No apparent association between mRNA COVID-19 vaccination and venous thromboembolism
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".