Review of food challenges in a pediatric tertiary care centre
Bibliographic record
Abstract
Results Of 322 challenges (median age 4.8 years), 204 (63%) passed, 89 (28%) failed and 29 (9%) refused to complete the challenge. Passed challenges included 54 (26%) egg, 52 (25%) peanut, 32 (16%) milk, 22 (11%) tree nuts, 17 (9%) fish and shellfish and 27 (13%) others. Failed challenges included 43 (48%) peanut, 17 (19%) egg, 12 (13%) milk, 5 (7%) tree nuts, 4 (4%) fish and shellfish and 8 (9%) others. ImmunoCAP medians for passed challenges were peanut 0.35 KU/L, egg 0.45 KU/L and milk 0.35KU/L. Failed challenges ImmunoCAP medians were peanut 0.74 KU/L, egg 0.95 KU/L and milk 0.97 KU/L. Symptoms included 77 (86%) cutaneous/mucus membrane, 8 (9%) respiratory and 19 (21%) gastrointestinal. No patients had cardiovascular symptoms. Epinephrine was required to treat 14 (16%), prednisone in 10 (11%), antihistamine in 49 (55%) and bronchodilator in 2 (2%) reactions. 35 (39%) of patients did not require any treatment. There were no hospital admissions or deaths reported. Conclusions Reactions associated with controlled food challenges are frequently mild and reversible with treatment. ImmunoCAP levels in successful challenges tend to be lower compared to failed challenges.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".