuously.
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Objectives. To determine characteristics associated with a more severe COVID-19 outcome in people with Sjogren's disease (SJD). Methods. People with SJD and COVID-19 reported to two international registries (Sjogren Big Data Consortium and COVID-19 Global Rheumatology Alliance) from March 2020 to October 2021 were included. An ordinal COVID-19 severity scale was defined: (1) not hospitalized, (2) hospitalized with no ventilation, (3) hospitalized requiring non-invasive ventilation, (4) hospitalized requiring invasive ventilation, and (5) death. Odds ratios (OR) were estimated using a multivariable ordinal logistic regression model adjusted for age, sex, comorbidities and anti-rheumatic medications included as covariates. Results. A total of 898 people with SJD were included (825 (91.8%) women, mean age SARS-CoV-2 infection diagnosis: 55.5 years), including 652 patients with primary SJD and 246 with other associated systemic rheumatic diseases. 33.9% were hospitalized, 14.5% required ventilation, and 4.3% died. In the multivariable model, older age (OR 1.03, 95% CI 1.02 to 1.05), male sex (OR 1.81, 95% CI 1.10 to 2.92), two or more comorbidities (OR 2.99, 95% CI 1.92 to 4.67;vs none), baseline therapy with corticosteroids (OR 2.04, 95% CI 1.20 to 3.46), immunosuppressive agents (OR 2.09, 95% CI 1.30 to 3.38) and B-cell depleting agents (OR 5.38, 95% CI 2.77 to 10.47) were associated with worse outcomes (reference for all medications: hydroxychloroquine only). Conclusions. More severe COVID-19 outcomes in individuals with Sjogren's are largely driven by demographic factors and baseline comorbidities. Patients using immunosuppressants, especially rituximab, also experienced more severe outcomes.
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Background: There is a paucity of data in the literature about the outcome of patients with idiopathic infammatory myopathy (IIM) who have been infected with SARS-CoV-2. Objectives: To investigate factors associated with severe COVID-19 outcomes in patients with IIM. Methods: Data on demographics, number of comorbidities, region, COVID-19 time period, physician-reported disease activity, anti-rheumatic medication exposure at the clinical onset of COVID-19, and COVID-19 outcomes of IIM patients were obtained from the voluntary COVID-19 Global Rheumatology Alliance physician-reported registry of adults with rheumatic disease (from 17 March 2020 to 27 August 2021). An ordinal COVID-19 severity scale was used as primary outcome of interest, with each outcome category being mutually exclusive from the other:a) no hospital-ization, b) hospitalization (and no death), or c) death. Odds ratios (OR) were estimated using multivariable ordinal logistic regression. In ordinal logistic regression, the effect size of a categorical predictor can be interpreted as the odds of being one level higher on the ordinal COVID-19 severity scale than the reference category. Results: Complete hospitalization and death outcome data was available in 348 IIM cases. Mean age was 53 years, and 223 (64.1%) were female. Overall, 167/348 (48.0%) people were not hospitalized, 136/348 (39.1%) were hospitalized (and did not die), and 45/348 (12.9%) died. Older age (OR=1.59 per decade of life, 95%CI 1.32-1.93), male sex (OR=1.63, 95%CI 1.004-2.64;versus female), high disease activity (OR=4.05, 95%CI 1.29-12.76;versus remission), presence of two or more comorbidities (OR=2.39, 95%CI 1.22-4.68;versus none), predni-solone-equivalent dose >7.5 mg/day (OR=2.37, 95%CI 1.27-4.44;versus no gluco-corticoid intake), and exposure to rituximab (OR=2.60, 95%CI 1.23-5.47;versus csDMARDs only) were associated with worse COVID-19 outcomes (Table 1). Conclusion: These are the frst global registry data on the impact of COVID-19 on IIM patients. Older age, male gender, higher comorbidity burden, higher disease activity, higher glucocorticoid intake and rituximab exposure were associated with worse outcomes. These fndings will inform risk stratifcation and management decisions for IIM patients.
