COVID-19 in patients with autoimmune diseases: characteristics and outcomes in a multinational network of cohorts across three countries

COVID-19 breakthrough infections in type 1 diabetes mellitus: a cross-sectional study by the COVID-19 Vaccination in Autoimmune Diseases (COVAD) Group

To investigate the frequency, profile, and severity of COVID-19 breakthrough infections (BI) in patients with type I diabetes mellitus (T1DM) compared to healthy controls (HC) after vaccination. The second COVID-19 Vaccination in Autoimmune Diseases (COVAD-2) survey is a multinational cross-sectional electronic survey which has collected data on patients suffering from various autoimmune diseases including T1DM. We performed a subgroup analysis on this cohort to investigate COVID-19 BI characteristics in patients with T1DM. Logistic regression with propensity score matching analysis was performed. A total of 9595 individuals were included in the analysis, with 100 patients having T1DM. Among the fully vaccinated cohort, 16 (16%) T1DM patients had one BI and 2 (2%) had two BIs. No morbidities or deaths were reported, except for one patient who required hospitalization with oxygen without admission to intensive care. The frequency, clinical features, and severity of BIs were not significantly different between T1DM patients and HCs after adjustment for confounding factors. Our study did not show any statistically significant differences in the frequency, symptoms, duration, or critical care requirements between T1DM and HCs after COVID-19 vaccination. Further research is needed to identify factors associated with inadequate vaccine response in patients with BIs, especially in patients with autoimmune diseases.

The Stanford Medicine data science ecosystem for clinical and translational research

Objective

To describe the infrastructure, tools, and services developed at Stanford Medicine to maintain its data science ecosystem and research patient data repository for clinical and translational research.

Materials and Methods

The data science ecosystem, dubbed the Stanford Data Science Resources (SDSR), includes infrastructure and tools to create, search, retrieve, and analyze patient data, as well as services for data deidentification, linkage, and processing to extract high-value information from healthcare IT systems. Data are made available via self-service and concierge access, on HIPAA compliant secure computing infrastructure supported by in-depth user training.

Results

The Stanford Medicine Research Data Repository (STARR) functions as the SDSR data integration point, and includes electronic medical records, clinical images, text, bedside monitoring data and HL7 messages. SDSR tools include tools for electronic phenotyping, cohort building, and a search engine for patient timelines. The SDSR supports patient data collection, reproducible research, and teaching using healthcare data, and facilitates industry collaborations and large-scale observational studies.

Discussion

Research patient data repositories and their underlying data science infrastructure are essential to realizing a learning health system and advancing the mission of academic medical centers. Challenges to maintaining the SDSR include ensuring sufficient financial support while providing researchers and clinicians with maximal access to data and digital infrastructure, balancing tool development with user training, and supporting the diverse needs of users.

Conclusion

Our experience maintaining the SDSR offers a case study for academic medical centers developing data science and research informatics infrastructure.

Transforming the Information System for Research in Primary Care (SIDIAP) in Catalonia to the OMOP Common Data Model and Its Use for COVID-19 Research

Purpose

The primary aim of this work was to convert the Information System for Research in Primary Care (SIDIAP) from Catalonia, Spain, to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Our second aim was to provide a descriptive analysis of COVID-19-related outcomes among the general population.

Patients and Methods

We mapped patient-level data from SIDIAP to the OMOP CDM and we performed more than 3,400 data quality checks to assess its readiness for research. We established a general population cohort as of the 1st March 2020 and identified outpatient COVID-19 diagnoses or tested positive for, hospitalised with, admitted to intensive care units (ICU) with, died with, or vaccinated against COVID-19 up to 30th June 2022.

Results

After verifying the high quality of the transformed dataset, we included 5,870,274 individuals in the general population cohort. Of those, 604,472 had either an outpatient COVID-19 diagnosis or positive test result, 58,991 had a hospitalisation, 5,642 had an ICU admission, and 11,233 died with COVID-19. A total of 4,584,515 received a COVID-19 vaccine. People who were hospitalised or died were more commonly older, male, and with more comorbidities. Those admitted to ICU with COVID-19 were generally younger and more often male than those hospitalised and those who died.

Conclusion

We successfully transformed SIDIAP to the OMOP CDM. From this dataset, a general population cohort of 5.9 million individuals was identified and their COVID-19-related outcomes over time were described. The transformed SIDIAP database is a valuable resource that can enable distributed network research in COVID-19 and beyond.

