COVID-19 associated autoimmunity is a feature of severe respiratory disease - a Bayesian analysis.
Claudia C dos Santos,
Alex P Di Battista,
Arthur S Slutsky,
Andrew J Baker,
Marvin J Fritzler,
on behalf of the COVID19 Longitudinal Biomarkers of Lung Injury (COLOBILI) study group
Posted 19 Feb 2021
medRxiv DOI: 10.1101/2021.02.17.21251953
Posted 19 Feb 2021
BackgroundSerological and clinical features with similarities to systemic autoimmunity have been reported in severe COVID-19, but there is a lack of studies that include contemporaneous controls who do not have COVID-19. MethodsObservational cohort study of adult patients admitted to an intensive care unit with acute respiratory failure. Patients were divided into COVID+ and COVID- based on SARS-CoV-2 PCR from nasopharyngeal swabs and/or endotracheal aspirates. No COVID-19 specific interventions were given. The primary clinical outcome was death in the ICU within 3 months; secondary outcomes included in-hospital death and disease severity measures. Measurements including autoantibodies, were done longitudinally. ANOVA and Fishers exact test were used with =0.05, with a false discovery rate of q=0.05. Bayesian analysis was performed to provide credible estimates of the possible states of nature compatible with our results. Results22 COVID+ and 20 COVID- patients were recruited, 69% males, median age 60.5 years. Overall, 64% had anti-nuclear antibodies, 38% had antigen-specific autoantibodies, 31% had myositis related autoantibodies, and 38% had high levels of anti-cytokine autoantibodies. There were no statistically significant differences between COVID+ and COVID- for any of the clinical or autoantibody parameters. A specific pattern of anti-nuclear antibodies was associated with worse clinical severity for both cohorts. ConclusionsSevere COVID+ patients have similar humoral autoimmune features as comparably ill COVID- patients, suggesting that autoantibodies are a feature of critical illness regardless of COVID-19 status. The clinical significance of autoimmune serology and the correlation with severity in critical illness remains to be elucidated.
- Downloaded 270 times
- Download rankings, all-time:
- Site-wide: 97,782
- In intensive care and critical care medicine: 205
- Year to date:
- Site-wide: 13,425
- Since beginning of last month:
- Site-wide: 11,401
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!