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Background: Some factors associated with severe COVID-19 outcomes have been identifed in patients with psoriasis (PsO) and infammatory/autoimmune rheumatic diseases, namely older age, male sex, comorbidity burden, higher disease activity, and certain medications such as rituximab. However, information about specifcities of patients with PsO, psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA), including disease modifying anti-rheumatic drugs (DMARDs) specifcally licensed for these conditions, such as IL-17 inhibitors (IL-17i), IL-23/IL-12 + 23 inhibitors (IL-23/IL-12 + 23i), and apremilast, is lacking. Objectives: To determine characteristics associated with severe COVID-19 outcomes in people with PsO, PsA and axSpA. Methods: This study was a pooled analysis of data from two physician-reported registries: the Psoriasis Patient Registry for Outcomes, Therapy and Epidemiology of COVID-19 Infection (PsoProtect), comprising patients with PsO/PsA, and the COVID-19 Global Rheumatology Alliance (GRA) registry, comprising patients with PsA/axSpA. Data from the beginning of the pandemic up to 25 October, 2021 were included. An ordinal severity outcome was defned as: 1) not hospitalised, 2) hospitalised without death, and 3) death. A multivariable ordinal logistic regression model was constructed to assess the relationship between COVID-19 severity and demographic characteristics (age, sex, time period of infection), comorbidities (hypertension, other cardiovascular disease [CVD], chronic obstructive lung disease [COPD], asthma, other chronic lung disease, chronic kidney disease, cancer, smoking, obesity, diabetes mellitus [DM]), rheumatic/skin disease (PsO, PsA, axSpA), physician-reported disease activity, and medication exposure (methotrexate, lefunomide, sulfasalazine, TNFi, IL17i, IL-23/IL-12 + 23i, Janus kinase inhibitors (JAKi), apremilast, glucocorticoids [GC] and NSAIDs). Age-adjustment was performed employing four-knot restricted cubic splines. Country-adjustment was performed using random effects. Results: A total of 5008 individuals with PsO (n=921), PsA (n=2263) and axSpA (n=1824) were included. Mean age was 50 years (SD 13.5) and 51.8% were male. Hospitalisation (without death) was observed in 14.6% of cases and 1.8% died. In the multivariable model, the following variables were associated with severe COVID-19 outcomes: older age (Figure 1), male sex (OR 1.53, 95%CI 1.29-1.82), CVD (hypertension alone: 1.26, 1.02-1.56;other CVD alone: 1.89, 1.22-2.94;vs no hypertension and no other CVD), COPD or asthma (1.75, 1.32-2.32), other lung disease (2.56, 1.66-3.97), chronic kidney disease (2.32, 1.50-3.59), obesity and DM (obesity alone: 1.36, 1.07-1.71;DM alone: 1.85, 1.39-2.47;obesity and DM: 1.89, 1.34-2.67;vs no obesity and no DM), higher disease activity and GC intake (remission/low disease activity and GC intake: 1.96, 1.36-2.82;moderate/severe disease activity and no GC intake: 1.35, 1.05-1.72;moderate/severe disease activity and GC intake 2.30, 1.41-3.74;vs remission/low disease activity and no GC intake). Conversely, the following variables were associated with less severe COVID-19 outcomes: time period after 15 June 2020 (16 June 2020-31 December 2020: 0.42, 0.34-0.51;1 January 2021 onwards: 0.52, 0.41-0.67;vs time period until 15 June 2020), a diagnosis of PsO (without arthritis) (0.49, 0.37-0.65;vs PsA), and exposure to TNFi (0.58, 0.45-0.75;vs no DMARDs), IL17i (0.63, 0.45-0.88;vs no DMARDs), IL-23/IL-12 + 23i (0.68, 0.46-0.997;vs no DMARDs) and NSAIDs (0.77, 0.60-0.98;vs no NSAIDs). Conclusion: More severe COVID-19 outcomes in PsO, PsA and axSpA are largely driven by demographic factors (age, sex), comorbidities, and active disease. None of the DMARDs typically used in PsO, PsA and axSpA, were associated with severe COVID-19 outcomes, including IL-17i, IL-23/IL-12 + 23i, JAKi and apremilast.
