Food Protein Induced Enterocolitis Syndrome Presenting With Life-Threatening Methemoglobinemia: A Case Report and Review of the Literature
Bibliographic record
Abstract
Food protein induced enterocolitis syndrome (FPIES) can present with diarrhea, hypovolemia and electrolyte imbalance in infancy. We present a case of life-threatening methemoglobinemia in a 1-month-old infant, a rare complication of FPIES triggered by cow ’s milk protein intake. A previously healthy 1-month-old boy presented with lethargy, increased work of breathing and 2-day history of vomiting. Review of systems revealed a 3-week history of diarrhea. He was lethargic, shocky and dusky, and was intubated for persistent hypoxia. His blood work revealed severe acidemia with pH of 6.95 and methemoglobin level of 66% (normal range < 3%). His methemoglobin level and clinical status normalized following volume resuscitation, packed red blood cell transfusion and prompt intravenous methylene blue administration. Further investigations revealed a diagnosis of FPIES which was managed with a hypoallergenic formula. Methemoglobinemia should be considered in young infants presenting with severe vomiting and diarrhea, secondary to dietary protein intolerance syndromes. Prompt management with methylene blue and fluid resuscitation can result in excellent prognosis, along with specific ongoing management for FPIES. Int J Clin Pediatr. 2020;9(2):35-40 doi: https://doi.org/10.14740/ijcp366
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".