Accidental exposures to peanut in a large cohort of Canadian children with peanut allergy
Bibliographic record
Abstract
BACKGROUND: We previously estimated that the annual rate of accidental exposure to peanut in 1411 children with peanut allergy, followed for 2227 patient-years, was 11.9% (95% CI, 10.6, 13.5). This cohort has increased to 1941 children, contributing 4589 patient-years, and we determined the annual incidence of accidental exposure, described the severity, management, location, and identified associated factors. FINDINGS: Children with physician-confirmed peanut allergy were recruited from Canadian allergy clinics and allergy advocacy organizations from 2004 to May 2014. Parents completed questionnaires regarding accidental exposure to peanut over the preceding year. Five hundred and sixty-seven accidental exposures occurred in 429 children over 4589 patient-years, yielding an annual incidence rate of 12.4% (95% CI, 11.4, 13.4). Of 377 accidental exposures that were moderate or severe, only 109 (28.9%) sought medical attention and of these 109, only 40 (36.7%) received epinephrine. Of the 181 moderate/severe accidental exposures treated outside a health care facility, only 11.6% received epinephrine. Thirty-seven percent of accidental exposures occurred at home. In multivariate analyses, longer disease duration, recruitment through an allergy advocacy association, and having other food allergies decreased the likelihood of accidental exposures. Age ≥ 13 years at study entry and living with a single parent increased the risk. CONCLUSION: Despite increased awareness, accidental exposures continue to occur, mainly at home, and most are managed inappropriately by both health care professionals and caregivers. Consequently, more education is required on the importance of strict allergen avoidance and the need for prompt and correct management of anaphylaxis.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".