Allergen‐induced early and late asthmatic responses to inhaled seasonal and perennial allergens
Bibliographic record
Abstract
BACKGROUND: The allergen bronchoprovocation (ABP) test is a validated model to study asthma pathophysiology and response to treatments. The inhibitory effect of agents on the allergen-induced late asthmatic response (LAR) is a predictor of their efficacy in asthma treatment. However, it is difficult to predict the magnitude of a LAR, which may vary according to immune responsiveness and the type of allergen used for ABP. AIM: To determine the relationship between the magnitudes of early asthmatic response (EAR) and LAR in mild asthmatic subjects according to the type of allergen inhaled and its determinants. METHODS: This is a retrospective analysis of a large database of ABPs, all performed with a common standardized methodology. Patients were either challenged with house dust mites (HDMs), animals or pollens allergens. EAR was defined as a ≥ 20% fall in forced expiratory volume in 1 s (FEV1 ) < 3 h following ABP and LAR as a ≥ 15% fall in FEV1 between 3 and 7 h post-ABP. The ratio of EAR % fall in FEV1 /LAR % fall in FEV1 was compared between the groups of subjects according to the allergen used for ABP. RESULTS: Data from 290 subjects were analysed: 87 had an isolated EAR and 203 had a dual response (EAR + LAR). Dual responders had a significantly lower baseline PC20 , a more marked fall in FEV1 at EAR, and a trend towards higher baseline sputum eosinophil percentages. The ratio of EAR over LAR was significantly lower in HDM compared with pollen ABP, indicating a larger LAR for a similar EAR. No correlations were observed between the ratio of EAR over LAR and the various parameters recorded in the different groups analysed. CONCLUSION: Different mechanisms may be involved in modulating the magnitude of the LAR, according to the type of allergen. HDM seems to induce a stronger LAR than pollens, animal allergens being intermediary in this regard.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 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".