Characterizing the Association Between Asthma and Clinical Outcomes in Emergency Department Patients With Symptomatic COVID-19
Bibliographic record
Abstract
Few studies have investigated the risks of developing intubation and death in patients seen in the emergency department (ED) with COVID-19 and pre-existing asthma. We conducted a retrospective cohort study using data from the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) from March 1st, 2020, to December 31st, 2021. Inclusion criteria were age ≥18 and a positive SARS-CoV-2 test. The primary outcome was a composite of intubation or death, and the secondary outcome was severe COVID-19, as defined by the World Health Organization. Multivariable modified Poisson regression was used to assess the association between asthma and outcomes, adjusted for possible confounding. Out of 38,139 patients, 2,826 (7.41%) had asthma, and 17.1% were using inhaled corticosteroids (ICS). The study found no significant evidence suggesting an association between asthma and intubation or death in the hospital (relative risk (RR): 0.97; 95% CI: 0.86-1.1). The highest risk group for the primary outcome was patients aged 80+ years (RR: 10.54; 95% CI: 7.01-15.85), compared to the reference group 18-29 years. Users of ICS agents had a slightly higher risk of the primary outcome compared to non-ICS users (RR: 1.12; 95% CI: 1.01-1.25).
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".