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Record W7160170974 · doi:10.5281/zenodo.20022100

A REVIEW OF ANTIBIOTIC-INDUCED DRUG ALLERGIES: MECHANISMS, PREVALENCE, AND FUTURE PERSPECTIVES

2025· article· en· W7160170974 on OpenAlexaff
Ghassan Shannan, Zeina S Malek, Nasser Thallaj

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsPrivy Council Office
Fundersnot available
KeywordsAllergyDrugDrug allergyDrug reactionAdverse effectPublic healthAntibioticsPharmacovigilance

Abstract

fetched live from OpenAlex

Drug allergies pose a significant public health challenge, contributing to a substantial proportion of adverse drug reactions, particularly among antibiotics. This review explores the mechanisms underlying drug allergies, emphasizing the role of antibiotics, which frequently induce hypersensitivity reactions. Drug allergies are classified into immediate and delayed hypersensitivity types, with immediate reactions mediated by immunoglobulin E (IgE) and delayed responses involving T lymphocytes. A critical aspect of antibiotic-induced allergies is haptenization, where antibiotics interact with host proteins, forming antigenic determinants that trigger immune responses. Recent studies highlight the prevalence of allergic reactions to specific antibiotics, such as amoxicillin and sulfamethoxazole, raising concerns regarding their clinical use and management. The review examines the emerging pharmacologic interaction (p-i) concept, which suggests that certain antibiotics may activate T lymphocytes directly without requiring haptenization. Additionally, the diagnostic challenges associated with distinguishing true allergic reactions from adverse drug effects are discussed, emphasizing the need for more sensitive and specific testing methods. This review aims to synthesize current knowledge on antibiotic-induced allergies, identify gaps in understanding, and propose future research directions. By enhancing our understanding of the immunological mechanisms involved, this work seeks to improve diagnostic and therapeutic strategies, ultimately contributing to better patient safety and care in clinical settings.Original Article: https://www.researchgate.net/profile/Ghassan-Shannan/publication/390695383_A_REVIEW_OF_ANTIBIOTIC-INDUCED_DRUG_ALLERGIES_MECHANISMS_PREVALENCE_AND_FUTURE_PERSPECTIVES/links/67f926debfbe974b23a8ea0a/A-REVIEW-OF-ANTIBIOTIC-INDUCED-DRUG-ALLERGIES-MECHANISMS-PREVALENCE-AND-FUTURE-PERSPECTIVES.pdf?origin=publication_detail&_tp=eyJjb250ZXh0Ijp7ImZpcnN0UGFnZSI6InB1YmxpY2F0aW9uIiwicGFnZSI6InB1YmxpY2F0aW9uRG93bmxvYWQiLCJwcmV2aW91c1BhZ2UiOiJwdWJsaWNhdGlvbiJ9fQ&__cf_chl_tk=QLV9MRY8J6r6.Dfl0cQUikE64WZ0PG2ptqkza2TRqUw-1777877716-1.0.1.1-ZHjcD665igF3kvTsb_wZEsOblLaAsTP_UDgtrXn6ybEThis version is archived in the Arab International University (AIU) repository for open access and dissemination purposes. The content of this paper has not been modified from the original publication.For more information, please visit the official repository of Arab International University (AIU):https://aiu.edu.sy

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.910
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.278
Teacher spread0.258 · 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
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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