Predicting Penicillin Allergy: A United States Multicenter Retrospective Study.

Alexei Gonzalez-Estrada,Miguel A. Park, John J.O. Accarino,Aleena Banerji,Ismael Carrillo-Martin, Michael E. D’Netto, W. Tatiana Garzon-Siatoya, Heather D. Hardway, Hajara Joundi, Susan Kinate,Jessica H. Plager,Matthew A. Rank,Christine RF. Rukasin,Upeka Samarakoon,Gerald W. Volcheck, Alexander D. Weston,Anna R. Wolfson,Kimberly G. Blumenthal

The journal of allergy and clinical immunology. In practice(2024)

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摘要
•What is already known about this topic? Considering prior studies empirically determining historical factors predicting penicillin allergy, a recent reaction (< 5 years) and presence of anaphylaxis makes confirmation more likely. There has not been US-based dataset modeling prediction of positive penicillin allergy skin testing.•What does this article add to our knowledge? Although our machine learning model was unable to accurately predict penicillin allergy, we identified reactions requiring medical attention, female sex, and reaction of hives/urticaria as new drivers for a positive immediate penicillin allergy skin testing.•How does this study impact current management guidelines? In this large multi-site US-based retrospective study, we confirmed some previously established penicillin allergy predictive tools and align with recent European data suggesting that some drug-induced urticaria should be considered high risk.
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关键词
penicillin allergy label,machine learning,logistic regression,predictors
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