Risk Factors for Infection and Health Impacts of the Coronavirus Disease 2019 (COVID-19) Pandemic in People With Autoimmune Diseases
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Abstract
Background
People with autoimmune or inflammatory conditions taking immunomodulatory/suppressive medications may have higher risk of novel coronavirus disease 2019 (COVID-19). Chronic disease care has also changed for many patients, with uncertain downstream consequences.
Methods
We included participants with autoimmune or inflammatory conditions followed by specialists at Johns Hopkins. Participants completed periodic surveys querying comorbidities, disease-modifying medications, exposures, COVID-19 testing and outcomes, social behaviors, and disruptions to healthcare. We assessed whether COVID-19 risk is higher among those on immunomodulating or suppressive agents and characterized pandemic-associated changes to care and mental health.
Results
In total, 265 (5.6%) developed COVID-19 over 9 months of follow-up (April–December 2020). Patient characteristics (age, race, comorbidity, medications) were associated with differences in social distancing behaviors during the pandemic. Glucocorticoid exposure was associated with higher odds of COVID-19 in models incorporating behavior and other potential confounders (odds ratio [OR]: 1.43; 95% confidence interval [CI]: 1.08, 1.89). Other medication classes were not associated with COVID-19 risk. Diabetes (OR: 1.72; 95% CI: 1.08, 2.73), cardiovascular disease (OR: 1.68; 95% CI: 1.24, 2.28), and kidney disease (OR: 1.76; 95% CI: 1.04, 2.97) were associated with higher odds of COVID-19. Of the 2156 reporting pre-pandemic utilization of infusion, mental health or rehabilitative services, 975 (45.2%) reported disruptions therein, which disproportionately affected individuals experiencing changes to employment or income.
Conclusions
Glucocorticoid exposure may increase risk of COVID-19 in people with autoimmune or inflammatory conditions. Disruption to healthcare and related services was common. Those with pandemic-related reduced income may be most vulnerable to care disruptions.
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SciScore for 10.1101/2021.02.03.21251069: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Approval was obtained from the Institutional Review Board at Johns Hopkins Medical Institutions. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:A number of important limitations of our study are worth noting. First, we lacked detailed information on exact timing of COVID-19 infection, so could not incorporate this information into the analyses or assess potential time-varying risk factors …
SciScore for 10.1101/2021.02.03.21251069: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Approval was obtained from the Institutional Review Board at Johns Hopkins Medical Institutions. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:A number of important limitations of our study are worth noting. First, we lacked detailed information on exact timing of COVID-19 infection, so could not incorporate this information into the analyses or assess potential time-varying risk factors or confounding. We also could miss potential COVID-19 cases if participants were loss to follow-up or were not tested for COVID-19 in the Maryland/District of Columbia area, although, follow-up was relatively complete with participants completing a median 8 of 9 follow-up surveys. Further, we used self-reported medications, comorbidities, COVID-19 testing and result status. We also did not collect detailed information on medication dosages (beyond glucocorticoids), which could possibly lead to misclassification. We also identified eligible participants using diagnostic codes, when it is possible that this information may inaccurately identify patients. Nonetheless, we required ≥2 codes for a specific disease/condition from providers in specific specialty departments to reduce potential misclassification. Results are also derived from individuals who responded to our initial survey invitation and may not apply to the larger group of patients; responders were more likely to be white and have higher SES, so it’s possible our results have underestimated the impact of the pandemic in vulnerable groups. Lastly, as for any observational study, the potential for unmeasured confounding cannot be eliminated.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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