Safety and feasibility of oral immunotherapy to multiple allergens for food allergy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Thirty percent of children with food allergy are allergic to more than one food. Previous studies on oral immunotherapy (OIT) for food allergy have focused on the administration of a single allergen at the time. This study aimed at evaluating the safety of a modified OIT protocol using multiple foods at one time. METHODS: Participants underwent double-blind placebo-controlled food challenges (DBPCFC) up to a cumulative dose of 182 mg of food protein to peanut followed by other nuts, sesame, dairy or egg. Those meeting inclusion criteria for peanut only were started on single-allergen OIT while those with additional allergies had up to 5 foods included in their OIT mix. Reactions during dose escalations and home dosing were recorded in a symptom diary. RESULTS: Forty participants met inclusion criteria on peanut DBPCFC. Of these, 15 were mono-allergic to peanut and 25 had additional food allergies. Rates of reaction per dose did not differ significantly between the two groups (median of 3.3% and 3.7% in multi and single OIT group, respectively; p = .31). In both groups, most reactions were mild but two severe reactions requiring epinephrine occurred in each group. Dose escalations progressed similarly in both groups although, per protocol design, those on multiple food took longer to reach equivalent doses per food (median +4 mo.; p < .0001). CONCLUSIONS: Preliminary data show oral immunotherapy using multiple food allergens simultaneously to be feasible and relatively safe when performed in a hospital setting with trained personnel. Additional, larger, randomized studies are required to continue to test safety and efficacy of multi-OIT. TRIAL REGISTRATION: Clinicaltrial.gov NCT01490177.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 it