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Record W1495090702 · doi:10.4212/cjhp.v58i2.295

Cross-Allergy Among the ß-lactam Antibiotic Agents: A Review of the Risks

2005· review· en· W1495090702 on OpenAlexaffvenue
Rosemary Zvonar

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2005
Typereview
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsMedicineAllergyDrug allergyAntibioticsCephalosporinDrugIntensive care medicineImmunologyPharmacologyMicrobiology

Abstract

fetched live from OpenAlex

ABSTRACT Background: Allergies to s-lactam antibiotics are often encountered in pharmacists’ daily practice. The frequency and risks of cross-allergy between agents may lead to uncertainty in the prescribing of s-lactam antibiotics. Objective: To review and summarize the current literature pertaining to the incidence and risks of immunoglobulin-E (IgE)- mediated allergy and of cross-allergy between the s-lactam antibiotics, and to formulate a concise approach to allergy assessment and prescribing in these situations. Methods: The search terms “penicillins”, “cephalosporins”, and “carbapenems” (along with the specific drug names “imipenem”, “meropenem”, and “ertapenem”), as well as “allergy” and “drug hypersensitivity”, were used to search the MEDLINE and Reactions databases for pertinent English-language articles. The bibliographies of the review articles identified in this way were also perused for pertinent references. Results: Of all the s-lactam antibiotics, true (IgE-mediated) allergy occurs most frequently with penicillins. The risks of cross-allergy with penicillins and cephalosporins are well delineated; however, cross-reactivity between other classes and among agents within an individual class is not as clear. Conclusions: Recommendations for the approach to allergy assessment and prescribing of the s-lactam agents in patients with various s-lactam allergies are presented. In some situations, specific skin testing will indicate whether a drug can safely be prescribed. In most cases, some monitoring or supervision is appropriate when the drug is administered. RESUME Historique : Les allergies aux betalactamines sont chose courante dans la pratique quotidienne du pharmacien. La frequence et les risques d’allergie croisee entre les divers medicaments de cette classe peuvent expliquer une certaine hesitation a prescrire les betalactamines. Objectif : Passer en revue et presenter un resume de la litterature actuelle pour ce qui est de l’incidence et des risques d’allergie a mediation par l’immunoglobuline E (IgE) et d’allergie croisee entre les betalactamines, ainsi que formuler un demarche concise pour l’evaluation de l’allergie et la prescription dans de telles circonstances. Methodes : Les mots cles «penicillins», «cephalosporins», «carbapenems» (accompagnes des noms de medicaments specifiques : «imipenem», «meropenem» et «ertapenem»), «allergy» et «drug hypersensitivity» ont servis a la recherche, dans les bases de donnees MEDLINE et Reactions, d’articles pertinents en anglais. Les bibliographies des articles de synthese ainsi identifies ont ete attentivement examinees a la recherche de references pertinentes. Resultats : De toutes les betalactamines, la vraie allergie (a mediation par l’IgE) survient le plus souvent avec les penicillines. Les risques d’allergie croisee avec les penicillines et les cephalosporines sont bien definis, ce qui, en revanche, n’est pas aussi clair pour la reactivite croisee avec les carbapenems et entre les medicaments d’une meme classe. Conclusions : Des recommandations relativement a la demarche en matiere d’evaluation de l’allergie et de prescription des betalactamines chez les patients presentant differentes allergies aux betalactamines sont presentees. Dans certains cas, un test cutane specifique permettra de dire si tel ou tel medicament est sur. Dans la plupart des cas, il est indique d’effectuer une certaine surveillance ou supervision durant l’administration du medicament.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.095
GPT teacher head0.415
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2005
Admission routes2
Has abstractyes

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