Disproportionality analysis of adverse neurological and psychiatric reactions with the ChAdOx1 (Oxford-AstraZeneca) and BNT162b2 (Pfizer-BioNTech) COVID-19 vaccines in the United Kingdom
Bibliographic record
Abstract
ABSTRACT Objective The information on neurologic or psychiatric adverse reactions to the COVID-19 vaccines is limited. Our objective was to examine the odds of neurological and psychiatric adverse reactions to BNT162b2 (Pfizer-BioNTech) and ChAdOx1 (Oxford-AstraZeneca) COVID-19 vaccines. Methods We analyzed all Adverse Vaccine Reaction reports to the United Kingdom Medicines and Healthcare products Regulatory Agency between December 9, 2020 and June 30, 2021 that mentioned the BNT162b2 or ChAdOx1 vaccines. We compared the rates of adverse neurological and psychiatric reactions with ChAdOx1 to those with BNT162b2. P-values were obtained by a Bonferroni-adjusted Z-test for proportions. Results As of June 30, 2021, 53.2 M doses of ChAdOx1 and 46.1 M doses of BNT162b2 had been administered. We extracted information from 300,518 distinct reports. The number of individual adverse neurologic or psychiatric reaction reports were less than 200/M doses administered, except headache which was reported in 1,550 and 395 cases/M doses of ChAdOx1 and BNT162b2, respectively. Compared to BNT162b2, cerebral hemorrhagic or thrombotic events, headaches and migraines, Guillain-Barre syndrome and paresthesias, tremor and freezing, delirium, hallucinations, nervousness, poor sleep quality, and postural dizziness were more frequently reported with ChAdOx1. Reactions more frequently reported with BNT162b2 than ChAdOx1 were Bell’s palsy, facial paralysis, dysgeusia, anxiety, and presyncope or syncope. Conclusion Significant differences in the neurologic and psychiatric adverse event profiles of the ChAdOx1 and BNT162b2 vaccines may exist, emphasizing the need for additional research. The beneficial and protective effects of the COVID-19 vaccines far outweigh the low potential risk of neurologic and psychiatric reactions.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".