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Record W2414028078 · doi:10.1539/joh.16-0053-cs

Anaphylaxis in laboratory workers because of rodent handling: two case reports

2016· article· en· W2414028078 on OpenAlexaff
Thatchai Kampitak, Stephen Betschel

Bibliographic record

VenueJournal of Occupational Health · 2016
Typearticle
Languageen
FieldMedicine
TopicOccupational exposure and asthma
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsAnaphylaxisMedicineAllergyImmunoglobulin EAsthmaImmunologyRespiratory systemOccupational asthmaAllergenDermatologyAntibodyInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Occupational allergy to rodents among laboratory animal workers is common. Most patients generally experience allergic symptoms after the first few years of work. Associated symptoms are usually mild, such as rhinoconjunctivits, urticaria, and asthma. Anaphylaxis, although rare, could be severe and life threatening. METHODS: We have described in this study two cases of laboratory workers that developed skin and respiratory reactions following laboratory rat and mouse bites, consistent with anaphylaxis. RESULTS: Skin testing was found positive for rat epithelium in the patient with anaphylaxis due to rat bite. Elevated levels of specific IgE antibodies against rat and mouse epitheliums were also detected in both the patients. CONCLUSION: These cases illustrate a severe hypersensitivity reaction that could potentially occur in occupational workers that are in close contact with rodents. Reduction of allergen exposure, regular screening, and job modification could be beneficial for affected individuals. Health care workers should be made aware that anaphylaxis could be a serious consequence of laboratory animal bites, particularly in those already sensitized.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0050.003
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0040.002
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0030.004
Research integrity0.0120.006
Insufficient payload (model declined to judge)0.0030.002

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 head0.036
GPT teacher head0.380
Teacher spread0.344 · 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 designCase report
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

Citations14
Published2016
Admission routes1
Has abstractyes

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