Recognition, treatment, and prevention of perioperative anaphylaxis: a narrative review
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".