Cat allergen exposure in a naturalistic exposure chamber: A prospective observational study in cat‐allergic subjects
Bibliographic record
Abstract
BACKGROUND: To determine the proportion and reproducibility of cat-allergic mild asthmatics with early asthmatic response (EAR) during cat allergen exposure in a naturalistic exposure chamber (NEC). METHODS: This was a prospective, observational study in 30 cat-allergic mild asthmatics who received two 180-min cat-allergen (Felis domesticus allergen 1 [Fel d 1]) challenges 27 days apart in an NEC. RESULTS: An EAR (≥20% reduction from baseline in forced expiratory volume in 1 s [FEV1]) was observed in 67% and 52% of subjects at first and second NEC exposure, respectively, with similar median time to EAR; 44% of subjects had an EAR on days 1 and 28. Late asthmatic response (≥15% reduction in FEV1 within 24 h of NEC exit) was observed in 33% of subjects following either exposure. Average FEV1 and total nasal symptom score during NEC exposure were highly correlated within subjects between NEC exposures (r = 0.91, p < 0.0001; r = 0.73, p < 0.001), but total ocular symptom score was not. Time to EAR, but not average FEV1, was significantly associated with NEC Fel d 1 concentration, which was variable. There were no serious adverse events; 12/30 subjects experienced 20 adverse events (including asthma, 10%; headache, 10%). CONCLUSIONS: The NEC model demonstrates that average FEV1 change is highly reproducible and has a low correlation with cat allergen levels. However, time to EAR and incidence of EAR are less reproducible and are highly correlated with NEC allergen levels. Average FEV1, rather than incidence of EAR or time to EAR, could be considered as an endpoint for interventional trials testing cat-specific anti-allergy therapies using an NEC.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".