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Record W4416562599 · doi:10.3934/medsci.2025023

COVID-19 vaccines and autoimmune disorders: A scoping review

2025· article· en· W4416562599 on OpenAlexaff
Claudia Chaufan, Laurie Manwell, Camila Heredia, Jennifer L. McDonald

Bibliographic record

VenueAIMS Medical Science · 2025
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsWilfrid Laurier UniversityYork University
Fundersnot available
KeywordsVaccinationAutoimmune diseaseAutoimmunityDiseaseAdverse effectRheumatoid arthritisSystemic lupus erythematosusType 1 diabetes

Abstract

fetched live from OpenAlex

BackgroundUpon the global COVID-19 vaccination campaign, unprecedented in the history of public health, concerns have emerged regarding potential associations between vaccination and autoimmune disorders. Historical research has long identified mechanisms by which vaccines might trigger or unmask autoimmune processes. However, systematic synthesis of evidence concerning COVID-19 vaccines and autoimmunity remains limited.ObjectiveTo review the literature on associations between COVID-19 vaccination and autoimmunity, focusing on six conditions: Graves' disease, Hashimoto's thyroiditis, multiple sclerosis, rheumatoid arthritis, systemic lupus erythematosus, and type 1 diabetes mellitus.MethodsWe conducted a scoping review of 109 studies published in 2022, retrieved from PubMed and the WHO COVID-19 databases. Inclusion criteria encompassed English-language articles reporting empirically verifiable clinical manifestations of autoimmune disease associated with any COVID-19 vaccine, without restrictions by population, geography, or study type.ResultsAcross 109 included studies, relapses or flares in patients with autoimmune disorders were reported in nearly 60% of studies, while about one-quarter described new-onset autoimmune disorders in persons without prior autoimmunity. Several mechanisms of action linking COVID-19 vaccination and autoimmune disorders were reported, such as autoimmune inflammatory syndrome induced by adjuvants, molecular mimicry, bystander immune activation, and interactions with immunosuppressive and disease modifying therapies. Serious adverse events, though less common than mild or moderate ones, were also reported. General and population-specific vaccine efficacy were claimed but empirical support was often lacking.ConclusionsThis review highlights the substantial patterns of reported associations of autoimmune disorders following COVID-19 vaccination, in patients with and without prior autoimmunity. The general and population-specific benefits of vaccination are claimed, but evidence for them is lacking. A proper evaluation of risks and benefits is needed to support vaccination recommendations given the reported associations between it and autoimmune disorders.

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 distilled prediction

Teacher imitation

Not 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)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.438
Teacher spread0.393 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2025
Admission routes1
Has abstractyes

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