Modified oral food challenge protocol approach in the diagnosis of Food Protein-Induced Enterocolitis Syndrome
Bibliographic record
Abstract
BACKGROUND: Food Protein-Induced Enterocolitis Syndrome (FPIES) is a non-IgE mediated food allergy most commonly presenting in infants. The most common food triggers include soy, cow's milk and grains. Symptoms may include intractable vomiting, diarrhea, lethargy, pallor, abdominal distention, hypotension and/or shock. Oral food challenges (OFCs) given at food protein dose of 0.06-0.6 g/kg in 3 equivalent doses administered over a few hours are recommended in guidelines to confirm a diagnosis. CASE PRESENTATION: The patient is a 6-month-old girl with a history of severe FPIES symptoms to egg. In our clinic, we perform OFC with 1/100 serving dose on visit 1 and then increase the dose monthly. The patient takes the tolerated dose daily at home between visits. An OFC to baked egg at 1/100 of a serving was performed and was well-tolerated on her initial visit. The patient remained on the same dose upon returning home. Within 1-week, she developed FPIES symptoms including watery diarrhea and severe emesis requiring ondansetron. She required an Emergency Department visit for one of the reactions. CONCLUSIONS: Our patient had severe FPIES symptoms with a small amount of egg. We believe that administration of three large food challenge doses on one clinic visit, as guidelines currently suggest, does not allow adequate time for symptoms to appear. Our patient likely would have suffered a severe reaction. Also, this guidelines protocol does not allow for monitoring of more delayed or chronic FPIES. We propose a modified protocol to OFCs with cautious up-dosing to allow for safer OFCs and monitoring of chronic FPIES. We have implemented an OFC approach where only one food challenge dose (starting with 1/100 of final dose) is given at each visit. The up-titration of the dose is completed every 4-weeks with one dose only. When the serving sized dose is reached and tolerated, the food can be maintained in the diet.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".