Dataset Information

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

ABSTRACT:

Objective

Patients with autoimmune diseases were advised to shield to avoid coronavirus disease 2019 (COVID-19), but information on their prognosis is lacking. We characterized 30-day outcomes and mortality after hospitalization with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.

Methods

A multinational network cohort study was conducted using electronic health records data from Columbia University Irving Medical Center [USA, Optum (USA), Department of Veterans Affairs (USA), Information System for Research in Primary Care-Hospitalization Linked Data (Spain) and claims data from IQVIA Open Claims (USA) and Health Insurance and Review Assessment (South Korea). All patients with prevalent autoimmune diseases, diagnosed and/or hospitalized between January and June 2020 with COVID-19, and similar patients hospitalized with influenza in 2017-18 were included. Outcomes were death and complications within 30 days of hospitalization.

Results

We studied 133 589 patients diagnosed and 48 418 hospitalized with COVID-19 with prevalent autoimmune diseases. Most patients were female, aged ≥50 years with previous comorbidities. The prevalence of hypertension (45.5-93.2%), chronic kidney disease (14.0-52.7%) and heart disease (29.0-83.8%) was higher in hospitalized vs diagnosed patients with COVID-19. Compared with 70 660 hospitalized with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2-4.3% vs 6.32-24.6%).

Conclusion

Compared with influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality.

SUBMITTER: Tan EH

PROVIDER: S-EPMC7989171 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Tan Eng Hooi EH Sena Anthony G AG Prats-Uribe Albert A You Seng Chan SC Ahmed Waheed-Ul-Rahman WU Kostka Kristin K Reich Christian C Duvall Scott L SL Lynch Kristine E KE Matheny Michael E ME Duarte-Salles Talita T Bertolin Sergio Fernandez SF Hripcsak George G Natarajan Karthik K Falconer Thomas T Spotnitz Matthew M Ostropolets Anna A Blacketer Clair C Alshammari Thamir M TM Alghoul Heba H Alser Osaid O Lane Jennifer C E JCE Dawoud Dalia M DM Shah Karishma K Yang Yue Y Zhang Lin L Areia Carlos C Golozar Asieh A Recalde Martina M Casajust Paula P Jonnagaddala Jitendra J Subbian Vignesh V Vizcaya David D Lai Lana Y H LYH Nyberg Fredrik F Morales Daniel R DR Posada Jose D JD Shah Nigam H NH Gong Mengchun M Vivekanantham Arani A Abend Aaron A Minty Evan P EP Suchard Marc M Rijnbeek Peter P Ryan Patrick B PB Prieto-Alhambra Daniel D

Rheumatology (Oxford, England) 20211001 SI

<h4>Objective</h4>Patients with autoimmune diseases were advised to shield to avoid coronavirus disease 2019 (COVID-19), but information on their prognosis is lacking. We characterized 30-day outcomes and mortality after hospitalization with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza.<h4>Methods</h4>A multinational network cohort study was conducted using electronic health records data ...[more]

PMID: 33725121

Similar Datasets

Project description:Patients with autoimmune diseases were advised to shield to avoid COVID-19, but information on their prognosis is lacking. We characterised 30-day outcomes and mortality after hospitalisation with COVID-19 among patients with prevalent autoimmune diseases, and compared outcomes after hospital admissions among similar patients with seasonal influenza. Multinational network cohort study. Electronic health records data from Columbia University Irving Medical Center (CUIMC) (NYC, United States [US]), Optum [US], Department of Veterans Affairs (VA) (US), Information System for Research in Primary Care-Hospitalisation Linked Data (SIDIAP-H) (Spain), and claims data from IQVIA Open Claims (US) and Health Insurance and Review Assessment (HIRA) (South Korea). All patients with prevalent autoimmune diseases, diagnosed and/or hospitalised between January and June 2020 with COVID-19, and similar patients hospitalised with influenza in 2017-2018 were included. 30-day complications during hospitalisation and death. We studied 133,589 patients diagnosed and 48,418 hospitalised with COVID-19 with prevalent autoimmune diseases. The majority of participants were female (60.5% to 65.9%) and aged ≥50 years. The most prevalent autoimmune conditions were psoriasis (3.5 to 32.5%), rheumatoid arthritis (3.9 to 18.9%), and vasculitis (3.3 to 17.6%). Amongst hospitalised patients, Type 1 diabetes was the most common autoimmune condition (4.8% to 7.5%) in US databases, rheumatoid arthritis in HIRA (18.9%), and psoriasis in SIDIAP-H (26.4%).Compared to 70,660 hospitalised with influenza, those admitted with COVID-19 had more respiratory complications including pneumonia and acute respiratory distress syndrome, and higher 30-day mortality (2.2% to 4.3% versus 6.3% to 24.6%). Patients with autoimmune diseases had high rates of respiratory complications and 30-day mortality following a hospitalization with COVID-19. Compared to influenza, COVID-19 is a more severe disease, leading to more complications and higher mortality. Future studies should investigate predictors of poor outcomes in COVID-19 patients with autoimmune diseases. Patients with autoimmune conditions may be at increased risk of COVID-19 infection andcomplications.There is a paucity of evidence characterising the outcomes of hospitalised COVID-19 patients with prevalent autoimmune conditions. Most people with autoimmune diseases who required hospitalisation for COVID-19 were women, aged 50 years or older, and had substantial previous comorbidities.Patients who were hospitalised with COVID-19 and had prevalent autoimmune diseases had higher prevalence of hypertension, chronic kidney disease, heart disease, and Type 2 diabetes as compared to those with prevalent autoimmune diseases who were diagnosed with COVID-19.A variable proportion of 6% to 25% across data sources died within one month of hospitalisation with COVID-19 and prevalent autoimmune diseases.For people with autoimmune diseases, COVID-19 hospitalisation was associated with worse outcomes and 30-day mortality compared to admission with influenza in the 2017-2018 season.

