Dataset Information

Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis.

ABSTRACT: 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.

SUBMITTER: Tan EH

PROVIDER: S-EPMC7709171 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis.

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 Relcade Martina M Casajust Paula P Jonnagaddala Jitendra J Subbian Vignesh V Vizcaya David D Lai Lana Yh LY 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

medRxiv : the preprint server for health sciences 20201127

<h4>Objective</h4>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.<h4>Design</h4>Multinational network cohort study.<h4>Setting</h4>Electronic health records data from Columbia University Irving M ...[more]

PMID: 33269355

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Project description:BACKGROUND:Concurrent autoimmune illnesses contribute to increased medical burden and reduced quality of life in patients with autoimmune hepatitis (AIH). The frequency of coexisting autoimmune conditions among North American patients with AIH and their families remains incomplete. Challenges associated with disease capture in the electronic medical record, high study costs, and geographic spread of patients are formidable barriers to understanding the extent of concurrent autoimmune conditions in these groups. OBJECTIVE:This objective of this study was to examine the frequency of extrahepatic autoimmune diseases (EHAD) among AIH cases and healthy controls as well as their first-degree relatives using social networking sites (SNS). METHODS:We developed a 53-question survey detailing the history of autoimmune diseases. A survey link was posted at routine intervals within specific Web-based cohorts on SNS. Healthy controls, without self-reported autoimmune liver disease, were recruited from Amazon's Mechanical Turk. Continuous variables were summarized using medians and P values obtained with the Wilcoxon rank-sum test. Categorical variables were compared using the chi-square test. RESULTS:Compared with controls (n=1162), cases (n=306) were more likely to be older (median age: 49 vs 33 years), female (284/306, 92.81% vs 955/1162, 82.18%), and have an EHAD (128/306, 41.83% vs 218/1162, 18.76%; P=.001). The most frequent EHADs among cases were thyroid disease (49/306, 16.01% ), Sjögren syndrome (27/306, 8.82%), Raynaud phenomenon (23/306, 7.52%), and psoriasis (22/306, 7.19%). Overall, 55.88% (171/306) of cases and 35.71% (1601/4484) of controls reported at least 1 first-degree relative (FDR) with a history of EHAD (P=.001). Cases had a significantly higher risk of EHAD than controls after the adjustment for age, sex, race, and body mass index: odds ratio 2.46 (95% CI 1.8-3.3); P=.001. CONCLUSIONS:Patients with AIH report higher prevalence of coexistent EHAD than healthy controls, and their FDRs are also more likely to have autoimmune disorders.

Project description:ImportanceSystemic inflammation has been suggested to explain reported associations between infections and dementia. Associations between autoimmune diseases and dementia also suggest a role for peripheral systemic inflammation.ObjectiveTo investigate the associations of infections and autoimmune diseases with subsequent dementia incidence and to explore potential shared signals presented by the immune system in the 2 conditions.Design, setting, and participantsThis nationwide, population-based, registry-based cohort study was conducted between 1978 and 2018 (40-year study period). All Danish residents born 1928 to 1953, alive and in Denmark on January 1, 1978, and at age 65 years were included. Persons with prior registered dementia and those with HIV infections were excluded. Data were analyzed between May 2022 and January 2023.ExposuresHospital-diagnosed infections and autoimmune diseases.Main outcomes and measuresAll-cause dementia, defined as the date of a first registered dementia diagnosis after age 65 years in the registries. Poisson regression with person-years at risk as an offset variable was used to analyze time to first dementia diagnosis.ResultsA total of 1 493 896 individuals (763 987 women [51%]) were followed for 14 093 303 person-years (677 147 [45%] with infections, 127 721 [9%] with autoimmune diseases, and 75 543 [5%] with dementia). Among individuals with infections, 343 504 (51%) were men, whereas among those with autoimmune diseases, 77 466 (61%) were women. The dementia incidence rate ratio (IRR) following any infection was 1.49 (95% CI, 1.47-1.52) and increased along with increasing numbers of infections in a dose-dependent manner. Dementia rates were increased for all infection sites in the short term, but not always in the long term. The dementia IRR following any autoimmune disease was 1.04 (95% CI, 1.01-1.06), but no dose-dependent increase was observed, and only a few autoimmune conditions showed increased IRRs for dementia.Conclusions and relevanceThese findings may point toward a role for infection-specific processes in the development of dementia, rather than general systemic inflammation, as previously hypothesized. Assessing these 2 conditions in a single setting may allow for additional insights into their roles in dementia and for hypotheses on possible underlying mechanisms.

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:The incidence and complexity of drug-induced autoimmune diseases (DIAD) have been on the rise in recent years, which may lead to serious or fatal consequences. Besides, many environmental and industrial chemicals can also cause DIAD. However, there are few effective approaches to estimate the DIAD potential of drugs and other chemicals currently, and the structural characteristics and mechanism of action of DIAD compounds have not been clarified. In this study, we developed the in silico models for chemical DIAD prediction and investigated the structural characteristics of DIAD chemicals based on the reliable drug data on human autoimmune diseases. We collected 148 medications which were reported can cause DIAD clinically and 450 medications that clearly do not cause DIAD. Several different machine learning algorithms and molecular fingerprints were combined to develop the in silico models. The best performed model provided the good overall accuracy on validation set with 76.26%. The model was made freely available on the website http://diad.sapredictor.cn/. To further investigate the differences in structural characteristics between DIAD chemicals and non-DIAD chemicals, several key physicochemical properties were analyzed. The results showed that AlogP, molecular polar surface area (MPSA), and the number of hydrogen bond donors (nHDon) were significantly different between the DIAD and non-DIAD structures. They may be related to the DIAD toxicity of chemicals. In addition, 14 structural alerts (SA) for DIAD toxicity were detected from predefined substructures. The SAs may be helpful to explain the mechanism of action of drug induced autoimmune disease, and can used to identify the chemicals with potential DIAD toxicity. The structural alerts have been integrated in a structural alert-based web server SApredictor (http://www.sapredictor.cn). We hope the results could provide useful information for the recognition of DIAD chemicals and the insights of structural characteristics for chemical DIAD toxicity.

Dataset Information

Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis.

Publications

Characteristics, outcomes, and mortality amongst 133,589 patients with prevalent autoimmune diseases diagnosed with, and 48,418 hospitalised for COVID-19: a multinational distributed network cohort analysis.

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