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Record W4403109742 · doi:10.1017/cjn.2024.299

Neurological Events Following COVID-19 Vaccination: Does Ethnicity Matter?

2024· article· en· W4403109742 on OpenAlexaffvenueabout
Manav V. Vyas, Robert Chen, Michael A. Campitelli, Tomi Odugbemi, Isobel Sharpe, Joseph Chu

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2024
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsToronto Western HospitalUniversity Health NetworkUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsEthnic groupVaccinationMedicineIncidence (geometry)Retrospective cohort studyCoronavirus disease 2019 (COVID-19)Intracerebral hemorrhagePediatricsCohortCerebral palsy2019-20 coronavirus outbreakDemographyStroke (engine)Internal medicineVirologyPhysical therapyDiseaseOutbreak

Abstract

fetched live from OpenAlex

We conducted a retrospective cohort study in Ontario, Canada between December 1, 2020 and June 31, 2021 to compare the incidence of neurological events (hospitalization or emergency room visit) within six weeks of COVID-19 vaccination in Chinese, South Asian and Other ethnic groups. Compared to Others, the crude rates after the first dose for Bell's palsy, ischemic stroke and intracerebral hemorrhage were lower in Chinese (34, 159 and 48 per 1,000,000 doses) and in South Asians (44, 148 and 32), but similar after adjusting for age, sex and vaccine type. Our findings should help encourage vaccination for all, irrespective of ethnicity.

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)0.002
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 score0.853
Threshold uncertainty score0.296

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.371
Teacher spread0.302 · 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".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

Explore more

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