Project description:ObjectiveTo characterise patients with and without prevalent hypertension and COVID-19 and to assess adverse outcomes in both inpatients and outpatients.Design and settingThis is a retrospective cohort study using 15 healthcare databases (primary and secondary electronic healthcare records, insurance and national claims data) from the USA, Europe and South Korea, standardised to the Observational Medical Outcomes Partnership common data model. Data were gathered from 1 March to 31 October 2020.ParticipantsTwo non-mutually exclusive cohorts were defined: (1) individuals diagnosed with COVID-19 (diagnosed cohort) and (2) individuals hospitalised with COVID-19 (hospitalised cohort), and stratified by hypertension status. Follow-up was from COVID-19 diagnosis/hospitalisation to death, end of the study period or 30 days.OutcomesDemographics, comorbidities and 30-day outcomes (hospitalisation and death for the 'diagnosed' cohort and adverse events and death for the 'hospitalised' cohort) were reported.ResultsWe identified 2 851 035 diagnosed and 563 708 hospitalised patients with COVID-19. Hypertension was more prevalent in the latter (ranging across databases from 17.4% (95% CI 17.2 to 17.6) to 61.4% (95% CI 61.0 to 61.8) and from 25.6% (95% CI 24.6 to 26.6) to 85.9% (95% CI 85.2 to 86.6)). Patients in both cohorts with hypertension were predominantly >50 years old and female. Patients with hypertension were frequently diagnosed with obesity, heart disease, dyslipidaemia and diabetes. Compared with patients without hypertension, patients with hypertension in the COVID-19 diagnosed cohort had more hospitalisations (ranging from 1.3% (95% CI 0.4 to 2.2) to 41.1% (95% CI 39.5 to 42.7) vs from 1.4% (95% CI 0.9 to 1.9) to 15.9% (95% CI 14.9 to 16.9)) and increased mortality (ranging from 0.3% (95% CI 0.1 to 0.5) to 18.5% (95% CI 15.7 to 21.3) vs from 0.2% (95% CI 0.2 to 0.2) to 11.8% (95% CI 10.8 to 12.8)). Patients in the COVID-19 hospitalised cohort with hypertension were more likely to have acute respiratory distress syndrome (ranging from 0.1% (95% CI 0.0 to 0.2) to 65.6% (95% CI 62.5 to 68.7) vs from 0.1% (95% CI 0.0 to 0.2) to 54.7% (95% CI 50.5 to 58.9)), arrhythmia (ranging from 0.5% (95% CI 0.3 to 0.7) to 45.8% (95% CI 42.6 to 49.0) vs from 0.4% (95% CI 0.3 to 0.5) to 36.8% (95% CI 32.7 to 40.9)) and increased mortality (ranging from 1.8% (95% CI 0.4 to 3.2) to 25.1% (95% CI 23.0 to 27.2) vs from 0.7% (95% CI 0.5 to 0.9) to 10.9% (95% CI 10.4 to 11.4)) than patients without hypertension.ConclusionsCOVID-19 patients with hypertension were more likely to suffer severe outcomes, hospitalisations and deaths compared with those without hypertension.

