Epinephrine treatment of food-induced and other cause anaphylaxis in United States and Canadian Emergency Departments: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Studies from more than 10 years ago showed epinephrine treatment of food-induced anaphylaxis in the emergency department (ED) was unacceptably low. We investigated whether epinephrine treatment of food-induced and other cause anaphylaxis in United States and Canadian EDs has changed over time. METHODS: Guided by a health sciences librarian, we performed a systematic search in Medline, Embase, and Web of Science on 11 January 2023. We included observational studies that reported epinephrine use to treat anaphylaxis in the ED. We stratified by anaphylaxis etiology (food-, venom-, medication-induced, or any cause). Associations between year and epinephrine use were tested using Spearman correlation and proportional meta-analysis. RESULTS: Of 2458 records identified in our initial search, 40 met inclusion criteria. Of these, 14 examined food-induced, 4 venom-induced, 0 medication-induced, and 24 any cause anaphylaxis. For epinephrine treatment of food-induced anaphylaxis in the ED, among studies using similar definition of anaphylaxis, meta-analysis showed a pooled value of 20.7% (95% CI 17.8, 23.8) for studies performed >10 years ago and 45.1% (95% CI 38.4, 52.0) from those in the last 10 years. For anaphylaxis of any cause, there was no change over time, with a pooled value of 45.0% (95% CI 39.8, 50.3) over the last 10 years. DISCUSSION: Epinephrine treatment of food-induced anaphylaxis in the ED has increased over time. There was no clear change for anaphylaxis of any cause. Over the last 10 years, approximately 45% of ED patients with anaphylaxis received epinephrine. A limitation of the evidence is heterogeneity in anaphylaxis definitions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.017 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".