Factors Associated with Severe COVID-19 Among Patients with Rheumatoid Arthritis: A Large, Nationwide Electronic Health Record Cohort Study in the United States

美国一项基于全国性大型电子健康记录队列研究探讨了类风湿性关节炎患者发生重症 COVID-19 的相关因素

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Abstract

INTRODUCTION: To evaluate factors associated with severe coronavirus disease 2019 (COVID-19) among patients with rheumatoid arthritis (RA) in the US. METHODS: Adults with RA who had a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, based on molecular or antigen test or clinical diagnosis, were identified from the Optum(®) COVID-19 Electronic Health Record dataset (March 1, 2020-April 28, 2021). The primary outcome was the occurrence of severe COVID-19 (hospitalization or death) within 30 days from SARS-CoV-2 infection. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were estimated using multivariable logistic regression models to assess the association between severe COVID-19 and patient characteristics, including demographics, baseline comorbidities, and recent RA treatments. RESULTS: During the study period, 6769 SARS-CoV-2 infections were identified in patients with RA, among whom 1460 (22%) developed severe COVID-19. Multivariable logistic regression analysis showed that being older, male, and non-White and having diabetes and cardiovascular conditions are associated with greater odds of severe COVID-19. In addition, compared with no use, the adjusted odds of severe COVID-19 were lower with recent use of tumor necrosis factor inhibitors (aOR 0.60, 95% CI 0.41-0.86) and higher with recent use of corticosteroids (aOR 1.38, 95% CI 1.13-1.69) or rituximab (aOR 2.87, 95% CI 1.60-5.14), respectively. CONCLUSION: Nearly one in five patients with RA developed severe COVID-19 disease within 30 days after SARS-CoV-2 infection. In patients with RA, recent use of corticosteroids and rituximab were two factors associated with a greater risk of severe COVID-19 in addition to the risk factors among demographics and comorbidities previously identified in the general population.

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