COVID-19 Among Patients with Psoriasis: A Single-Center Retrospective Cross-Sectional Study

Objective

Psoriasis patients may have been affected by COVID-19 differently than the normal population due to using different types of treatments, including immunosuppressive agents and biological therapies, the probability of lower effectiveness, and different side effects of the vaccines. This study aimed to evaluate the epidemiologic and clinical features of COVID-19 and the effect of the psoriasis treatment on it.

Materials and Methods

Psoriasis patients followed up in our clinic between March 2020 and July 2022 were evaluated in terms of clinicodemographic characteristics, treatment methods, and COVID-19 vaccination status and compared regarding COVID-19 history.

Results

A total of 110 patients (female:male ratio=1:1.2) with a mean age of 45.6±14.3 years were evaluated. Thirty patients (27.2%) developed COVID-19 during psoriasis treatment. Unvaccinated patients had COVID-19 (6/11, 55%) more frequently than vaccinated ones (24/99, 24%), but it was not statistically significant (p=0.067). Although patients who received biological therapy were also more frequently infected with SARS-CoV-2 than patients who received other types of therapies (18/53 [34%] versus 12/57 [21%], respectively), the difference was again not statistically significant.A patient with hypertension using acitretin was hospitalized for pulmonary involvement because of COVID-19. No exacerbation of psoriasis was observed in patients who developed COVID-19, while psoriasis flares occurred following COVID-19 mRNA vaccination in two patients.

Conclusion

Patients with psoriasis should get vaccinated against COVID-19, as vaccination prevents the disease and does not result in serious side effects. Although using biological agents for the treatment of psoriasis could be related to a higher risk of getting COVID-19, these agents do not increase the risk of severe COVID-19. Therefore, they may be beneficial in reducing the risk of both psoriasis exacerbations and severe COVID-19 due to the cytokine storm among patients using biological for psoriasis.However, large-scale and controlled studies are needed to support our conclusions.

Prospects of Novel and Repurposed Immunomodulatory Drugs against Acute Respiratory Distress Syndrome (ARDS) Associated with COVID-19 Disease

Acute respiratory distress syndrome (ARDS) is intricately linked with SARS-CoV-2-associated disease severity and mortality, especially in patients with co-morbidities. Lung tissue injury caused as a consequence of ARDS leads to fluid build-up in the alveolar sacs, which in turn affects oxygen supply from the capillaries. ARDS is a result of a hyperinflammatory, non-specific local immune response (cytokine storm), which is aggravated as the virus evades and meddles with protective anti-viral innate immune responses. Treatment and management of ARDS remain a major challenge, first, because the condition develops as the virus keeps replicating and, therefore, immunomodulatory drugs are required to be used with caution. Second, the hyperinflammatory responses observed during ARDS are quite heterogeneous and dependent on the stage of the disease and the clinical history of the patients. In this review, we present different anti-rheumatic drugs, natural compounds, monoclonal antibodies, and RNA therapeutics and discuss their application in the management of ARDS. We also discuss on the suitability of each of these drug classes at different stages of the disease. In the last section, we discuss the potential applications of advanced computational approaches in identifying reliable drug targets and in screening out credible lead compounds against ARDS.

SARS-CoV-2 spike protein promotes inflammatory cytokine activation and aggravates rheumatoid arthritis

BACKGROUND

Coronavirus disease 2019 (COVID-19) induces inflammation, autoantibody production, and thrombosis, which are common symptoms of autoimmune diseases, including rheumatoid arthritis (RA). However, the effect of COVID-19 on autoimmune disease is not yet fully understood.

METHODS

This study was performed to investigate the effects of COVID-19 on the development and progression of RA using a collagen-induced arthritis (CIA) animal model. Human fibroblast-like synoviocytes (FLS) were transduced with lentivirus carrying the SARS-CoV-2 spike protein gene in vitro, and the levels of inflammatory cytokine and chemokine expression were measured. For in vivo experiments, CIA mice were injected with the gene encoding SARS-CoV-2 spike protein, and disease severity, levels of autoantibodies, thrombotic factors, and inflammatory cytokine and chemokine expression were assessed. In the in vitro experiments, the levels of inflammatory cytokine and chemokine expression were significantly increased by overexpression of SARS-CoV-2 spike protein in human FLS.

