Immediate and non-immediate allergic reactions to amoxicillin present a diagnostic dilemma: a case series
Bibliographic record
Abstract
BACKGROUND: Allergic reactions to amoxicillin are very common occurrences in the pediatric age group; however, onset of symptoms can present a diagnostic dilemma. CASE PRESENTATION: We present a case series that describes three children (8-year-old white girl, 2-year-old white boy and 14-month-old Chinese boy) who presented with varied onset of allergic reactions to amoxicillin, specifically immediate (within the first hour after exposure) and non-immediate onset. One child developed immediate onset allergy to oral challenge with amoxicillin although his clinical history was evident for non-immediate onset allergy to amoxicillin. He was the only case that had a positive skin test to penicillin. Two other children presented with reactions toward the end of their treatment course of amoxicillin, yet one patient developed immediate onset allergy while the other patient developed non-immediate onset allergy after challenge. CONCLUSIONS: This case series demonstrates diagnostic challenges facing physicians assessing allergic reactions to amoxicillin. As onset of reactions can dictate severity and pathogenic type of allergy, a thorough clinical history and subsequent appropriate diagnostic testing including medication challenge can help establish the diagnosis.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".