ANTIBIOTIC SKIN TESTING FOR CHILDREN LABELED WITH TYPE 1 HYPERSENSITIVITY: A USEFUL CLINICAL TOOL
Bibliographic record
Abstract
INTRODUCTION: Children are often unnecessarily labeled as being allergic to antibiotics that may potentially be life saving. Aside from penicillin, good diagnostic testing has not been available in pediatrics to differentiate between type 1 hypersensitivity and other causes of adverse reactions to antibiotics. OBJECTIVE: We sought to determine the safety of antibiotic skin testing of children and to describe its potential clinical impact. METHODS: A retrospective chart review was performed of patients between 0 and 18 years of age who were seen in our clinic over a 2-year period with a history of a possible immunoglobulin E–mediated reaction to various antibiotics other than penicillin. We included patients with either extremely limited antibiotic options or complex medical issues that require antibiotics. We did not perform testing if there was a history of a convincing immunoglobulin E–mediated or serum sickness–like reaction. Skin testing was performed by using nonirritating concentrations of the antibiotic in question that have been used in adults. If skin-prick testing results were negative, we performed intradermal testing. A provocative challenge was offered if all skin-testing results were negative. RESULTS: of 28 visits, 23 met our inclusion criteria; 4 (17%) of 23 could not be skin-tested. Of those who were skin-prick–tested, all 19 (100%) had a negative result, and 17 (89%) of 19 also had a negative intradermal test. Of those 17 (88%), 15 patients agreed to undergo provocative challenge, 14 (93%) of whom were then unlabeled as allergic to the respective antibiotic. CONCLUSIONS: Skin-prick testing is a novel tool in pediatrics that may have an important clinical impact in the accurate diagnosis of antibiotic allergies by guiding provocative challenges.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".