Antibiotic Allergy in Children: More than Just a Label
Bibliographic record
Abstract
Within the broad category of adverse drug reactions in children, there has been a recent focus specifically on the evaluation of children with antibiotic allergy, in particular, beta-lactam allergy. The potential consequences of being labeled beta-lactam allergy are increasingly recognized. Appropriate evaluation of children with suspected reactions to antibiotics is essential as it is increasingly being recognized that the label of "penicillin allergy" is associated with adverse health and economic outcomes. This review will focus on the 3 main classes of antibiotics reported to cause allergic reactions in children: beta lactams (penicillin derivatives and cephalosporins), macrolides, and sulfonamides. This article is a narrative review of the prevalence, diagnosis, and management of different types of antibiotic allergies in children. Our review reveals that antibiotic allergy is often overreported and not appropriately diagnosed in the pediatric age groups. There is a recent shift in the diagnostic paradigm from the use of skin tests and if negative challenges to the use of challenge only in the pediatric age group. Larger studies to establish the usefulness and safety of this new approach as well as updated guidelines are needed.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".