Food protein-induced enterocolitis syndrome in a tertiary pediatric center: safety of guideline-conforming food challenges
Bibliographic record
Abstract
Food protein-induced enterocolitis syndrome is a non-IgE-mediated reaction to food that is poorly understood, and underdiagnosed. Trigger foods can belong to any food group, but are most commonly milk, soy, rice, oat, egg, and fish. In this retrospective study (2015-2020), we describe the clinical presentations and triggers of 37 children referred to tertiary hospital with a confirmed or suspected diagnosis of food protein-inducted enterocolitis. We reviewed the safety of current recommendations by looking at the outcome of 24 oral food challenges. All of these patients presented with clear cut systemic reactions including lethargy. We also assessed the severity of the reactions. Oral food challenges occurred in the hospital day unit with the majority of patients having IV access in place. Despite a clear history of FPIES with lethargy and the requirement for re-hydration of the challenged population, 21/24 (88%) of the FPIES OFCs were successful. Of the three patients who reacted, symptoms were of moderate nature, mainly vomiting. This highlights the importance of early diagnosis and a pro-active approach to performing guideline-directed oral food challenges in patients with food protein-induced enterocolitis syndrome.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".