MétaCan
Menu
Back to cohort
Record W4280505772 · doi:10.1016/j.blre.2022.100970

No apparent association between mRNA COVID-19 vaccination and venous thromboembolism

2022· review· en· W4280505772 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBlood Reviews · 2022
Typereview
Languageen
FieldMedicine
TopicHeparin-Induced Thrombocytopenia and Thrombosis
Canadian institutionsUniversity of OttawaOttawa HospitalMcMaster UniversitySaskatchewan Cancer AgencyUniversity of Saskatchewan
Fundersnot available
KeywordsVaccinationMedicineCoronavirus disease 2019 (COVID-19)ImmunologyImmune systemThrombosisIntensive care medicineInternal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

By January 2022 over ten billion doses of COVID-19 vaccines had been administered worldwide. Concerns about COVID-19 vaccine-associated thrombosis arose after the characterization of a rare prothrombotic condition associated with adenoviral vector-based COVID-19 vaccines known as vaccine-induced immune thrombotic thrombocytopenia (VITT). Although mRNA COVID-19 vaccines have not been linked to VITT, concerns about thrombosis after vaccination persist despite safety data from hundreds of millions of recipients of mRNA COVID-19 vaccines. With widespread vaccination some VTE will occur shortly after vaccination by chance alone because VTE is a common condition that affects 1 to 2 in 1000 persons each year. Detailed analysis is required to determine whether these VTE events are coincidental or associated when they occur in close proximity to mRNA vaccine administration. This paper will review what is currently known about rates of VTE after mRNA vaccination in adults, discuss the reasons why uncertainty on this topic persists, and briefly review the implications of these findings for clinical practice and health policy.

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.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.158
GPT teacher head0.400
Teacher spread0.241 · 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