MétaCan
Menu
Back to cohort
Record W4403054721 · doi:10.58931/cait.2021.1219

Amoxicillin Allergy: Old Concepts, New Concepts and Change of Concepts

2021· article· en· W4403054721 on OpenAlexaboutno aff
Moshe Ben‐Shoshan

Bibliographic record

VenueCanadian allergy & immunology today. · 2021
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsAmoxicillinAllergyMedicineImmunologyMicrobiologyAntibioticsBiology

Abstract

fetched live from OpenAlex

More than one million Canadian children are treated annually with antibiotics, mainly amoxicillin.1-4 Up to 10% of children develop rashes while treated with amoxicillin.1-5 The majority of children presenting with rashes during amoxicillin treatment are diagnosed with amoxicillin hypersensitivity without further evaluation and often carry this diagnosis into adulthood. There remains controversy in the medical literature regarding the most accurate and safe strategy for diagnosing amoxicillin hypersensitivity. As a result, most children continue to avoid amoxicillin and other penicillin derivatives throughout life in favor of alternatives that are reported to be less effective, more toxic, and more expensive. There is much we do not know about the pathogenesis of amoxicillin hypersensitivity. Consequently, the appropriate diagnostic strategy required to establish the presence of true amoxicillin hypersensitivity is unclear. In order to develop an appropriate diagnostic approach, it is important to understand the pathogenic mechanisms accounting for amoxicillin hypersensitivity and the validity of the available confirmatory tests. This review will discuss the pathogenic mechanisms underlying amoxicillin allergy, describe the challenges in the diagnosis of amoxicillin allergy, critically assess the role of skin testing and IgE levels and discuss the appropriate diagnostic strategy in individuals presenting with suspected amoxicillin allergy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.291
Teacher spread0.261 · 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 designNot applicable
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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian allergy & immunology today.Same topicDrug-Induced Adverse ReactionsFrench-language works237,207