Effect of Immunosuppressive or Immunomodulatory Agents on Severe <scp>COVID</scp>‐19 Outcomes: A <scp>Population‐Based</scp> Cohort Study
Bibliographic record
Abstract
OBJECTIVE: We estimated the association between immunosuppressive and immunomodulatory agent (IIA) exposure and severe COVID-19 outcomes in a population-based cohort study. METHODS: Participants were 18 years or older, tested positive for SARS-CoV-2 between February 6, 2020, and August 15, 2021, and were from administrative health data for the entire province of British Columbia, Canada. IIA use within 3 months prior to positive SARS-CoV-2 test included conventional disease-modifying antirheumatic drugs (antimalarials, methotrexate, leflunomide, sulfasalazine, individually), immunosuppressants (azathioprine, mycophenolate mofetil/mycophenolate sodium [MMF], cyclophosphamide, cyclosporine, individually and collectively), tumor necrosis factor inhibitor (TNFi) biologics (adalimumab, certolizumab, etanercept, golimumab, infliximab, collectively), non-TNFi biologics or targeted synthetic disease-modifying antirheumatic drugs (tsDMARDs) (rituximab separately from abatacept, anakinra, secukinumab, tocilizumab, tofacitinib and ustekinumab collectively), and glucocorticoids. Severe COVID-19 outcomes were hospitalizations for COVID-19, ICU admissions, and deaths within 60 days of a positive test. Exposure score-overlap weighting was used to balance baseline characteristics of participants with IIA use compared with nonuse of that IIA. Logistic regression measured the association between IIA use and severe COVID-19 outcomes. RESULTS: From 147,301 participants, we identified 515 antimalarial, 573 methotrexate, 72 leflunomide, 180 sulfasalazine, 468 immunosuppressant, 378 TNFi biologic, 49 rituximab, 144 other non-TNFi biologic or tsDMARD, and 1348 glucocorticoid prescriptions. Risk of hospitalizations for COVID-19 was significantly greater for MMF (odds ratio [95% CI]): 2.82 [1.81-4.40], all immunosuppressants: 2.08 [1.51-2.87], and glucocorticoids: 1.63 [1.36-1.96], relative to nonuse. Similar outcomes were seen for ICU admission and MMF: 2.52 [1.34-4.74], immunosuppressants: 2.88 [1.73-4.78], and glucocorticoids: 1.86 [1.37-2.54]. Only glucocorticoids use was associated with a significant increase in 60-day mortality: 1.58 [1.21-2.06]. No other IIAs displayed statistically significant associations with severe COVID-19 outcomes. CONCLUSION: Current use of MMF and glucocorticoids were associated with an increased risk of severe COVID-19 outcomes compared with nonuse. These results emphasize the variety of circumstances of patients taking IIAs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".