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Background: An increased risk of severe COVID-19 outcomes may be seen in patients with autoimmune diseases on moderate to high daily doses of glucocorticoids, as well as in those with comorbidities. However, specific information about COVID-19 outcomes in SLE is scarce. Objectives: To determine the characteristics associated with severe COVID-19 outcomes in a multi-national cross-sectional registry of COVID-19 patients with SLE. Methods: SLE adult patients from a physician-reported registry of the COVID-19 GRA were studied. Variables collected at COVID-19 diagnosis included age, sex, race/ethnicity, region, comorbidities, disease activity, time period of COVID-19 diagnosis, glucocorticoid (GC) dose, and immunomodulatory therapy. Immunomodulatory therapy was categorized as: antimalarials only, no SLE therapy, traditional immunosuppressive (IS) drug monotherapy, biologics/targeted synthetic IS drug monotherapy, and biologic and traditional IS drug combination therapy. We used an ordinal COVID-19 severity outcome defined as: not hospitalized/hospitalized without supplementary oxygen;hospitalized with non-invasive ventilation;hospitalized with mechanical ventilation/extracorporeal membrane oxygenation;and death. An ordinal logistic regression model was constructed to assess the association between demographic characteristics, comorbidities, medications, disease activity and COVID-19 severity. This assumed that the relationship between each pair of outcome groups is of the same direction and magnitude. Results: Of 1069 SLE patients included, 1047 (89.6%) were female, with a mean age of 44.5 (SD: 14.1) years. Patient outcomes included 815 (78.8%) not hospitalized/hospitalized without supplementary oxygen;116 (11.2) hospitalized with non-invasive ventilation, 25 (2.4%) hospitalized with mechanical ventilation/ extracorporeal membrane oxygenation and 78 (7.5%) died. In a multivariate model (n=804), increased age [OR=1.03 (1.01, 1.04)], male sex [OR =1.93 (1.21, 3.08)], COVID-19 diagnosis between June 2020 and January 2021 (OR =1.87 (1.17, 3.00)), no IS drug use [OR =2.29 (1.34, 3.91)], chronic renal disease [OR =2.34 (1.48, 3.70)], cardiovascular disease [OR =1.93 (1.34, 3.91)] and moderate/ high disease activity [OR =2.24 (1.46, 3.43)] were associated with more severe COVID-19 outcomes. Compared with no use of GC, patients using GC had a higher odds of poor outcome: 0-5 mg/d, OR =1.98 (1.33, 2.96);5-10 mg/d, OR =2.88 (1.27, 6.56);>10 mg/d, OR =2.01 (1.26, 3.21) (Table 1). Conclusion: Increased age, male sex, glucocorticoid use, chronic renal disease, cardiovascular disease and moderate/high disease activity at time of COVID-19 diagnosis were associated with more severe COVID-19 outcomes in SLE. Potential limitations include possible selection bias (physician reporting), the cross-sectional nature of the data, and the assumptions underlying the outcomes modelling.
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Background: The COVID-19 pandemic has disrupted healthcare delivery and education of physicians, including rheumatology trainees. Objectives: To assess the impact of the COVID-19 pandemic on the clinical experiences, research opportunities, and well-being of rheumatology trainees. Methods: A voluntary, anonymous, web-based survey was administered in English, Spanish, or French from 19/08/2020 to 05/10/2020. Adult and paediatric rheumatology trainees worldwide in training in 2020 were invited to participate via social media and email. Using multiple choice questions, Likert scales, and free text answers, we assessed trainee patient care activities, redeployment, research, and well-being. Results: The 302 respondents were from 33 countries, with most (83%, 252/302) in adult rheumatology training. Many trainees (45%, 135/300) reported an increase in non-rheumatology clinical work (e.g. care of COVID-19 patients), with 52% of these (70/135) also continuing rheumatology clinical work. COVID-19 redeployment was not optional for 68% (91/134). Trainees reported a negative impact of the pandemic in their growth in rheumatology (Figure 1). They also reported a substantial impact on several training areas: outpatient clinics (79%, 238/302), inpatient consultations (59%, 177/302), formal teaching (55%, 167/302), procedures (53%, 147/302), teaching opportunities (52%, 157/302), and ultrasonography (36%, 110/302), with 87-96% perceiving a negative impact on these areas. Only 54% (159/294) reported feeling comfortable with their level of clinical supervision during the pandemic (Figure 1). Many trainees (46%, 128/280) reported changes in research experiences during the pandemic;39% (110/285) reported that COVID-19 negatively affected their ability to continue their pre-pandemic research and 50% (142/285) reported difficulty maintaining research goals (Figure 1). Some rheumatology trainees reported having health condition(s) putting them at high risk for COVID-19 (10%, 30/302) and 14% of trainees (41/302) reported having had COVID-19 (Table 1). Only 53% (160/302) reported feeling physically safe in the workplace while 25% (76/302) reported not feeling physically safe;reasons included lack of training about COVID-19, lack of comfort in the clinical setting, insufficient personal protective equipment, immunocompromised state, and pregnancy. Half (151/302) reported burnout and 68% (204/302) an increase in stress from work during the pandemic (Figure 1), whilst 25% (75/302) reported that changes to their training programme negatively impacted their physical health. Conclusion: The COVID-19 pandemic has negatively impacted the experience of rheumatology training as well as the well-being of trainees globally. Our data highlight concerns for rheumatology trainees including research opportunities and clinical care which should be a focus for curriculum planning.
