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Comparative Performance of 4 Penicillin-Allergy Prediction Strategies in a Large Cohort.
Ghiordanescu, Ileana-Maria; Ciocanea-Teodorescu, Iuliana; Molinari, Nicolas; Jelen, Anais; Al-Ali, Omar; Schrijvers, Rik; Demoly, Pascal; Chiriac, Anca Mirela.
Afiliação
  • Ghiordanescu IM; Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; IDESP (The Desbrest Institute of Epidemiology and Public Health), University of Montpellier-INSERM (National Institute of Health and Medical Research), Montpellier, France. Electronic address: ileana-maria.ghiordanescu@drd.umfcd.r
  • Ciocanea-Teodorescu I; Carol Davila University of Medicine and Pharmacy, Bucharest, Romania; Victor Babeș National Institute of Pathology, Bucharest, Romania.
  • Molinari N; IDESP (The Desbrest Institute of Epidemiology and Public Health), University of Montpellier-INSERM (National Institute of Health and Medical Research), Montpellier, France; Division of Medical Information, La Colombiere University Hospital of Montpellier, Montpelier, France.
  • Jelen A; Department of Pulmonology, Division of Allergy, Arnaud de Villeneuve, University Hospital of Montpellier, Montpellier, France.
  • Al-Ali O; Department of Pulmonology, Division of Allergy, Arnaud de Villeneuve, University Hospital of Montpellier, Montpellier, France; Transversal Unit of Allergology, University Hospital of Nîmes, Nîmes, France.
  • Schrijvers R; Department of Microbiology, Immunology and Transplantation, Allergy and Clinical Immunology Research Group, KU, Leuven, Belgium.
  • Demoly P; IDESP (The Desbrest Institute of Epidemiology and Public Health), University of Montpellier-INSERM (National Institute of Health and Medical Research), Montpellier, France; Department of Pulmonology, Division of Allergy, Arnaud de Villeneuve, University Hospital of Montpellier, Montpellier, France.
  • Chiriac AM; IDESP (The Desbrest Institute of Epidemiology and Public Health), University of Montpellier-INSERM (National Institute of Health and Medical Research), Montpellier, France; Department of Pulmonology, Division of Allergy, Arnaud de Villeneuve, University Hospital of Montpellier, Montpellier, France.
Article em En | MEDLINE | ID: mdl-39038539
ABSTRACT

BACKGROUND:

A safe and pragmatic guide for labelling and delabelling patients with suspected penicillin allergy is mandatory.

OBJECTIVE:

To compare the performance of 4 penicillin-allergy prediction strategies in a large independent cohort.

METHODS:

We conducted a retrospective study for subjects presenting between January 2014 and December 2021 at the University Hospital of Montpellier, with a history of hypersensitivity to penicillins. The outcome targeted by the study was a positive penicillin-allergy test.

RESULTS:

Of the 1,884 participants included, 382 (20.3%) had positive penicillin-allergy tests. The ENDA (European Network on Drug Allergy) and Blumenthal strategies yielded relatively high sensitivities and low specificities and, by design, did not misclassify any positive subjects with severe index reactions. The PEN-FAST <3 score had a negative predictive value of 90% (95% confidence interval [95% CI] 88%-91%), with a sensitivity of 66% (95% CI 62%-71%) and a specificity of 73% (95% CI 71%-75%), and incorrectly delabelled 18 subjects with anaphylaxis and 15 with other severe nonimmediate reactions. For the adapted Chiriac score, the specificity corresponding to 66% sensitivity was 73% (95% CI 70%-75%). Conversely, at a 73% specificity threshold, the sensitivity was 65% (95% CI, 61%-70%). Attempts to improve these prediction algorithms did not substantially enhance performance.

CONCLUSIONS:

The ENDA and Blumenthal strategies are safe for high-risk subjects, but their delabelling effectiveness is limited, leading to unnecessary avoidance. Conversely, the PEN-FAST and Chiriac scores are performant in delabelling, but more frequently misclassify high-risk subjects with positive penicillin-allergy tests. Selection of the most appropriate tool requires careful consideration of the target population and the desired goal.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article