Are peanut oral food challenges still useful? An evaluation of children with suspected peanut allergy, sensitization to Ara h 2 and controlled asthma
Bibliographic record
Abstract
BACKGROUND: Sensitization to Ara h 2 has been proposed as a promising biological marker for the severity of peanut allergy and may reduce the need for oral food challenges. This study aimed to evaluate whether peanut oral food challenge is still a useful diagnostic tool for children with suspected peanut allergy and an elevated level of Ara h 2-specific IgE. Additionally, we assessed whether well-controlled asthma is an additional risk for severe reactions. METHODS: A retrospective analysis of 107 children with sensitization to Ara h 2-specific IgE (> 0.35 kU/l) undergoing open peanut challenges during 2012-2018 in the Tampere University Hospital Allergy Centre, Finland. RESULTS: Of the 107 challenges, 82 (77%) were positive. Serum levels of Ara h 2 -sIgE were higher in subjects with a positive challenge than in those who remained negative (median 32.9 (IQR 6.7-99.8) vs. 2.1 (IQR 1.0-4.9) kU/l), p < 0.001) but were not significantly different between subjects with and without anaphylaxis. No correlation was observed between the serum level of Ara h 2-sIgE and reaction severity grading. Well-controlled asthma did not affect the challenge outcome. CONCLUSIONS: Elevated levels of Ara h 2-specific IgE are associated with a positive outcome in peanut challenges but not a reliable predictor of reaction severity. Additionally, well-controlled asthma is not a risk factor for severe reactions in peanut challenges in children with sensitization to Ara h 2.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".