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Background: The COVID-19 pandemic led to a rapid increase in remote consultations in rheumatology care. Due to the potential impact of this change on rheumatology clinical training, we investigated trainees' experiences with telemedicine. Objectives: To assess the impact of telemedicine use during the COVID-19 pandemic on rheumatology training, including supervision. Methods: A voluntary, anonymous web-based survey was administered in English, Spanish, or French from 19/08/2020 to 05/10/2020. Adult and paediatric rheumatology trainees worldwide in training in 2020 were invited to participate via social media and email. Using multiple choice questions, Likert scales, and free text answers, we collected data regarding prior and current telemedicine use, training, and supervision. Results: 302 respondents from 33 countries completed the survey, with most (83%, 252/302) in adult rheumatology training. Reported use of telemedicine increased from 13% (39/302) pre-pandemic to 82% (247/302) (Table 1). European trainees predominantly utilised audio-only compared to trainees from the rest of the world (ROW) who predominantly utilised audio-video telemedicine. Most trainees continued to evaluate new patients using telemedicine (65%, 161/247). A larger proportion of trainees were comfortable using telemedicine to evaluate follow-up (69% 170/247) versus new patients (25%, 41/161) (Figure 1). Only 32% (97/302) were trained in telemedicine, with the highest proportion among United States (US) trainees (59%, 69/116);subjects included software, clinical skills, and billing. The majority of trainees found this helpful (92%, 89/97). Supervision was most frequently in the form of verbal discussion after the consultation (Table 1);24% (59/247) had no telemedicine supervision during the pandemic. In general, trainees found telemedicine negatively impacted their supervision (51%, 123/242) and clinical teaching quality (70%, 171/244);only 9% reported a positive impact on these areas. Conclusion: Adoption of telemedicine during the COVID-19 pandemic has led to areas of concern for rheumatology trainees including inadequate supervision and clinical teaching. Our results suggest a need for education on evaluation of new patients using telemedicine, increasing telemedicine training, and ensuring adequate supervisory arrangements.
