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Efficacy of a Clinical Decision Rule to Enable Direct Oral Challenge in Patients With Low-Risk Penicillin Allergy

2023· article· en· W4384561107 on OpenAlexaffabout
Ana Maria Copaescu, Sara Vogrin, Fiona James, Kyra Chua, Morgan Rose, Joseph De Luca, Jamie Waldron, Andrew Awad, Jack Godsell, Elise Mitri, Belinda Lambros, Abby Douglas, Rabea Khoudja, Ghislaine Annie Clarisse Isabwe, Geneviève Genest, Michael Fein, Cristine Radojicic, Ann C. Collier, Patricia Lugar, Cosby A. Stone, Moshe Ben‐Shoshan, Nicholas Turner, Natasha E. Holmes, Elizabeth J. Phillips, Jason A. Trubiano

Bibliographic record

VenueJAMA Internal Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsMontreal Children's HospitalMcGill University Health Centre
Fundersnot available
KeywordsMedicinePenicillinRandomized controlled trialPopulationAllergyClinical endpointClinical trialIntensive care medicinePediatricsInternal medicineAntibioticsImmunologyEnvironmental health

Abstract

fetched live from OpenAlex

Importance: Fewer than 5% of patients labeled with a penicillin allergy are truly allergic. The standard of care to remove the penicillin allergy label in adults is specialized testing involving prick and intradermal skin testing followed by an oral challenge with penicillin. Skin testing is resource intensive, limits practice to specialist-trained physicians, and restricts the global population who could undergo penicillin allergy delabeling. Objective: To determine whether a direct oral penicillin challenge is noninferior to the standard of care of penicillin skin testing followed by an oral challenge in patients with a low-risk penicillin allergy. Design, Setting, and Participants: This parallel, 2-arm, noninferiority, open-label, multicenter, international randomized clinical trial occurred in 6 specialized centers, 3 in North America (US and Canada) and 3 in Australia, from June 18, 2021, to December 2, 2022. Eligible adults had a PEN-FAST score lower than 3. PEN-FAST is a prospectively derived and internationally validated clinical decision rule that enables point-of-care risk assessment for adults reporting penicillin allergies. Interventions: Patients were randomly assigned to either direct oral challenge with penicillin (intervention arm) or a standard-of-care arm of penicillin skin testing followed by oral challenge with penicillin (control arm). Main Outcome and Measure: The primary outcome was a physician-verified positive immune-mediated oral penicillin challenge within 1 hour postintervention in the intention-to-treat population. Noninferiority was achieved if a 1-sided 95% CI of the risk difference (RD) did not exceed 5 percentage points (pp). Results: A total of 382 adults were randomized, with 377 patients (median [IQR] age, 51 [35-65] years; 247 [65.5%] female) included in the analysis: 187 in the intervention group and 190 in the control group. Most patients had a PEN-FAST score of 0 or 1. The primary outcome occurred in 1 patient (0.5%) in the intervention group and 1 patient (0.5%) in the control group, with an RD of 0.0084 pp (90% CI, -1.22 to 1.24 pp). The 1-sided 95% CI was below the noninferiority margin of 5 pp. In the 5 days following the oral penicillin challenge, 9 immune-mediated adverse events were recorded in the intervention group and 10 in the control group (RD, -0.45 pp; 95% CI, -4.87 to 3.96 pp). No serious adverse events occurred. Conclusions and Relevance: In this randomized clinical trial, direct oral penicillin challenge in patients with a low-risk penicillin allergy was noninferior compared with standard-of-care skin testing followed by oral challenge. In patients with a low-risk history, direct oral penicillin challenge is a safe procedure to facilitate the removal of a penicillin allergy label. Trial Registration: ClinicalTrials.gov Identifier: NCT04454229.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.031
GPT teacher head0.352
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations186
Published2023
Admission routes2
Has abstractyes

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