Prevalence of Hypersensitivity Reactions in Children Associated with Acetaminophen: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Acetaminophen is the most commonly used antipyretic in children. However, there are limited data assessing hypersensitivity reactions related to acetaminophen usage. OBJECTIVES: To conduct a systematic review to characterize reported reactions to acetaminophen in adults and children, and perform a meta-analysis to assess the prevalence of acetaminophen hypersensitivity in children with a suspected acetaminophen allergy. METHODS: We performed a systematic review of studies reporting hypersensitivity reactions to acetaminophen by searching 2 electronic databases. From the selected studies, we included those assessing the prevalence of acetaminophen hypersensitivity by performing oral challenge in our meta-analysis. RESULTS: Eighty-five studies were included in the systematic review, assessing a total of 1,030 participants. Immediate (within 1 h of exposure) hypersensitivity reactions were reported in > 25% of the articles, while cutaneous nonimmediate reactions were similarly reported in about 25% of the articles. The remaining articles reported Steven-Johnson syndrome/toxic epidermal necrolysis, fixed drug eruptions, and cross-intolerance reactions. Five pediatric studies were included in our meta-analysis. The prevalence of acetaminophen hypersensitivity reaction among children undergoing oral challenge was 10.1% (95% confidence interval 4.5-15.5). CONCLUSION: Future studies assessing the risk of immediate and nonimmediate hypersensitivity reactions to acetaminophen and elucidating the mechanism of acetaminophen hypersensitivity reactions are required.
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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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.031 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".