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Updated guidance regarding the risk of allergic reactions to COVID-19 vaccines and recommended evaluation and management: A GRADE assessment and international consensus approach
Matthew Greenhawt, Timothy E. Dribin, Elissa M. Abrams, Marcus Shaker, Derek K. Chu, David B.K. Golden, Cem Akin, Aikaterini Anagnostou, Faisal ALMuhizi, Waleed Alqurashi, Peter D. Arkwright, James L. Baldwin, Aleena Banerji, Philippe Bégin, Moshe Ben‐Shoshan, Jonathan A. Bernstein, Theresa Bingemann, Carsten Bindslev‐Jensen, Kim Blumenthal, Aideen Byrne, J. Cahill, Scott B. Cameron, Dianne E. Campbell, Ronna L. Campbell, Michael Cavender, Edmond S. Chan, R. Sharon Chinthrajah, Pasquale Comberiati, Jacqueline J. Eastman, Anne K. Ellis, David M. Fleischer, Adam Fox, Pamela A. Frischmeyer‐Guerrerio, Rémi Gagnon, Lene H. Garvey, Mitchell H. Grayson, Ghislaine Annie Clarisse Isabwe, Nicholas Hartog, David Hendron, Caroline C. Horner, Johnathan O'B Hourihane, E.A. Ba, Manstein Kan, Blanka Kaplan, Constance H. Katelaris, Harold Kim, John M. Kelso, David A. Khan, David M. Lang, Dennis K. Ledford, Michael Levin, Phil Lieberman, Richard Loh, Douglas P. Mack, Bruce Mazer, K Mody, G. Mosnaim, Daniel Munblit, S. Shahzad Mustafa, Anil Nanda, Richard Nathan, John Oppenheimer, Iris M. Otani, Miguel Park, Ruby Pawankar, Kirsten P. Perrett, Jonny Peter, Matthieu Picard, Mitchell M. Pitlick, Allison Ramsey, Trine Holm Rasmussen, Melinda M. Rathkopf, Hari Reddy, Kara Robertson, Pablo Rodríguez del Río, Stephen Sample, Ajay Sheshadri, Javed Sheik, Sayantani Sindher, Jonathan M. Spergel, Cosby A. Stone, David R. Stukus, Mimi L.K. Tang, James M. Tracy, Paul Turner, Timothy K. Vander Leek, Dana Wallace, Julie Wang, Susan Wasserman, David Weldon, Anna R. Wolfson, Margitta Worm, Mona‐Rita Yacoub
Bibliographic record
VenueJournal of Allergy and Clinical Immunology · 2023
Typereview
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsUniversité de MontréalStollery Children's HospitalHôpital Maisonneuve-RosemontQueen's UniversityBC Children's HospitalUniversity of British ColumbiaFraser HealthUniversity of AlbertaMcGill UniversityUniversity of OttawaCentre Hospitalier Universitaire Sainte-JustineMcMaster UniversityMcMaster University Medical CentreUniversity of ManitobaSt. Joseph’s Healthcare HamiltonSt Joseph's Health CareUniversity of CalgaryImpactWestern UniversityMontreal Children's Hospital
FundersNational Institute of Allergy and Infectious DiseasesSanofi GenzymeGenentechAgency for Healthcare Research and QualityLEO PharmaBausch HealthPfizerIncyteAmerican Lung AssociationNational Peanut BoardBioCrystNational Institutes of HealthRegeneron PharmaceuticalsMylanCelldex TherapeuticsJapan Association for Chemical InnovationAmgenAustralasian Society of Clinical Immunology and AllergyMcGill UniversityDanoneAmerican Academy of Allergy, Asthma and Immunology FoundationMassachusetts General HospitalNational Center for Advancing Translational SciencesTeva Pharmaceutical IndustriesWorld Health OrganizationSanofiAimmune TherapeuticsCSL BehringAstraZenecaAstellas PharmaFood Allergy Research and EducationAsthma and Allergy Foundation of AmericaGlaxoSmithKline
KeywordsMedicineVaccinationAllergyPandemicImmunologyIntensive care medicinePediatricsCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)Internal medicine
Abstract
No abstract in any covered source. Its absence is recorded, not treated as a negative.
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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.
metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score0.564
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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.
Opus teacher head0.169
GPT teacher head0.461
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation status
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.
The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview
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".
Quick stats
Citations20
Published2023
Admission routes2
Has abstractno