Raw wheat allergy: a case report
Bibliographic record
Abstract
There is evidence that individuals with milk and egg allergy may be able to tolerate the allergen in question if it is thoroughly heated. There is no published literature on raw versus cooked wheat allergy. We describe a case of hypersensitivity to raw wheat in an individual who is able to consume cooked wheat products. The outpatient clinic chart of our patient was reviewed. Our patient gave consent to having her data presented in case report format. A 28 year-old female with a history of persistent allergic rhinitis and Arterial Tortuosity Syndrome had two episodes of anaphylaxis following a meal. In each instance she had ingested food cooked in batter. Skin prick tests to all foods ingested during the meals, including commercial wheat extract, were negative. Skin prick testing to wheat flour, white flour, the uncooked batter in question, as well as several commercial pancake mixes, were strongly positive. Our patient did not wish to undergo a double-blinded placebo controlled food challenge due to her underlying medical condition. Our patient demonstrates IgE-mediated hypersensitivity to raw wheat, including uncooked batter. Her episodes of anaphylaxis occurred on ingestion of battered fish and chicken, which may have contained raw wheat if only partially cooked. We theorize that she is sensitized to a conformational epitope. Research is warranted in this area to further explore the possibility of raw wheat allergy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".