Drug-induced anaphylaxis visits: temporal trends, triggers and management in four emergency departments across Canada
Bibliographic record
Abstract
Data is sparse on drug-induced anaphylaxis (DIA). We aimed to assess the percentage, diagnosis and management of DIA among all visits due to anaphylaxis in 3 pediatric Emergency Departments (ED)s and 1 adult ED across Canada. Children presenting to the Montreal Children's Hospital (MCH), British Columbia Children's Hospital (BCCH) and London Health Sciences Centre Children's Hospital (LHSC) and adults presenting to Hôpital du Sacré-Coeur de Montréal (HSC) with anaphylaxis were recruited as part of the Cross-Canada Anaphylaxis Registry (C-CARE). A standardized data form documenting the reaction and management was completed and patients were followed annually to determine if they were assessed by an allergist. From June 2012 to May 2016, 40 children presented to the MCH and 64 adults to HSC with DIA. From June 2014 to May 2016, 7 children and 4 children presented with DIA to the BCCH and the LHSC, respectively. More than half the cases were prospectively recruited. The percentage of DIA among all cases of anaphylaxis was similar in all three pediatric centres but was higher in the adult centre in Montreal. Most reactions in children were triggered by non-antibiotic drugs, and in adults, by antibiotics. The majority of adults and a third of children did not see an allergist after the initial reaction. In those that did see an allergist, diagnosis was established by either a skin test or an oral challenge in less than 20% of cases. Our results reveal high levels of DIA in adults compared to children and that most cases of suspected drug allergy are not appropriately established. It is crucial to develop guidelines for better assessment and diagnosis of DIA in order to appropriately manage these patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".