Asthma Exacerbations and Risk of Emergency Department Management Failure: Burden and Impact of Various Respiratory Pathogens in a Pediatric Population
Bibliographic record
Abstract
In asthmatic children, 60–80% of exacerbations are triggered by respiratory pathogens and represent an important burden of illness. The impact of pathogens on exacerbation severity and treatment response remains unclear. Our aim was to describe the prevalence of respiratory pathogens in children presenting to the emergency department (ED) and investigate the association between pathogens and (i) exacerbation severity on presentation and (ii) ED treatment failure. We performed a secondary analysis of the DOORWAY study, a prospective multi-center cohort of children (1–17 years) presenting to the ED with moderate or severe asthma exacerbation. All received per protocol oral corticosteroids and bronchodilators. Nasopharyngeal (NPA) secretions were analyzed by RT-PCR for 30 different pathogens. Linear and logistic multivariate regression models were used to estimate absolute risks and risk differences (RD) with their 95% CI representing average marginal effects. Of 958 patients with NPA specimens, 591 (61.7%) were positive for ≥ 1 pathogens; human rhinovirus (HRV) was the most prevalent (29.4%). Non-HRV infection (RD -12.9%; 95% CI -19.5; -6.3), human metapneumovirus (RD -13.6%; 95% CI -23.0%; -4.3%) and parainfluenza virus (PIV) (RD -31.7%; 95% CI -44.5%; -18.9%) were negatively associated with severity; no association was found between severity and the presence of any pathogen, co-infection, or the specific viruses HRV-A, HRV-B, HRV-C, respiratory syncytial virus, influenza (INF), enterovirus serotype D68, adenovirus or coronavirus. The risk of treatment failure in the absence of a pathogen was 12.5% (95% CI 9.0%; 16.0%). The presence of any pathogen (RD 8.2%; 95% CI 3.3%; 13.1%) and non-HRV infection as a group (RD 13.1%; 95% CI 6.4%; 19.8%), and of INF and PIV specifically (RD 24.9%; 95% CI 4.7%; 45.1% and RD 34.1%; 95% CI 7.5%; 60.7%) were positively associated with treatment failure. In this large cohort of children with moderate or severe exacerbation, no single respiratory pathogen was associated with higher severity on presentation. However, in addition to any pathogen and non-HVR infection, INF and PIV were specifically associated with higher treatment failure in the ED, supporting the need for influenza prevention, pathogen identification at presentation and exploration of pathogen-therapy interaction. All authors: No reported disclosures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".