RESULTS

The incidence and severity of RA in CIA mice were slightly increased by SARS-CoV-2 spike protein in vivo. In addition, the levels of autoantibodies and thrombotic factors, such as anti-CXC chemokine ligand 4 (CXCL4, also called PF4) antibodies and anti-phospholipid antibodies were significantly increased by SARS-CoV-2 spike protein. Furthermore, tissue destruction and inflammatory cytokine level in joint tissue were markedly increased in CIA mice by SARS-CoV-2 spike protein.

CONCLUSIONS

The results of the present study suggested that COVID-19 accelerates the development and progression of RA by increasing inflammation, autoantibody production, and thrombosis. Video Abstract.

Usefulness of linked data for infectious disease events: a systematic review

Surveillance is a key public health function to enable early detection of infectious disease events and inform public health action. Data linkage may improve the depth of data for response to infectious disease events. This study aimed to describe the uses of linked data for infectious disease events. A systematic review was conducted using Pubmed, CINAHL and Web of Science. Studies were included if they used data linkage for an acute infectious disease event (e.g. outbreak of disease). We summarised the event, study aims and designs; data sets; linkage methods; outcomes reported; and benefits and limitations. Fifty-four studies were included. Uses of linkage for infectious disease events included assessment of severity of disease and risk factors; improved case finding and contact tracing; and vaccine uptake, safety and effectiveness. The ability to conduct larger scale population level studies was identified as a benefit, in particular for rarer exposures, risk factors or outcomes. Limitations included timeliness, data quality and inability to collect additional variables. This review demonstrated multiple uses of data linkage for infectious disease events. As infectious disease events occur without warning, there is a need to establish pre-approved protocols and the infrastructure for data-linkage to enhance information available during an event.

COVID-19 vaccination-related adverse events among autoimmune disease patients: results from the COVAD study

OBJECTIVES

COVID-19 vaccines have been proven to be safe in the healthy population. However, gaps remain in the evidence of their safety in patients with systemic autoimmune and inflammatory disorders (SAIDs). COVID-19 vaccination-related adverse events (AEs) in patients with SAIDs and healthy controls (HC) seven days post-vaccination were assessed in the COVAD study, a patient self-reported cross-sectional survey.

METHODS

The survey was circulated in early 2021 by >110 collaborators (94 countries) to collect SAID details, COVID-19 vaccination details and 7-day vaccine AEs, irrespective of respondent vaccination status. Analysis was performed based on data distribution and variable type.

RESULTS

Ten thousand nine hundred respondents [median (interquartile range) age 42 (30-55) years, 74% females and 45% Caucasians] were analysed; 5867 patients (54%) with SAIDs were compared with 5033 HCs. Seventy-nine percent had minor and only 3% had major vaccine AEs requiring urgent medical attention (but not hospital admission) overall. Headache [SAIDs = 26%, HCs = 24%; odds ratio (OR) = 1.1 (95% CI: 1.03, 1.3); P = 0.014], abdominal pain [SAIDs = 2.6%, HCs = 1.4%; OR = 1.5 (95% CI: 1.1, 2.3); P = 0.011], and dizziness [SAIDs = 6%, HCs = 4%; OR = 1.3 (95% CI: 1.07, 1.6); P = 0.011], were slightly more frequent in SAIDs. Overall, major AEs [SAIDs = 4%, HCs = 2%; OR = 1.9 (95% CI: 1.6, 2.2); P < 0.001] and, specifically, throat closure [SAIDs = 0.5%, HCs = 0.3%; OR = 5.7 (95% CI: 2.9, 11); P = 0.010] were more frequent in SAIDs though absolute risk was small (0-4%). Major AEs and hospitalizations (<2%) were comparable across vaccine types in SAIDs.

CONCLUSION

Vaccination against COVID-19 is safe in SAID patients. SAIDs were at a higher risk of major AEs than HCs, though absolute risk was small. There are small differences in minor AEs between vaccine types in SAID patients.