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Background: Targeted DMARDs may dampen the inflammatory response in COVID-19, perhaps leading to a less severe clinical course. However, some DMARD targets may impair viral immune defenses. Due to sample size limitations, previous studies of DMARD use and COVID-19 outcomes have combined several heterogeneous rheumatic diseases and medications, investigating a single outcome (e.g., hospitalization). Objectives: To investigate the associations of baseline use of biologic or targeted synthetic (b/ts) DMARDs with a range of poor COVID-19 outcomes in rheumatoid arthritis (RA). Methods: We analyzed voluntarily reported cases of COVID-19 in patients with rheumatic diseases in the COVID-19 Global Rheumatology Alliance physician registry (March 12, 2020 -January 6, 2021). We investigated RA treated with b/ tsDMARD at the clinical onset of COVID-19 (baseline): abatacept (ABA), rituximab (RTX), Janus kinase inhibitors (JAK), interleukin-6 inhibitors (IL6i), or tumor necrosis factor inhibitors (TNFi). The outcome was an ordinal scale (1-4) for COVID-19 severity: 1) no hospitalization, 2) hospitalization without oxygen need, 3) hospitalization with any oxygen need or ventilation, or 4) death. Baseline covariates including age, sex, smoking, obesity, comorbidities (e.g., cardiovascular disease, cancer, interstitial lung disease [ILD]), concomitant non-biologic DMARD use, glucocorticoid use/ dose, RA disease activity, country, and calendar time were used to estimate propensity scores (PS) for b/tsDMARD. The primary analysis used PS matching to compare each drug class to TNFi. Ordinal logistic regression estimated ORs for the COVID-19 severity outcome. In a sensitivity analysis, we used traditional multivariable ordinal logistic regression adjusting for covariates without matching. Results: Of the 1,673 patients with RA on b/tsDMARDs at the onset of COVID-19, (mean age 56.7 years, 79.6% female) there were n=154 on ABA, n=224 on RTX, n=306 on JAK, n=180 on IL6i, and n=809 on TNFi. Overall, 498 (34.3%) were hospitalized and 112 (6.7%) died. Among all patients, 353 (25.3%) were ever smokers, 197 (11.8%) were obese, 462 (27.6%) were on glucocorticoids, 1,002 (59.8%) were on concomitant DMARDs, and 299 (21.7%) had moderate/ high RA disease activity. RTX users were more likely than TNFi users to have ILD (11.6% vs. 1.7%) and history of cancer (7.1% vs. 2.0%);JAK users were more likely than TNFi users to be obese (17.3% vs. 9.0%). After propensity score matching, RTX was strongly associated with greater odds of having a worse outcome compared to TNFi (OR 3.80, 95% CI 2.47, 5.85;Figure). Among RTX users, 42 (18.8%) died compared to 27 (3.3%) of TNFi users (Table). JAK use was also associated with greater odds of having a worse COVID-19 severity (OR 1.52, 95%CI 1.02, 2.28). ABA or IL6i use were not associated with COVID-19 severity compared to TNFi. Results were similar in the sensitivity analysis and after excluding cancer or ILD. Conclusion: In this large global registry of patients with RA and COVID-19, baseline use of RTX or JAK was associated with worse severity of COVID-19 compared to TNFi use. The very elevated odds for poor COVID-19 outcomes in RTX users highlights the urgent need for risk-mitigation strategies, such as the optimal timing of vaccination. The novel association of JAK with poor COVID-19 outcomes requires replication.
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Background: Many studies on COVID-19 outcomes in patients with RMD have either restricted to COVID positive RMD patients or compared them to the general clinic population as a comparator. Given heterogeneity in behaviors and risks, clinical characteristics associated with a positive diagnosis among patients with RMD seeking testing for Sars-CoV-2 remain less well studied. Objectives: Among patients with RMD receiving a Sars-CoV-2 PCR test, we aimed to identify RMD-related factors associated with a positive test result. Methods: Among patients seen at least once in the University of Washington (UW) rheumatology clinics between March 2018 to March 2020, we reviewed electronic medical records to identify patients undergoing Sars-CoV-2 PCR testing from March 1 through October 31, 2020. Patients with RMD were categorized into two groups: those who tested positive for Sars-CoV-2 and those who tested negative. We randomly selected patients from the negative group in a 2:1 ratio for further data abstraction. Student's t-test and Chi-squared tests were used to compare continuous and categorical variables, respectively, between the groups. To determine the correlates of testing positive for Sars-CoV-2, specifically RMD medication use and disease activity, we constructed different multivariable logistic regression models adjusted for age, sex, race/ethnicity, presence of comorbidities, body mass index, and smoking. Results: A total of 2768 RMD patients underwent SARS-CoV-2 PCR testing within the UW system, of whom 43 (1.5%) were positive at least once. Three patients with incomplete information were excluded. Patients who tested positive had higher prevalence of end stage renal disease (ESRD)/chronic kidney disease (CKD) (24% versus 11%), had higher rates of active disease (24% versus 20%), were older (>55 years) (mean age 57.3 versus 54.8 years), male (63% versus 55%), non-white race/ethnicity (32% versus 26%), and higher prevalence of multiple comorbidities (42% versus 31%) (Table 1). In the multivariable models, neither RMD medication use (versus no use, Table 1) nor high disease activity (vs low disease activity/remission) were statistically significantly associated with COVID-19 positivity. Among the 41 COVID-19 positive patients, a majority recovered without specific treatments, although approximately one third of the positive patients were hospitalized and three deaths were observed. Conclusion: In this study, patients who tested positive did not differ in many ways from those who tested negative. (Figure Presented).
