MétaCan
Menu
← Back to cohort
Record W3153812929 · doi:10.1101/2021.04.11.21255138

Vaccination of Front-Line Workers with the AstraZeneca COVID-19 Vaccine: Benefits in the Face of Increased Risk for Prothrombotic Thrombocytopenia

2021· preprint· en· W3153812929 on OpenAlexaffabout
Amin Adibi, Mohammad Mozafarihashjin, Mohsen Sadatsafavi

Bibliographic record

VenuemedRxiv · 2021
Typepreprint
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsSinai Health SystemLunenfeld-Tanenbaum Research InstituteCentre for Advancing Health Outcomes
Fundersnot available
KeywordsVaccinationMedicineFront lineCoronavirus disease 2019 (COVID-19)VirologyInternal medicineDiseaseGeographyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

ABSTRACT Background In March 2021, a number of regulatory and advisory bodies around the world recommended against using the AstraZeneca COVID-19 vaccine in younger adults pending further review of the risk for vaccine-induced prothrombotic immune thrombocytopenia (VIPIT). As an example, we consider the Canadian province of British Columbia (BC) which halted its front-line workers vaccination program with the AstraZeneca vaccine. The province received an additional 246,700 doses of AstraZeneca vaccine in the weeks before April 11th, enough to provide the first dose of vaccine to all unvaccinated front-line workers. It is unclear whether the alternative, mRNA vaccines can be immediately made available to front-line workers. Methods We reviewed the latest available evidence and used compartmental modelling to 1) compare the expected number of deaths due to COVID-19 and VIPIT under the scenarios of immediately continuing vaccination of front-line workers with the AstraZeneca vaccine or delaying it in favour of mRNA vaccines from a societal perspective, and 2) compare the individual mortality risk of immediately receiving the AstraZeneca vaccine with waiting to receive an mRNA vaccine later from a personal perspective. Results We estimate that if British Columbia continues the front-line worker vaccination program with the AstraZeneca vaccine, we expect to see approximately 45,000 fewer cases of COVID-19, 800 fewer hospitalizations, 120 fewer COVID-related deaths, and 2,300 fewer cases of Long COVID from April 15th to October 1st, 2021, for an expected number of VIPIT-related deaths of 0.674 [95% CI 0.414-0.997]. In the same period and in areas of high transmission ( R 0 =1.30), the projected excess risk of mortality due to COVID-19 and VIPIT was significantly higher in the delayed vaccination with mRNA vaccines scenario (3.5 to 4.5 times higher risk) than that of immediate vaccination with the AstraZeneca vaccine for those between 30 and 69 years of age. In areas with lower levels of transmission ( R 0 =1.15), the projected excess risk of mortality was 1.8 to 3.4 times higher in the delayed vaccination with mRNA vaccines scenario for those between 30 and 69 years of age. For those under 30, immediate vaccination with the AstraZeneca vaccine posed a higher risk than delayed vaccination with an mRNA vaccine, regardless of the level of transmission in the community. Conclusions The benefits of continuing immunization of front-line workers with the AstraZeneca vaccine far outweigh the risk both at a societal level and at a personal risk level for those over 40, and those over 30 in high-risk areas.

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)0.004
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.052
GPT teacher head0.351
Teacher spread0.299 · 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

Citations2
Published2021
Admission routes2
Has abstractyes

Explore more

Same venuemedRxiv→Same topicSARS-CoV-2 and COVID-19 Research→French-language works237,207→