Project description:BackgroundReal-world evidence on the association between autoimmune inflammatory rheumatic diseases, therapies related to these diseases, and COVID-19 outcomes are inconsistent. We aimed to investigate the potential association between autoimmune inflammatory rheumatic diseases and COVID-19 early in the COVID-19 pandemic.MethodsWe did an exposure-driven, propensity score-matched study using a South Korean nationwide cohort linked to general health examination records. We analysed all South Korean patients aged older than 20 years who underwent SARS-CoV-2 RT-PCR testing between Jan 1 and May 30, 2020, and received general health examination results from the Korean National Health Insurance Service. We defined autoimmune inflammatory rheumatic diseases (inflammatory arthritis and connective tissue diseases) based on the relevant ICD-10 codes, with at least two claims (outpatient or inpatient) within 1 year. The outcomes were positive SARS-CoV-2 RT-PCR test, severe COVID-19 (requirement of oxygen therapy, intensive care unit admission, application of invasive ventilation, or death), and COVID-19-related death. Adjusted odds ratios (ORs) with 95% CIs were estimated after adjusting for the potential confounders.FindingsBetween Jan 1 and May 30, 2020, 133 609 patients (70 050 [52·4%] female and 63 559 [47·6%] male) completed the general health examination and were tested for SARS-CoV-2; 4365 (3·3%) were positive for SARS-CoV-2, and 8297 (6·2%) were diagnosed with autoimmune inflammatory rheumatic diseases. After matching, patients with an autoimmune inflammatory rheumatic disease showed an increased likelihood of testing positive for SARS-CoV-2 (adjusted OR 1·19, 95% CI 1·03-1·40; p=0·026), severe COVID-19 outcomes (1·26, 1·02-1·59; p=0·041), and COVID-19-related death (1·69, 1·01-2·84; p=0·046). Similar results were observed in patients with connective tissue disease and inflammatory arthritis. Treatment with any dose of systemic corticosteroids or disease-modifying antirheumatic drugs (DMARDs) were not associated with COVID-19-related outcomes, but those receiving high dose (≥10 mg per day) of systemic corticosteroids had an increased likelihood of a positive SARS-CoV-2 test (adjusted OR 1·47, 95% CI 1·05-2·03; p=0·022), severe COVID-19 outcomes (1·76, 1·06-2·96; p=0·031), and COVID-19-related death (3·34, 1·23-8·90; p=0·017).InterpretationEarly in the COVID-19 pandemic, autoimmune inflammatory rheumatic diseases were associated with an increased likelihood of a positive SARS-CoV-2 PCR test, worse clinical outcomes of COVID-19, and COVID-19-related deaths in South Korea. A high dose of systemic corticosteroid, but not DMARDs, showed an adverse effect on SARS-CoV-2 infection and COVID-19-related clinical outcomes.FundingNational Research Foundation of Korea.

Project description:ImportanceThe Undiagnosed Diseases Network (UDN) is a national network that evaluates individual patients whose signs and symptoms have been refractory to diagnosis. Providing reliable estimates of admission outcomes may assist clinical evaluators to distinguish, prioritize, and accelerate admission to the UDN for patients with undiagnosed diseases.ObjectiveTo develop computational models that effectively predict admission outcomes for applicants seeking UDN evaluation and to rank the applications based on the likelihood of patient admission to the UDN.Design, setting, and participantsThis prognostic study included all applications submitted to the UDN from July 2014 to June 2019, with 1209 applications accepted and 1212 applications not accepted. The main inclusion criterion was an undiagnosed condition despite thorough evaluation by a health care professional; the main exclusion criteria were a diagnosis that explained the objective findings or a review of the records that suggested a diagnosis. A classifier was trained using information extracted from application forms, referral letters from health care professionals, and semantic similarity between referral letters and textual description of known mendelian disorders. The admission labels were provided by the case review committee of the UDN. In addition to retrospective analysis, the classifier was prospectively tested on another 288 applications that were not evaluated at the time of classifier development.Main outcomes and measuresThe primary outcomes were whether a patient was accepted or not accepted to the UDN and application order ranked based on likelihood of admission. The performance of the classifier was assessed by comparing its predictions against the UDN admission outcomes and by measuring improvement in the mean processing time for accepted applications.ResultsThe best classifier obtained sensitivity of 0.843, specificity of 0.738, and area under the receiver operating characteristic curve of 0.844 for predicting admission outcomes among 1212 accepted and 1210 not accepted applications. In addition, the classifier can decrease the current mean (SD) UDN processing time for accepted applications from 3.29 (3.17) months to 1.05 (3.82) months (68% improvement) by ordering applications based on their likelihood of acceptance.Conclusions and relevanceA classification system was developed that may assist clinical evaluators to distinguish, prioritize, and accelerate admission to the UDN for patients with undiagnosed diseases. Accelerating the admission process may improve the diagnostic journeys for these patients and serve as a model for partial automation of triaging or referral for other resource-constrained applications. Such classification models make explicit some of the considerations that currently inform the use of whole-genome sequencing for undiagnosed disease and thereby invite a broader discussion in the clinical genetics community.

Dataset Information

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

Objective

Methods

Results

Conclusion

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets