The links between allergen skin test sensitivity, airway responsiveness and airway response to allergen
Bibliographic record
Abstract
BACKGROUND: The allergen-induced early asthmatic response [provocation concentration (PC)20, the concentration causing a 20% forced expiratory volume in 1 s (FEV)1 fall] depends on the level of IgE sensitivity and the degree of nonallergic airway hyperresponsiveness (AHR) and can be predicted from histamine PC20 and allergen skin test endpoint. OBJECTIVES: We examined the relationships between allergen PC20, methacholine PC20, and allergen skin test endpoint and assessed the accuracy of both the histamine PC20-based prediction of allergen PC20 (using methacholine) and a new methacholine PC20-based prediction equation. METHODS: From 158 allergen challenges, the allergen PC20, the methacholine PC20, and the skin test endpoint were recorded and relationships between these three were sought. We compared the measured allergen PC20 to that predicted from the previous histamine PC20-based and the new methacholine-based formulae. RESULTS: In single regressions, allergen PC20 correlated with both methacholine PC20 (r=0.25, P=0.0015) and skin test endpoint (r=0.52, P <0.00005). The relationship was improved by multiple regression of log-allergen PC20vs. log-methacholine PC20 and log-endpoint (r=0.61, P <0.00005). The histamine-based formula predicted allergen PC20 to within 2 doubling concentrations in 80% and within 3 in 92%. The new methacholine-based formula to within 2 and 3 concentrations in 81% and 94%, respectively; only nine of 158 subjects were outside the 3 concentrations. CONCLUSIONS: We have confirmed the dependence of the allergen-induced early asthmatic response upon the level of allergic sensitivity and the degree of AHR, the latter as assessed by methacholine challenge. The allergen PC20 can be predicted to within 3 doubling concentrations in 94% of cases.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".