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Record W4226182562 · doi:10.3934/medsci.2022005

Recognition, treatment, and prevention of perioperative anaphylaxis: a narrative review

2022· review· en· W4226182562 on OpenAlexaff
Erin Long, Juan Camilo Ruiz, Julena Foglia, Kamen Valchanov, Andrew Meikle

Bibliographic record

VenueAIMS Medical Science · 2022
Typereview
Languageen
FieldMedicine
TopicFood Allergy and Anaphylaxis Research
Canadian institutionsRoyal Columbian HospitalVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsAnaphylaxisPerioperativeMedicineTryptaseAnesthesiologyIntensive care medicineAnesthesiaDiscontinuationAllergyImmunologyInternal medicineMast cell

Abstract

fetched live from OpenAlex

<abstract> <p>Perioperative anaphylaxis events are allergic reactions which occur in the perioperative period when patients are exposed to a multitude of agents, received anesthesia, and undergo a procedure. These reactions are rare and can be life-threatening, with the common signs being hypotension, hypoxia, elevated airway pressures and urticaria. Perioperative anaphylaxis can be mediated by immunoglobulin E (IgE) or non-IgE mechanisms. Globally, the incidence of reactions and frequency of specific triggers varies considerably. Perioperative anaphylaxis events often result in discontinuation of surgery, extended hospital stays, unanticipated intensive care admissions and increased morbidity and mortality. Common causative agents include neuromuscular blocking agents (NMBA's), beta-lactam antibiotics, chlorhexidine, and latex. The primary treatment of perioperative anaphylaxis is removal of the offending agent, epinephrine, and adequate fluid resuscitation. Post-operative workup involves serial serum tryptase measurements, skin testing, in-vitro testing and challenges to determine the culprit agent. Several countries including the UK, Spain, France, Australia, and New Zealand have established guidelines, reporting systems, and specialized clinics dedicated to perioperative hypersensitivity reactions. Future efforts should address diagnostic challenges as well as increasing awareness of other perioperative anaphylaxis triggers. This narrative review will provide an overview of the epidemiology, diagnosis, management, and prevention of perioperative anaphylaxis events.</p> </abstract>

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)0.002
metaresearch head score (Gemma)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.127
GPT teacher head0.448
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 teacher head, not a consensus.

Study designOther design
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

Citations1
Published2022
Admission routes1
Has abstractyes

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