The Course of COVID-19 in Patients with Systemic Autoimmune Rheumatic Diseases

Patients with systemic autoimmune rheumatic disease (SARD) have increased susceptibility to viral infections, including SARS-CoV-2. The aim of this study was to analyse the SARD patient population with COVID-19 (coronavirus disease 2019) in terms of baseline characteristics, severity, course and outcomes of the disease compared with the non-SARD group, and to identify factors associated with prognosis, including remdesivir therapy efficacy. Retrospective study comprised 8220 COVID-19 cases from the SARSTer database, including 185 with SARD. Length of hospitalisation, duration of oxygen therapy, mortality and the need for HFNO (high-flow nasal oxygen) and/or NIV (noninvasive ventilation) were significantly higher in the SARD versus non-SARD group. There was no difference in clinical features on admission to hospital. Patients with SARD were older and more likely to have cardiovascular, pulmonary and chronic kidney diseases. Age, the presence of cardiovascular disease, more severe conditions on admission and higher inflammatory marker values were found to be risk factors for death in the SARD group. In patients with SARD treated with remdesivir, there was a trend towards improved mortality but without statistical significance. Length of hospitalisation, 28-day mortality and the need for HFNO and/or NIV were higher in the SARD group. These patients often had other chronic diseases and were older.

Machine Learning Techniques to Explore Clinical Presentations of COVID-19 Severity and to Test the Association With Unhealthy Opioid Use: Retrospective Cross-sectional Cohort Study

BACKGROUND

The COVID-19 pandemic has exacerbated health inequities in the United States. People with unhealthy opioid use (UOU) may face disproportionate challenges with COVID-19 precautions, and the pandemic has disrupted access to opioids and UOU treatments. UOU impairs the immunological, cardiovascular, pulmonary, renal, and neurological systems and may increase severity of outcomes for COVID-19.

OBJECTIVE

We applied machine learning techniques to explore clinical presentations of hospitalized patients with UOU and COVID-19 and to test the association between UOU and COVID-19 disease severity.

METHODS

This retrospective, cross-sectional cohort study was conducted based on data from 4110 electronic health record patient encounters at an academic health center in Chicago between January 1, 2020, and December 31, 2020. The inclusion criterion was an unplanned admission of a patient aged ≥18 years; encounters were counted as COVID-19-positive if there was a positive test for COVID-19 or 2 COVID-19 International Classification of Disease, Tenth Revision codes. Using a predefined cutoff with optimal sensitivity and specificity to identify UOU, we ran a machine learning UOU classifier on the data for patients with COVID-19 to estimate the subcohort of patients with UOU. Topic modeling was used to explore and compare the clinical presentations documented for 2 subgroups: encounters with UOU and COVID-19 and those with no UOU and COVID-19. Mixed effects logistic regression accounted for multiple encounters for some patients and tested the association between UOU and COVID-19 outcome severity. Severity was measured with 3 utilization metrics: low-severity unplanned admission, medium-severity unplanned admission and receiving mechanical ventilation, and high-severity unplanned admission with in-hospital death. All models controlled for age, sex, race/ethnicity, insurance status, and BMI.

RESULTS

Topic modeling yielded 10 topics per subgroup and highlighted unique comorbidities associated with UOU and COVID-19 (eg, HIV) and no UOU and COVID-19 (eg, diabetes). In the regression analysis, each incremental increase in the classifier's predicted probability of UOU was associated with 1.16 higher odds of COVID-19 outcome severity (odds ratio 1.16, 95% CI 1.04-1.29; P=.009).

CONCLUSIONS

Among patients hospitalized with COVID-19, UOU is an independent risk factor associated with greater outcome severity, including in-hospital death. Social determinants of health and opioid-related overdose are unique comorbidities in the clinical presentation of the UOU patient subgroup. Additional research is needed on the role of COVID-19 therapeutics and inpatient management of acute COVID-19 pneumonia for patients with UOU. Further research is needed to test associations between expanded evidence-based harm reduction strategies for UOU and vaccination rates, hospitalizations, and risks for overdose and death among people with UOU and COVID-19. Machine learning techniques may offer more exhaustive means for cohort discovery and a novel mixed methods approach to population health.

Risk of COVID-19 infection, hospitalization and mortality in psoriasis patients treated with interleukin-17 inhibitors: A systematic review and meta-analysis

BACKGROUND

Coronavirus disease 2019 (COVID-19) have brought great disaster to mankind, and there is currently no globally recognized specific drug or treatment. Severe COVID-19 may trigger a cytokine storm, manifested by increased levels of cytokines including interleukin-17 (IL-17), so a new strategy to treat COVID-19 may be to use existing IL-17 inhibitors, which have demonstrated efficacy, safety and tolerability in the treatment of psoriasis. However, the use of IL-17 inhibitors in patients with psoriasis during the COVID-19 pandemic remains controversial due to reports that IL-17 inhibitors may increase the risk of respiratory tract infections.

