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Record W4406112825 · doi:10.3389/fphar.2024.1519522

Association between penicillin allergy labels and serious adverse events in hospitalized patients: a systematic review and meta-analysis

2025· review· en· W4406112825 on OpenAlexaboutno aff
Shipeng Zhang, Tianyi Dong, Jiawen Xian, Xinyue Xiao, Jiaqing Yuan, Tong Zeng, Ke Deng, Rui Fu, Hanyu Wang, Yanjie Jiang, Xueying Li

Bibliographic record

VenueFrontiers in Pharmacology · 2025
Typereview
Languageen
FieldMedicine
TopicDrug-Induced Adverse Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsPenicillinMedicineAdverse effectMeta-analysisAllergyPenicillin allergyAnaphylaxisIntensive care medicineDermatologyTraditional medicineInternal medicineImmunologyAntibioticsMicrobiologyBiology

Abstract

fetched live from OpenAlex

Background To date, several studies have demonstrated that erroneous labeling of Penicillin allergy (PAL) can significantly impact treatment options and result in adverse clinical outcomes, while other studies have reported no negative effects. Therefore, to systematically evaluate these effects and investigate the association between adverse clinical outcomes and the Penicillin label, we conducted this meta-analysis. Method Searches were conducted in the PubMed, Embase, Cochrane Library, and Web of Science databases from inception to 13 July 2024. The search strategy utilized terms (“antibiotic allergy label,” “penicillin allergy label,” and “allergy label”) and (“death,” “readmission,” “adverse outcome,” and “clinical adverse outcome”). In the study selection process, the PICOS framework and stringent inclusion/exclusion criteria were applied. The quality of the initially included studies was independently assessed using the Newcastle-Ottawa Scale (NOS). Data from the included studies, including relative risk (RR) and 95% confidence intervals (CI), were extracted and analyzed using Stata 16.0. Sensitivity analyses were conducted to validate the results. Heterogeneity was assessed using the I 2 and Cochrane Q tests, and publication bias was evaluated using Egger’s test and funnel plot analysis. Results A total of 497 relevant studies were identified through four databases. Following a thorough screening process, 11 studies encompassing 1,200,785 participants were ultimately included. The combined evidence suggests that penicillin allergy labeling is associated with increased mortality RR = 1.06 (95% CI 1.06–1.07, I 2 = 0.00%), acute heart failure (RR = 1.19, 95% CI 1.09–1.30, τ 2 = 0.00, I 2 = 92.39%), ICU events (RR = 1.10, 95% CI 1.01–1.19, τ 2 = 0.00, I 2 = 57.09%), and mechanical ventilation events (RR = 1.16, 95% CI 1.09–1.24, τ 2 = 0.00, I 2 = 23.11%). Additionally, there was no significant association with readmissions (RR = 1.05, 95% CI 0.95–1.16, I 2 = 0.00%). Conclusion Our findings indicate that penicillin allergy labels are associated with an increased risk of mortality in patients, as well as being linked to acute heart failure, heightened ICU requirements, and mechanical ventilation. Systematic Review Registration: PROSPERO, identifier CRD42024571535. Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD4202457153 .

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)0.019
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.047
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0170.039
Bibliometrics0.0090.009
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.355
Teacher spread0.327 · 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 designMeta-analysis
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

Citations10
Published2025
Admission routes1
Has abstractyes

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