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Record W3112956657 · doi:10.1002/art.41619

COVID‐19 Outcomes in Patients With Systemic Autoimmune Rheumatic Diseases Compared to the General Population: A US Multicenter, Comparative Cohort Study

2020· article· en· W3112956657 on OpenAlexfundno aff
Kristin M. D’Silva, April Jorge, A. N. Cohen, Natalie McCormick, Yuqing Zhang, Zachary S. Wallace, Hyon K. Choi

Bibliographic record

VenueArthritis & Rheumatology · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNational Institutes of HealthNational Institute of Arthritis and Musculoskeletal and Skin DiseasesRheumatology Research Foundation
KeywordsMedicineARDSCoronavirus disease 2019 (COVID-19)Systemic diseasePopulationCohortSystemic inflammationCohort studyDiseaseInternal medicineIntensive care medicineLungInfectious disease (medical specialty)Inflammation

Abstract

fetched live from OpenAlex

OBJECTIVE: Patients with systemic autoimmune rheumatic diseases (ARDs) continue to be concerned about risks of severe coronavirus disease 2019 (COVID-19) outcomes. This study was undertaken to evaluate the risks of severe outcomes in COVID-19 patients with systemic ARDs compared to COVID-19 patients without systemic ARDs. METHODS: Using a large multicenter electronic health record network, we conducted a comparative cohort study of patients with systemic ARDs diagnosed as having COVID-19 (identified by diagnostic code or positive molecular test result) compared to patients with COVID-19 who did not have systemic ARDs, matched for age, sex, race/ethnicity, and body mass index (primary matched model) and additionally matched for comorbidities and health care utilization (extended matched model). Thirty-day outcomes were assessed, including hospitalization, intensive care unit (ICU) admission, mechanical ventilation, acute renal failure requiring renal replacement therapy, ischemic stroke, venous thromboembolism, and death. RESULTS: We initially identified 2,379 COVID-19 patients with systemic ARDs (mean age 58 years; 79% female) and 142,750 comparators (mean age 47 years; 54% female). In the primary matched model (2,379 patients with systemic ARDs and 2,379 matched comparators with COVID-19 without systemic ARDs), patients with systemic ARDs had a significantly higher risk of hospitalization (relative risk [RR] 1.14 [95% confidence interval (95% CI) 1.03-1.26]), ICU admission (RR 1.32 [95% CI 1.03-1.68]), acute renal failure (RR 1.81 [95% CI 1.07-3.07]), and venous thromboembolism (RR 1.74 [95% CI 1.23-2.45]) versus comparators but did not have a significantly higher risk of mechanical ventilation or death. In the extended model, all risks were largely attenuated, except for the risk of venous thromboembolism (RR 1.60 [95% CI 1.14-2.25]). CONCLUSION: Our findings indicate that COVID-19 patients with systemic ARDs may be at a higher risk of hospitalization, ICU admission, acute renal failure, and venous thromboembolism when compared to COVID-19 patients without systemic ARDs. These risks may be largely mediated by comorbidities, except for the risk of venous thromboembolism.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.377
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations166
Published2020
Admission routes1
Has abstractyes

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