OBJECTIVES

The systematic review and meta-analysis aimed to evaluate the effect of IL-17 inhibitors on the risk of COVID-19 infection, hospitalization, and mortality in patients with psoriasis.

METHODS

Databases (including Embase, PubMed, SCI-Web of Science, Scopus, CNKI, and the Cochrane Library) were searched up to August 23, 2022, for studies exploring differences in COVID-19 outcomes between psoriasis patients using IL-17 inhibitors and those using non-biologics. Two authors independently extracted data and assessed the risk of bias in a double-blind manner. The risk ratios (RRs) and 95% confidence intervals (CIs) were calculated and heterogeneities were determined by the Q test and I 2 statistic. And the numbers needed to treat (NNTs) were calculated to assess the clinical value of IL-17 inhibitors in preventing SARS-CoV-2 infection and treating COVID-19.

RESULTS

Nine observational studies involving 7,106 participants were included. The pooled effect showed no significant differences in the rates of SARS-CoV-2 infection (P = 0.94; I 2 = 19.5%), COVID-19 hospitalization (P = 0.64; I 2 = 0.0%), and COVID-19 mortality (P = 0.32; I 2 = 0.0%) in psoriasis patients using IL-17 inhibitors compared with using non-biologics. Subgroup analyses grouped by age and COVID-19 cases, respectively, revealed consistent results as above. Meanwhile, the pooled NNTs showed no significant differences between the two groups in the clinical value of preventing SARS-CoV-2 infection and treating COVID-19.

CONCLUSION

The use of IL-17 inhibitors in patients with psoriasis does not increase the risk of SARS-CoV-2 infection or worsen the course of COVID-19.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/, identifier CRD42022335195.

Nineteen months into the pandemic, what have we learned about COVID-19-related outcomes in patients with psoriasis?

BACKGROUND

The impact of psoriasis on the outcomes of Coronavirus disease 2019 (COVID-19) is yet to be precisely delineated.

OBJECTIVES

To assess the risk of COVID-19, COVID-19-associated hospitalization, and mortality among patients with psoriasis as compared with age-, sex-, and ethnicity-matched control subjects. In addition, we aim to delineate determinants of COVID-19-associated hospitalization and mortality in patients with psoriasis.

METHODS

A population-based retrospective cohort study was performed to longitudinally follow patients with psoriasis and their matched controls with regard to COVID-19-related outcomes. The risk of COVID-19 infection, COVID-19-associated hospitalization, and mortality were assessed using uni- and multi-variable Cox regression analyses. Determinants of COVID-19-associated hospitalization and mortality were evaluated using multivariable logistic regression analysis.

RESULTS

The study population included 144 304 patients with psoriasis and 144 304 age- and sex-matched control individuals. Patients with psoriasis displayed a slightly elevated risk of SARS-CoV-2 infection (fully-adjusted HR, 1.05; 95% CI, 1.03-1.08; p < 0.001). Relative to controls, patients with psoriasis had comparable multivariate risk of COVID-19-associated hospitalization (fully-adjusted HR, 1.08; 95% CI, 0.99-1.18; p = 0.065) and COVID-19-associated mortality (fully-adjusted HR, 0.88; 95% CI, 0.73-1.05; p = 0.162). When evaluating individuals hospitalized due to COVID-19, patients with psoriasis were more likely to have type-2 diabetes mellitus (adjusted OR, 1.24; 95% CI, 1.03-1.50; p = 0.027) and obesity (adjusted OR, 1.37; 95% CI, 1.13-1.65; p = 0.001) relative to controls.

CONCLUSIONS

While patients with psoriasis are at a higher risk of contracting SARS-CoV-2 infection, they are not more susceptible to the complications of COVID-19.

Correlation between Type I Interferon Associated Factors and COVID-19 Severity

Antiviral type I interferons (IFN) produced in the early phase of viral infections effectively inhibit viral replication, prevent virus-mediated tissue damages and promote innate and adaptive immune responses that are all essential to the successful elimination of viruses. As professional type I IFN producing cells, plasmacytoid dendritic cells (pDC) have the ability to rapidly produce waste amounts of type I IFNs. Therefore, their low frequency, dysfunction or decreased capacity to produce type I IFNs might increase the risk of severe viral infections. In accordance with that, declined pDC numbers and delayed or inadequate type I IFN responses could be observed in patients with severe coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as compared to individuals with mild or no symptoms. Thus, besides chronic diseases, all those conditions, which negatively affect the antiviral IFN responses lengthen the list of risk factors for severe COVID-19. In the current review, we would like to briefly discuss the role and dysregulation of pDC/type I IFN axis in COVID-19, and introduce those type I IFN-dependent factors, which account for an increased risk of COVID-19 severity and thus are responsible for the different magnitude of individual immune responses to SARS-CoV-2.

