Evidence map›Paper›PMID 40730792›Full record

ArticleNPJ vaccines2025

A Bayesian network analysis of the Pfizer COVID-19 vaccine in the paediatric population.

Tej Shukla, Helen J Mayfield, John C B Litt, Samuel J Brown, Jane Sinclair, Sophie Wen, Philip N Britton, Rajesh Puranik, Kirsty R Short, Tina Moghaddam and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ vaccines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Tej ShuklaGuy's and St Thomas' NHS Foundation Trust, London, UK. Shuklatd@gmail.com.
Helen J MayfieldSchool of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
John C B LittCollege of Medicine and Public Health, Flinders University, Adelaide, SA, Australia.
Samuel J BrownSchool of Chemistry and Molecular Biosciences, Faculty of Science, The University of Queensland, Brisbane, QLD, Australia.
Jane SinclairSchool of Chemistry and Molecular Biosciences, Faculty of Science, The University of Queensland, Brisbane, QLD, Australia.
Sophie WenCentre for Clinical Research, The University of Queensland, Brisbane, QLD, Australia.
Philip N BrittonDepartment of Infectious Diseases and Microbiology, Children's Hospital at, Westmead, NSW, Australia.
Rajesh PuranikDepartment of Cardiology, Royal Prince Alfred Hospital, Sydney, NSW, Australia.
Kirsty R ShortSchool of Chemistry and Molecular Biosciences, Faculty of Science, The University of Queensland, Brisbane, QLD, Australia.
Tina MoghaddamSchool of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
Olivia WilliamsSchool of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
Colleen L LauSchool of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
Amalie DydaSchool of Public Health, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Pfizer COVID-19 vaccines have been associated with an increased risk of myocarditis. However, COVID-19 infection is also associated with complications. A Bayesian network (BN), informed by Australian and international data, was created to determine individual risks and benefits of the Pfizer COVID-19 vaccine in the paediatric. The risk of myocarditis between vaccine-associated, COVID-19 and background rates was compared, as well as secondary outcomes such as hospitalization, and MIS-C. At a population level, hospitalizations, intensive care admissions and MIS-C cases prevented at differing transmission rates and vaccine coverage were analyzed. The model estimated that teenage males were 4.47 times more likely to develop myocarditis from COVID-19 compared to the vaccine. Furthermore, the risk of hospitalizations and MIS-C were more likely in the unvaccinated cohort for all ages. The population level benefits of COVID-19 Pfizer vaccine at mitigating myocarditis are more nuanced, contingent on age, transmission rates and vaccination coverage.

Identifiers

PMID40730792
PMCPMC12307593

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.