Association of blood inflammatory endotypes and asthma burden in moderate-to-severe pediatric asthma
Bibliographic record
Abstract
Background: The complexity underlying immunological mechanisms in children with moderate to severe asthma is unclear. Aim: We aimed to investigate association of blood inflammatory parameters on asthma burden in children with moderate to severe asthma. Methods: Blood inflammatory parameters (eosinophil and neutrophil counts and inflammatory mediators) were measured in 126 children (6-17 years) with moderate-severe asthma from SysPharmPediA cohort across four European countries. Children were divided into mixed, eosinophilic, neutrophilic, and paucigranulocytic asthma based upon blood eosinophil (cut-offs: 0.3×109/L or 0.5×109/L) and neutrophil counts (cut-off: 4×109/L). Inflammatory mediators and burden of disease (asthma control, exacerbations and school days missed in past year) were compared between groups. Results: Children with neutrophilic asthma had lowest lung function (FEV1%predicted pre-salbutamol) compared to other blood inflammatory endotypes. Children with increased blood eosinophils and neutrophils (mixed group) were most often uncontrolled and had highest asthma-related school absence in past year. IL-6 and MMP-9 levels were higher in patients with mixed or neutrophilic asthma, while TIMP-2 was lower in patients with neutrophilic asthma compared to children with eosinophilic or paucigranulocytic asthma. IL-5 was increased in eosinophilic group compared to neutrophilic and paucigranulocytic groups. Conclusion: Different blood inflammatory endotypes can be identified in children with moderate to severe asthma while being on maintenance treatment. High blood neutrophil and eosinophil counts despite inhaled corticosteroid (ICS) use are associated with a higher asthma burden.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".