Reporting of COVID-19 Reinfection and Potential Role of Immunosuppressant/Immunomodulating Agents: A Cross-Sectional Observational Analysis Based on a Spontaneous Reporting Database

BACKGROUND

The enduring presence of COVID-19 and subsequent increasing incidence of COVID-19 reinfection has prompted evaluation of associated risk factors, particularly the role of immunosuppression.

OBJECTIVE

The objective of this study was to characterize cases indicative of COVID-19 reinfection with respect to their reported use of immunosuppressant/immunomodulating agents.

METHODS

This cross-sectional observational study leveraged the Pfizer global safety database (SDB) containing adverse event data collected in association with use of Pfizer products between 1 October 2019, and 30 June 2022. Selected Medical Dictionary for Drug Regulatory Activities (MedDRA^®) Preferred Terms were used to identify COVID-19 cases; the search was further refined to comprise cases that subsequently reported events potentially indicative of COVID-19 reinfection.

RESULTS

Of the cumulative total of 218,242 COVID-19 cases reported into the SDB, 4590 cases (2.1%) involving potential COVID-19 reinfection were identified. Of these 4590 cases of potential Covid-19 reinfection, a total of 134 cases reported COVID-19 specifically during treatment with pharmaceutical products, of which approximately 16% (21/134) of cases reported use of immunosuppressant/immunomodulating agents. Likewise, in the overall dataset (213,652 cases; excluding the 4590 cases involving potential COVID-19 recurrence), the percentage of reported immunosuppressant/immunomodulating agents was low (12%). In applying similar parameters to a dataset that excludes COVID-19 vaccine cases, 18% of cases reported use of immunosuppressant/immunomodulating agents (similar to the aforementioned 16% of cases reported from the overall total dataset that was inclusive of vaccine cases).

CONCLUSION

This pharmacovigilance study provides a characterization of cases indicative of COVID-19 reinfection with respect to reported use of immunosuppressant/immunomodulating agents. The observations generated from this cross-sectional observational analysis may prompt further research into the role of immunosuppression in COVID-19 reinfection, in an effort to better inform clinical practice and patient management.

COVID-19 among patients with giant cell arteritis: a single-centre observational study from Slovenia

OBJECTIVES

Patients with giant cell arteritis (GCA) represent a fragile population with an increased infection risk. In a recent study, older age, a higher number of comorbidities, higher disease activity and prednisolone ≥ 10 mg/day were associated with worse COVID-19 outcome. We aimed to evaluate the frequency and severity of COVID-19 in a well-defined GCA cohort.

METHODS

We reviewed medical records of histologically and/or by imaging-proven GCA patients diagnosed between September 2011 and February 2020 at our secondary/tertiary centre and followed during the COVID-19 pandemic between March 2020 and February 2022 (24 months). Descriptive statistics were used to explore the studied population.

RESULTS

Of 314 patients with GCA diagnosed for the first time during a 102-month period, 49 patients died before March 2020. Of the remaining 265 patients, 55 (20.8%) patients suffered from a total of 57 SARS-CoV-2 infections. We observed 44 (77.2%) mild and 13 (22.8%) severe COVID-19 episodes (the latter defined as needing hospitalization, death or thrombotic complication). Patients with severe COVID-19 were more likely to have arterial hypertension (12 [92.3%] vs. 25 [56.8%]; p = 0.022), cardiovascular disease (7 [53.8%] vs. 10 [22.7%]; p = 0.043) or obesity (5 [38.5%] vs. 5 [11.4%]; p = 0.038). Neither prednisolone dose 1-5 mg/day (p = 0.483) nor leflunomide use (p = 1.000) was associated with COVID-19 course. There were no significant differences in sex, age, GCA type, GCA disease duration and other comorbidities in patients with mild and severe COVID-19 in our cohort.

