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Record W4323353183 · doi:10.1093/jcag/gwac036.170

A170 ADVERSE EVENTS & SEROLOGICAL RESPONSES FOLLOWING SARS-COV-2 VACCINATION IN INDIVIDUALS WITH INFLAMMATORY BOWEL DISEASE

2023· article· en· W4323353183 on OpenAlexaffabout
Ante Markovinović, Michelle Herauf, Joshua Quan, Lindsay Hracs, Joseph W. Windsor, Nasrin Sharifi, Stephanie Coward, Léa Caplan, Julia Gorospe, Christopher Ma, Remo Panaccione, R Ingram, Jamil N. Kanji, G Tipples, Jessalyn K. Holodinsky, C Berstein, Sasha Bernatsky, Eric I. Benchimol, Gilaad G. Kaplan

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of TorontoMcGill UniversityUniversity of Calgary
Fundersnot available
KeywordsMedicineVaccinationAdverse effectInflammatory bowel diseaseCohortSerologyProspective cohort studyInternal medicineImmunizationImmunologyDiseaseAntibody

Abstract

fetched live from OpenAlex

Abstract Background The rapid development and distribution of SARS-CoV-2 vaccines has raised concerns surrounding vaccine safety in immunocompromised populations, such as those with inflammatory bowel disease (IBD). Purpose We described adverse events (AEs) following SARS-CoV-2 vaccination in those with IBD and determined relationships between AEs to post-vaccination antibody titres. Method Individuals with IBD from a prospective cohort in Calgary, Canada (n=670) who received a 1st, 2nd, 3rd, and/or 4th dose of a SARS-CoV-2 vaccine (Pfizer-BioNTech, Moderna, and/or AstraZeneca) were interviewed via telephone for AEs using the Adverse Events Following Immunization form. Subsequently, we assessed injection site reaction as a specific AE outcome. Multivariable logistic regression models were used to assess the association between anti-SARS-CoV-2 spike protein antibody (anti-S) levels within 1–12 weeks of vaccination and injection site reaction following 1st, 2nd, and 3rd dose vaccination. Models were adjusted for age, sex, IBD type, IBD medications, vaccine type, and prior COVID-19 infection. Additionally, we evaluated the risk of flare of IBD within 30 days of vaccination via chart review. Result(s) Table 1 describes AEs in individuals with IBD following 1st dose (n=331), 2nd dose (n=331), 3rd dose (n=195), and 4th dose (n=100) of a SARS-CoV-2 vaccine. AEs were reported in 83.3% of participants after 1st dose, 79.1% after 2nd dose, 77.4% after 3rd dose, and 67.0% after 4th dose. Injection site reaction (pain, redness, etc.) was the most common AE (50.8% of AEs), with fatigue and malaise (18.1%), headache and migraine (8.6%), musculoskeletal discomfort (8.2%), and fever and chills (6.5%) also commonly reported. Multivariable logistic regression determined no associations between anti-S concentration and injection site reaction for all doses. Age above 65 years was associated with decreased injection site reaction following 1st and 3rd doses, while female sex and mRNA vaccine type were associated with increased injection site reaction following 1st and 2nd doses. Prior COVID-19 infection, IBD type, and medication class were not associated with injection site reaction with any dose. Only one participant was diagnosed with a severe AE requiring hospitalization: Immune thrombocytopenic purpura (ITP) following 2nd dose of a Pfizer vaccination. No cases of IBD flare occurred within 30 days of vaccination. Image Conclusion(s) AEs following SARS-CoV-2 vaccination are generally mild and become less common with each consecutive dose. Antibody levels following each dose of the vaccine were not associated with injection site reactions. Females, those under 65 years of age, and those administered mRNA vaccines were more likely to experience an injection site reaction. Prior COVID-19 infection, IBD type, and IBD medication class did not predict injection site reactions. Vaccination was not associated with IBD flare within 30 days of vaccination. Please acknowledge all funding agencies by checking the applicable boxes below Other Please indicate your source of funding; Helmsley Disclosure of Interest A. Markovinovic: None Declared, M. Herauf: None Declared, J. Quan: None Declared, L. Hracs: None Declared, J. Windsor: None Declared, N. Sharifi: None Declared, S. Coward: None Declared, L. Caplan: None Declared, J. Gorospe: None Declared, C. Ma Grant / Research support from: Ferring, Pfizer, , Consultant of: AbbVie, Alimentiv, Amgen, Ferring, Pfizer, Takeda, , Speakers bureau of: AbbVie, Alimentiv, Amgen, Ferring, Pfizer, Takeda, R. Panaccione Grant / Research support from: AbbVie, Ferring, Janssen, Pfizer, Takeda, Consultant of: Abbott, AbbVie, Alimentiv, Amgen, Arena, AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Celltrion, Cosmos Pharmaceuticals, Eisai, Elan, Eli Lilly, Ferring, Galapagos, Genentech, Gilead Sciences, GlaxoSmithKline, Janssen, Merck, Mylan, Oppilan Pharma, Pandion Therapeutics, Pandion Pharma, Pfizer, Progenity, Protagonist, Roche, Sandoz, Satisfai Health, Schering-Plough, Shire, Sublimity Therapeutics, Takeda, Theravance, UCB, Speakers bureau of: AbbVie, Arena, Celgene, Eli Lilly, Ferring, Gilead Sciences, Janssen, Merck, Pfizer, Roche, Sandoz, Shire, Takeda, R. Ingram: None Declared, J. Kanji: None Declared, G. Tipples: None Declared, J. Holodinsky: None Declared, C. Berstein Grant / Research support from: AbbVie, Amgen, Janssen, Pfizer, Takeda, Speakers bureau of: AbbVie, Janssen, Pfizer, Takeda, D. Mahoney: None Declared, S. Bernatsky: None Declared, E. Benchimol: None Declared, G. Kaplan Grant / Research support from: Ferring, Speakers bureau of: AbbVie, Janssen, Pfizer

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.027
GPT teacher head0.316
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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