Oral allergy syndrome and risk of food-related anaphylaxis: a cross-sectional survey analysis
Bibliographic record
Abstract
Oral Allergy Syndrome (OAS) is an IgE-mediated allergic response to fresh fruits, nuts and vegetables caused by cross-reactivity between pollen allergens and structurally similar food proteins. Alder pollen is a prominent allergen in coastal British Columbia, present at high levels from February- April. We hypothesized that this exposure may lead to increased prevalence of Alder pollen allergy and OAS. We sought to determine our population-based prevalence, cross-reactivity patterns, and incidence of food-related anaphylaxis. A chart review of 574 allergic rhinitis patients seen from January 2010 - June 2011 was performed. 274 OAS patients were invited to participate in an online, telephone or in-person survey. Patients completing the survey in the clinic were invited to undergo a panel of skin prick tests. 63 patients were surveyed, 14 underwent skin testing. Patient characteristics included: median age=37 (range 20-77), 83% female, 36% atopic dermatitis, 24% asthma. OAS prevalence among seasonal allergic rhinitis patients=242/574 (42%). 14/14 patients were skin test positive for Alder and Birch. The most common OAS foods were apple 44/63 (70%), cherry 37/63 (59%), and peach 38/63 (60%). 28 had epinephrine auto-injector devices; 4 had used their device; 6/10 reactions involved foods that had caused OAS including apple, celery, green pepper, tomato, peanut, walnut. In our population, the prevalence of OAS was slightly lower than expected at 42%. The most common OAS/pollen allergy was Alder, correlating with the high Alder pollen exposure in coastal British Columbia. OAS may be associated with serious reactions requiring use of epinephrine.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".