Adult-onset IgE-mediated food allergy at a Winnipeg allergy clinic: a case series
Bibliographic record
Abstract
BACKGROUND: It is a putatively understood phenomenon that the overall prevalence of allergic disease has been increasing in recent decades-particularly in industrialized nations. Despite this, there is a relative scarcity of data concerning the development of food-related allergic disease in the adult population. In addition, the paucity of data as it pertains to the Canadian population is particularly marked when compared to other nations. We sought to determine common culprit foods and the reactions they elicited in a series of 14 patients seen in the Winnipeg allergy and immunology clinic. METHODS: We conducted a retrospective review of patients identified by academic allergists in Winnipeg, Manitoba as fitting criteria for adult-onset IgE-mediated food allergy from May 2018-July 2020. We included patients with IgE-mediated symptoms, including the pollen-food syndrome which developed at the age of 16 or later. We collected data regarding the food which induced the reaction, what the reaction was, and any concomitant atopic disease. RESULTS: The most common culprit food identified was shellfish, followed by finfish, pollen-food syndrome, and wheat/flour. The most common reaction experienced was anaphylaxis, followed by food-dependent exercise-induced anaphylaxis and isolated (muco)cutaneous symptoms. With regard to concomitant atopic disease, allergic rhinitis/rhinoconjunctivitis stood out as the most prevalent. CONCLUSIONS: Adult-onset food allergy-particularly with resultant anaphylaxis-is an important phenomenon to recognize, even when patients have previously tolerated the food in question.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".