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Background: Acute Respiratory Distress Syndrome (ARDS) is a life-threatening complication of COVID-19 and has been reported in approximately one-third of hospitalized patients with COVID-191. Risk factors associated with the development of ARDS include older age and diabetes2. However, little is known about factors associated with ARDS in the setting of COVID-19, in patients with rheumatic disease or those receiving immunosuppressive medications. Prediction algorithms using traditional regression methods perform poorly with rare outcomes, often yielding high specificity but very low sensitivity. Machine learning algorithms optimized for rare events are an alternative approach with potentially improved sensitivity for rare events, such as ARDS in COVID-19 among patients with rheumatic disease. Objectives: We aimed to develop a prediction model for ARDS in people with COVID-19 and pre-existing rheumatic disease using a series of machine learning algorithms and to identify risk factors associated with ARDS in this population. Methods: We used data from the COVID-19 Global Rheumatology Alliance (GRA) Registry from March 24 to Nov 1, 2020. ARDS diagnosis was indicated by the reporting clinician. Five machine learning algorithms optimized for rare events predicted ARDS using 42 variables covering patient demographics, rheumatic disease diagnoses, medications used at the time of COVID-19 diagnosis, and comorbidities. Model performance was assessed using accuracy, area under curve, sensitivity, specificity, positive predictive value, and negative predictive value. Adjusted odds ratios corresponding to the 10 most influential predictors from the best performing model were derived using hierarchical multivariate mixed-effects logistic regression that accounted for within-country correlations. Results: A total of 5,931 COVID-19 cases from 67 countries were included in the analysis. Mean (SD) age was 54.9 (16.0) years, 4,152 (70.0%) were female, and 2,399 (40.5%) were hospitalized. ARDS was reported in 388 (6.5% of total and 15.6% of hospitalized) cases. Statistically significant differences in the risk of ARDS were observed by demographics, diagnoses, medications, and comorbidities using unadjusted univariate comparisons (data not shown). Gradient boosting machine (GBM) had the highest sensitivity (0.81) and was considered the best performing model (Table 1). Hypertension, interstitial lung disease, kidney disease, diabetes, older age, glucocorticoids, and anti-CD20 monoclonal antibodies were associated with the development of ARDS while tumor necrosis factor inhibitors were associated with a protective effect (Figure 1). Conclusion: In this global cohort of patients with rheumatic disease, a machine learning model, GBM, predicted the onset of ARDS with 81% sensitivity using baseline information obtained at the time of COVID-19 diagnosis. These results identify patients who may be at higher risk of severe COVID-19 outcomes. Further studies are necessary to validate the proposed prediction model in external cohorts and to evaluate its clinical utility. Disclaimer: The views expressed here are those of the authors and participating members of the COVID-19 Global Rheumatology Alliance, and do not necessarily represent the views of the ACR, NIH, (UK) NHS, NIHR, or the department of Health.
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Background: There is limited data regarding the risk of hospitalisation in patients with rheumatic disease and COVID-19 in Ireland. Objectives: We used the COVID-19 Global Rheumatology Alliance (GRA) registry data to study outcomes and their predictors. Methods: We examined data on patients and their disease-related characteristics entered into the COVID-19 GRA provider registry from Ireland (24th March 2020 to 31st August 2020). Multivariable logistic regression was used to assess the association of demographic and clinical characteristics with hospitalisation. Results: Of 105 patients, 47 (45.6%) were hospitalised and 10 (9.5%) died. Multivariable logistic regression analysis showed age (OR=1.06, 95%CI 1.01 to 1.10), number of comorbidities (OR=1.93, 95%CI 1.11 to 3.35), and glucocorticoid use (OR=15.01, 95%CI 1.77 to 127.16) were significantly associated with hospitalisation. A diagnosis of inflammatory arthritis was associated with a lower odds of hospitalisation (OR=0.09, 95%CI 0.02 to 0.32). Conclusion: Increasing age, comorbidity burden, and glucocorticoid use were associated with hospitalisation, while a diagnosis of inflammatory arthritis was associated with lower odds of hospitalization.