Oral food immunotherapy in patients with atopic dermatitis
Bibliographic record
Abstract
Atopic dermatitis (AD) is one of the main risk factors for infants in the development of food allergy. Oral immunotherapy (OIT) in early childhood has been found to be highly effective and safe in preschoolers with and without AD, especially in young infants. Delays in initiation of OIT in infants and children due to uncontrolled AD risk expansion of the number of foods children develop allergy to through unnecessary avoidance of multiple foods. Parents and caregivers may attribute eczema flares to OIT doses, which physicians usually ascribe to non-food triggers such as weather changes, psychological stress, and infection. There is a lack of published literature confirming OIT as a trigger of AD flares, and the degree to which OIT may be associated with AD flares needs to be further studied. We describe 8 case scenarios with varying degrees of AD flare before and during OIT. We propose management algorithms for children with preexisting concurrent AD and food allergy who are being considered for starting OIT and children with AD flares during OIT. Optimizing AD control strategies and providing adequate AD care education before starting OIT can reduce confusion for both parents and allergists if rashes arise during OIT, thus improving adherence to OIT.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".