Evaluation of cephalosporin allergy: Survey of drug allergy experts
Bibliographic record
Abstract
Background: Since the publication of the 2022 Drug Allergy Practice Parameters (DAPP) of the American Academy of Allergy, Asthma & Immunology (AAAAI) and American College of Allergy, Asthma & Immunology (ACAAI), it is unclear the extent to which the simplified and risk-stratified evaluation of cephalosporin allergy has been incorporated into allergy practice. Objective: We aimed to assess current cephalosporin allergy testing practices using real case examples. Methods: An 18-question REDCap survey was sent to the 136 members of the Adverse Reactions to Drugs, Biologics and Latex (ARDBL) Committee of the AAAAI between February and April 2023. Results: Forty-six (33.8%) ARDBL members completed the survey after 3 email attempts. Most practiced in the United States (32, 69.6%), 6 (13.0%) in Canada, and the rest in Europe and Asia. Almost half (47.7%) reported that the 2022 DAPP had increased their use of direct oral challenge, and 91% would prescribe cephalosporins in the setting of low-risk penicillin allergy history without testing. For low-risk cephalosporin reactions, 68% would perform a direct oral challenge with the culprit drug. In severe immediate penicillin reactions, 23% would evaluate with penicillin skin test before assessing cephalosporin allergy. For cephalosporin-related anaphylaxis, 48% would perform cephalosporin-based tests. For perioperative anaphylaxis with cefazolin, 57% would perform cephalosporin-based tests. For positive skin test result to cefazolin, 79% chose to avoid the culprit drug with follow-up oral challenge to a structurally dissimilar cephalosporin. Conclusion: Increased uptake of direct oral challenge represents the initial impact of the 2022 DAPP. However, there is significant variation in testing practices of cephalosporin allergy even among drug allergy experts, reflecting a need for a firmer evidence base to guide consensus around testing for higher-risk reactions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".