CONCLUSION

More than a fifth of our GCA patients had severe COVID-19. Treatment with leflunomide or low doses of glucocorticoids were not associated with severe course in our cohort. Key Points • Treatment with leflunomide or low doses of glucocorticoids were not associated with worse COVID-19 outcome. • Outcomes of COVID-19 improved as the COVID-19 pandemic, prevention and treatment options evolved. • Arterial hypertension, cardiovascular disease or obesity were associated with severe COVID-19.

COVID-19 disease and autoimmune disorders: A mutual pathway

Coronavirus disease 2019 (COVID-19) is a real challenge for humanity with high morbidity and mortality. Despite being primarily a respiratory illness, COVID-19 can affect nearly every human body tissue, causing many diseases. After viral infection, the immune system can recognize the viral antigens presented by the immune cells. This immune response is usually controlled and terminated once the infection is aborted. Nevertheless, in some patients, the immune reaction becomes out of control with the development of autoimmune diseases. Several human tissue antigens showed a strong response with antibodies directed against many severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins, such as SARS-CoV-2 S, N, and autoimmune target proteins. The immunogenic effects of SARS-CoV-2 are due to the sizeable viral RNA molecules with interrupted transcription increasing the pool of epitopes with increased chances of molecular mimicry and interaction with the host immune system, the overlap between some viral and human peptides, the viral induced-tissue damage, and the robust and complex binding between sACE-2 and SARS-CoV-2 S protein. Consequently, COVID-19 and its vaccine may trigger the development of many autoimmune diseases in a predisposed patient. This review discusses the mutual relation between COVID-19 and autoimmune diseases, their interactive effects on each other, the role of the COVID-19 vaccine in triggering autoimmune diseases, the factors affecting the severity of COVID-19 in patients suffering from autoimmune diseases, and the different ways to minimize the risk of COVID-19 in patients with autoimmune diseases.

Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS

Purpose

Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.

Patients and Methods

We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services.

Results

We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed.

Conclusion

We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.

Risk of Severe COVID-19 Outcomes Among Patients with Immune-Mediated Inflammatory Diseases or Malignancies: A Retrospective Analysis of Real-World Data in the United States

INTRODUCTION

There are concerns that patients in an immunocompromised state may be at risk for increased coronavirus disease 2019 (COVID-19) severity. The aim of this study was to describe the characteristics of patients with COVID-19 and immune-mediated inflammatory diseases (IMIDs) or malignancies and evaluate their risk of developing severe COVID-19.

METHODS

Cases of COVID-19 (ICD-10 code U07.1 or U07.2, or positive polymerase chain reaction or antigen test) among patients with IMIDs or malignancies were identified in the US-based Optum^® Electronic Health Records database between 1 February 2020 and 3 March 2021. Age- and sex-standardized risks of severe COVID-19 were calculated by condition of interest. The risks were further adjusted by multiple covariates, and 95% confidence intervals were estimated.

RESULTS

A total of 499,772 patients with COVID-19 were identified (mean [SD] age, 46.9 [20.7] years; 57.0% female). Patients with hematologic cancers (adjusted risk ratio [aRR] 2.0, 1.8-2.1), solid tumors (aRR 1.1, 1.1-1.1), or rheumatoid arthritis (aRR 1.2, 1.1-1.3) had a significantly higher risk of severe COVID-19 compared to the general population of patients with COVID-19. Patients with systemic lupus erythematosus (aRR 1.1, 0.9-1.2), psoriasis (aRR 1.0, 0.7-1.2), ulcerative colitis (aRR 0.9, 0.8-1.1), Crohn's disease (aRR 0.9, 0.7-1.0), or ankylosing spondylitis (aRR 0.8, 0.5-1.0) showed a comparable risk of severe COVID-19. Patients with atopic dermatitis (aRR 0.8, 0.7-0.9) or psoriatic arthritis (aRR 0.8, 0.6-1.0) showed a lower risk of severe COVID-19.

CONCLUSIONS

The risk of developing severe COVID-19 varied between the studied IMIDs and malignancies. Patients with hematologic cancers, solid tumors, or rheumatoid arthritis had significantly increased risk for severe COVID-19 compared to the general population. These findings highlight the need to protect and monitor immunocompromised patients such as those with IMIDs or malignancies as part of the strategy to control the pandemic worldwide.

