Evidence map›Paper›PMID 35814246›Full record

ArticleFrontiers in pharmacology2022

Profiling COVID-19 Vaccine Adverse Events by Statistical and Ontological Analysis of VAERS Case Reports.

Wenxin Guo, Jessica Deguise, Yujia Tian, Philip Chi-En Huang, Rohit Goru, Qiuyue Yang, Suyuan Peng, Luxia Zhang, Lili Zhao, Jiangan Xie and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.7field-weighted citation impact, top 3% of its field
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

17 citing papers in PubMed, 29 citations in OpenAlex.

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  17. COVID-19 Vaccines: An Updated Overview of Different Platforms.Bioengineering (Basel, Switzerland) · 2022
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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

11 authors at 4 institutions in 2 countries.

Wenxin GuoCollege of Literature, Science and the Arts, University of Michigan, Ann Arbor, MI, United States.
Jessica DeguiseCollege of Literature, Science and the Arts, University of Michigan, Ann Arbor, MI, United States.
Yujia TianDepartment of Cell Biology and Neuroscience, Rutgers University, New Brunswick, NJ, United States.
Philip Chi-En HuangCollege of Literature, Science and the Arts, University of Michigan, Ann Arbor, MI, United States.
Rohit GoruCollege of Literature, Science and the Arts, University of Michigan, Ann Arbor, MI, United States.
Qiuyue YangChongqing Engineering Research Center of Medical Electronics and Information Technology, School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing, China.
Suyuan PengNational Institute of Health Data Science, Peking University, Beijing, China.
Luxia ZhangNational Institute of Health Data Science, Peking University, Beijing, China.
Lili ZhaoDepartment of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, United States.
Jiangan XieChongqing Engineering Research Center of Medical Electronics and Information Technology, School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing, China.
Yongqun HeUnit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI, United States.
University of Michigan–Ann Arbor · USChongqing University of Posts and Telecommunications · CNPeking University · CNRutgers, The State University of New Jersey · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the beginning of the COVID-19 pandemic, vaccines have been developed to mitigate the spread of SARS-CoV-2, the virus that causes COVID-19. These vaccines have been effective in reducing the rate and severity of COVID-19 infection but also have been associated with various adverse events (AEs). In this study, data from the Vaccine Adverse Event Reporting System (VAERS) was queried and analyzed via the Cov19VaxKB vaccine safety statistical analysis tool to identify statistically significant (i.e., enriched) AEs for the three currently FDA-authorized or approved COVID-19 vaccines. An ontology-based classification and literature review were conducted for these enriched AEs. Using VAERS data as of 31 December 2021, 96 AEs were found to be statistically significantly associated with the Pfizer-BioNTech, Moderna, and/or Janssen COVID-19 vaccines. The Janssen COVID-19 vaccine had a higher crude reporting rate of AEs compared to the Moderna and Pfizer COVID-19 vaccines. Females appeared to have a higher case report frequency for top adverse events compared to males. Using the Ontology of Adverse Event (OAE), these 96 adverse events were classified to different categories such as behavioral and neurological AEs, cardiovascular AEs, female reproductive system AEs, and immune system AEs. Further statistical comparison between different ages, doses, and sexes was also performed for three notable AEs: myocarditis, GBS, and thrombosis. The Pfizer vaccine was found to have a closer association with myocarditis than the other two COVID-19 vaccines in VAERS, while the Janssen vaccine was more likely to be associated with thrombosis and GBS AEs. To support standard AE representation and study, we have also modeled and classified the newly identified thrombosis with thrombocytopenia syndrome (TTS) AE and its subclasses in the OAE by incorporating the Brighton Collaboration definition. Notably, severe COVID-19 vaccine AEs (including myocarditis, GBS, and TTS) rarely occur in comparison to the large number of COVID-19 vaccinations administered in the United States, affirming the overall safety of these COVID-19 vaccines.

Indexed as

adverse eventsCov19VaxKBCOVID-19COVID-19 vaccineontologyontology of adverse eventsSARS-CoV-2VAERS

Identifiers

PMID35814246
PMCPMC9263450
OpenAlexW4283451006

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.