Using In-depth History Screening as an Additional Method to Help Delabel Inappropriate β-Lactam Allergies
Notice bibliographique
Résumé
To the Editor—We commend Blumenthal et al [1] for their study demonstrating that self-reported β-lactam allergies are associated with poorer outcomes in the perioperative setting. This work adds to the growing literature showing the harms secondary to the use of alternative second-line therapies, which are often broader, costlier, more toxic, and less effective [2, 3]. Blumenthal et al also described several approaches to verifying the unreliable self-reported β-lactam allergies in the perioperative setting, including routine skin testing and specialist consultation and exposure to test doses of cefazolin [4, 5]. Unfortunately, these resources are not available expeditiously in many healthcare centers. We would like to highlight an additional method to help delabel inappropriate β-lactam allergies that is available to all clinicians—that of using in-depth history screening [6]. At our site, each patient presenting to the preoperative clinic with a reported β-lactam allergy underwent a brief assessment by a nurse or pharmacist to clarify the nature, timing, and precise exposure eliciting the reported allergy. Each assessment was reviewed with an infectious diseases physician and patients were deemed safe to proceed with β-lactam prophylaxis if they did not describe a history of type I/immunoglobulin E–mediated reaction or other severe reaction. Antibiotic prophylaxis orders (with approval by the surgical team) were scheduled into the computerized order entry system to be given before the first incision of the upcoming operation. We found, that, among 485 patients with self-reported β-lactam allergy, only 117 (24%) reported a history consistent with anaphylaxis, a figure smaller than that determined by Blumenthal et al [1] (approximately 40%). Using our assessment, 277 patients (57%) ended up receiving β-lactam prophylaxis, with none subsequently experiencing adverse reactions. After implementation of this process at our institution, the overall use of alternative antibiotic prophylaxis at our institution among those reporting a β-lactam allergy decreased from 82% to 56%, and this decrease was directly associated with the number of monthly assessments. Because access to skin testing and allergist consultation is not readily available for the large volumes of elective surgeries performed yearly in most centers, this interdisciplinary approach can provide an efficient solution to the problem well demonstrated by Blumenthal et al A simple screening tool using the principles of prospective audit and feedback can increase the use of β-lactam perioperative prophylaxis without any adverse events and without the use of skin testing. Potential conflicts of interest. All authors: No reported conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,007 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
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