Severe COVID-19 outcomes among patients with autoimmune rheumatic diseases or transplantation: a population-based matched cohort study
Bibliographic record
Abstract
Objectives To assess the risk of severe COVID-19 outcomes in patients with autoimmune rheumatic diseases (ARDs) and transplant recipients compared with matched general population comparators. Design Population-based matched cohort study using administrative health data sets. Setting British Columbia, Canada. Participants All adults with test-positive SARS-CoV-2 infections. SARS-CoV-2-positive patients with ARDs and those with transplantation were matched to SARS-CoV-2-positive general population comparators on age (±5 years), sex, month/year of initial positive SARS-CoV-2 test and health authority. Outcome measures COVID-19-related hospitalisations, intensive care unit (ICU) admissions, invasive ventilation and COVID-19-specific mortality. We performed multivariable conditional logistic regression models adjusting for socioeconomic status, Charlson Comorbidity Index, hypertension, rural address and number of previous COVID-19 PCR tests. Results Among 6279 patients with ARDs and 222 transplant recipients, all SARS-CoV-2 test positive, risk of hospitalisation was significantly increased among patients with ARDs (overall ARDs (adjusted OR (aOR) 1.30; 95% CI 1.19 to 1.43)); highest within ARDs: adult systemic vasculitides (aOR 2.18; 95% CI 1.17 to 4.05) and transplantation (aOR 10.56; 95% CI 6.88 to 16.22). Odds of ICU admission were significantly increased among patients with ARDs (overall ARDs (aOR 1.30; 95% CI 1.11 to 1.51)); highest within ARDs: ankylosing spondylitis (aOR 2.03; 95% CI 1.18 to 3.50) and transplantation (aOR 8.13; 95% CI 4.76 to 13.91). Odds of invasive ventilation were significantly increased among patients with ARDs (overall ARDs (aOR 1.60; 95% CI 1.27 to 2.01)); highest within ARDs: ankylosing spondylitis (aOR 2.63; 95% CI 1.14 to 6.06) and transplantation (aOR 8.64; 95% CI 3.81 to 19.61). Risk of COVID-19-specific mortality was increased among patients with ARDs (overall ARDs (aOR 1.24; 95% CI 1.05 to 1.47)); highest within ARDs: ankylosing spondylitis (aOR 2.15; 95% CI 1.02 to 4.55) and transplantation (aOR 5.48; 95% CI 2.82 to 10.63). Conclusions The risk of severe COVID-19 outcomes is increased in certain patient groups with ARDs or transplantation, although the magnitude differs across individual diseases. Strategies to mitigate risk, such as booster vaccination, prompt diagnosis and early intervention with available therapies, should be prioritised in these groups according to risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".