Biologics for Psoriasis During the COVID-19 Pandemic

Coronavirus disease 2019 (COVID-19), a new form of acute infectious respiratory syndrome first reported in 2019, has rapidly spread worldwide and has been recognized as a pandemic by the WHO. It raised widespread concern about the treatment of psoriasis in this COVID-19 pandemic era, especially on the biologics use for patients with psoriasis. This review will summarize key information that is currently known about the relationship between psoriasis, biological treatments, and COVID-19, and vaccination-related issues. We also provide references for dermatologists and patients when they need to make clinical decisions. Currently, there is no consensus on whether biological agents increase the risk of coronavirus infection; however, current research shows that biological agents have no adverse effects on the prognosis of patients with COVID-19 with psoriasis. In short, it is not recommended to stop biological treatment in patients with psoriasis to prevent the infection risk, and for those patients who tested positive for SARS-CoV-2, the decision to pause biologic therapy should be considered on a case-by-case basis, and individual risk and benefit should be taken into account. Vaccine immunization against SARS-CoV-2 is strictly recommendable in patients with psoriasis without discontinuation of their biologics but evaluating the risk-benefit ratio of maintaining biologics before vaccination is mandatory at the moment.

A standardized analytics pipeline for reliable and rapid development and validation of prediction models using observational health data

BACKGROUND AND OBJECTIVE

As a response to the ongoing COVID-19 pandemic, several prediction models in the existing literature were rapidly developed, with the aim of providing evidence-based guidance. However, none of these COVID-19 prediction models have been found to be reliable. Models are commonly assessed to have a risk of bias, often due to insufficient reporting, use of non-representative data, and lack of large-scale external validation. In this paper, we present the Observational Health Data Sciences and Informatics (OHDSI) analytics pipeline for patient-level prediction modeling as a standardized approach for rapid yet reliable development and validation of prediction models. We demonstrate how our analytics pipeline and open-source software tools can be used to answer important prediction questions while limiting potential causes of bias (e.g., by validating phenotypes, specifying the target population, performing large-scale external validation, and publicly providing all analytical source code).

METHODS

We show step-by-step how to implement the analytics pipeline for the question: 'In patients hospitalized with COVID-19, what is the risk of death 0 to 30 days after hospitalization?'. We develop models using six different machine learning methods in a USA claims database containing over 20,000 COVID-19 hospitalizations and externally validate the models using data containing over 45,000 COVID-19 hospitalizations from South Korea, Spain, and the USA.

RESULTS

Our open-source software tools enabled us to efficiently go end-to-end from problem design to reliable Model Development and evaluation. When predicting death in patients hospitalized with COVID-19, AdaBoost, random forest, gradient boosting machine, and decision tree yielded similar or lower internal and external validation discrimination performance compared to L1-regularized logistic regression, whereas the MLP neural network consistently resulted in lower discrimination. L1-regularized logistic regression models were well calibrated.

CONCLUSION

Our results show that following the OHDSI analytics pipeline for patient-level prediction modelling can enable the rapid development towards reliable prediction models. The OHDSI software tools and pipeline are open source and available to researchers from all around the world.

Epidemiology and Clinical Management of Rheumatic Autoimmune Diseases in the COVID-19 Pandemic: A Review

The coronavirus disease 2019 (COVID-19) has been in pandemic for more than 1 year, with serious negative effects produced worldwide. During this period, there have been a lot of studies on rheumatic autoimmune diseases (RADs) combined with COVID-19. The purpose of this study is to review and summarize these experiences. Pubmed, Web of science, Embase and the Cochrane library were searched from January 15, 2020 to July 15, 2021 using RADs and COVID-19 related keywords. Based on a comprehensive review of studies covering 16 countries, the prevalence of COVID-19 does not necessarily increase in RADs patients compared to the general population. In RADs population infected with COVID-19, a high proportion of female patients (54.44~95.2%), elderly patients (≥50y, 48~75.88%), and patients with pre-existing comorbidities (respiratory, 4.8~60.4%; endocrine, 8.52~44.72%; cardiovascular, 15.7~64.73%) were observed, although, this does not appear to have a decisive effect on disease severity. Many anti-rheumatic treatments have been extensively evaluated for their efficacy of treating COVID-19 in RADs patients, with TNF-α inhibitors and IL-6 receptor antagonist receiving more positive reviews. However, there is no conclusive information for most of the therapeutic regimens due to the lack of high-level evidence. Inflammatory markers or neutrophil-lymphocyte-ratio may be applied as indicators for clinical prognosis or therapeutic regimens adjustment. Thus, more research is still needed to address the prevalence, treatment, and clinical monitoring of RADs patients in COVID-19 pandemic.