Updated guidance regarding the risk of allergic reactions to COVID-19 vaccines and recommended evaluation and management: A GRADE assessment and international consensus approach.
Bibliographic record
Abstract
This guidance updates 2021 GRADE (Grading of Recommendations Assessment, Development and Evaluation) recommendations regarding immediate allergic reactions following coronavirus disease 2019 (COVID-19) vaccines and addresses revaccinating individuals with first-dose allergic reactions and allergy testing to determine revaccination outcomes. Recent meta-analyses assessed the incidence of severe allergic reactions to initial COVID-19 vaccination, risk of mRNA-COVID-19 revaccination after an initial reaction, and diagnostic accuracy of COVID-19 vaccine and vaccine excipient testing in predicting reactions. GRADE methods informed rating the certainty of evidence and strength of recommendations. A modified Delphi panel consisting of experts in allergy, anaphylaxis, vaccinology, infectious diseases, emergency medicine, and primary care from Australia, Canada, Europe, Japan, South Africa, the United Kingdom, and the United States formed the recommendations. We recommend vaccination for persons without COVID-19 vaccine excipient allergy and revaccination after a prior immediate allergic reaction. We suggest against >15-minute postvaccination observation. We recommend against mRNA vaccine or excipient skin testing to predict outcomes. We suggest revaccination of persons with an immediate allergic reaction to the mRNA vaccine or excipients be performed by a person with vaccine allergy expertise in a properly equipped setting. We suggest against premedication, split-dosing, or special precautions because of a comorbid allergic history.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".