Comparing the risk of anaphylaxis requiring epinephrine in oral immunotherapy and subcutaneous immunotherapy: A review of recent Canadian real-world literature
Bibliographic record
Abstract
Background: The safety of pediatric food oral immunotherapy (Ped-OIT) has been depicted by some as less favorable than subcutaneous immunotherapy (SCIT) owing to the increased number of serious adverse events requiring epinephrine. A review of real-world data comparing Ped-OIT and SCIT safety is necessary to guide shared decision making. Objectives: Our aim was to compare the safety and adverse event profiles of peanut Ped-OIT and SCIT using Canadian real-word literature. Methods: We performed a retrospective review of recent Canadian real-world literature on peanut Ped-OIT and SCIT safety and adverse events. Results: The incidences of systemic reactions requiring epinephrine were 11 in 270 patients (4.07%) and 12 in 41,020 doses (0.029%) in a multicenter study in British Columbia, Alberta, Manitoba, and Nova Scotia studying 270 preschool-age children treated with peanut OIT. Similarly, a multicenter study in South-Western Ontario examining 160 patients between the ages of 1 and 17 years who were treated with peanut OIT showed that the incidences of systemic reactions requiring epinephrine were 5 in 160 patients (3.1%) and 8 in 52,751 doses (0.015%). A single-center retrospective review of 380 patients receiving aeroallergen SCIT showed that the incidences of systemic reactions requiring epinephrine were 28 in 380 patients (7.4%) and 1 in 1047 injection visits (0.095%). These findings are comparable to those of a review of 860 patients in Ontario who received either aeroallergen or venom SCIT, in which the incidence of systemic reaction requiring epinephrine was 10 in 4242 injections (0.24%). Conclusion: Despite differences in the OIT protocols used and age groups studied, recent real-world data suggest that the safety of preschool peanut OIT or peanut OIT using a slower buildup schedule is comparable to that of SCIT.
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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 | 0.008 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.025 | 0.037 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 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".