Adverse events of special interest following the use of BNT162b2 in adolescents: a population-based retrospective cohort study
Bibliographic record
Abstract
Accruing evidence suggests an increased risk of myocarditis in adolescents from messenger RNA COVID-19 vaccines. However, other potential adverse events remain under-researched. We conducted a retrospective cohort study of adolescents aged 12–18 with a territory-wide electronic healthcare database of the Hong Kong population linked with population-based vaccination records and supplemented with age- and sex-specific population numbers. Two age- and sex-matched retrospective cohorts were formed to observe 28 days following the first and second doses of BNT162b2 and estimate the age- and sex-adjusted incidence rate ratios between the vaccinated and unvaccinated. Thirty AESIs adapted from the World Health Organization’s Global Advisory Committee on Vaccine Safety were examined. Eventually, the first-dose cohort comprised 274,881 adolescents (50.25% received the first dose) and the second-dose cohort 237,964 (50.29% received the second dose). Ninety-four (34.2 per 100,000 persons) adolescents in the first-dose cohort and 130 (54.6 per 100,000 persons) in the second-dose cohort experienced ≥1 AESIs. There were no statistically significant differences in the risk of any AESI associated with BNT162b2 except myocarditis [first-dose cohort: incidence rate ratio (IRR) = 9.15, 95% confidence interval (CI) 1.14–73.16; second-dose cohort: IRR = 29.61, 95% CI 4.04–217.07] and sleeping disturbances/disorders after the second dose (IRR = 2.06, 95% CI 1.01–4.24). Sensitivity analysis showed that, with myocarditis excluded as AESIs, no significantly elevated risk of AESIs as a composite outcome associated with vaccination was observed (P = 0.195). To conclude, the overall absolute risk of AESIs was low with no evidence of an increased risk of AESIs except myocarditis and sleeping disturbances/disorders.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".