Evidence map›Paper›PMID 38543142›Full record

ArticlePharmaceuticals (Basel, Switzerland)2024

Serious Safety Signals and Prediction Features Following COVID-19 mRNA Vaccines Using the Vaccine Adverse Event Reporting System.

Jung Yoon Choi, Yongjoon Lee, Nam Gi Park, Mi Sung Kim, Sandy Jeong Rhie

Open access · goldAbstract read
In one paragraph

Article in Pharmaceuticals (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. pDNA Impurities in mRNA Vaccines.Microorganisms · 2025
    Article
  3. Article
  4. Article
  5. Article
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

5 authors at 1 institution in 1 country.

Jung Yoon ChoiGraduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Republic of Korea.
Yongjoon LeeConpapa Inc., Seoul 06164, Republic of Korea.
Nam Gi ParkGraduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Republic of Korea.
Mi Sung KimGraduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Republic of Korea.
Sandy Jeong RhieGraduate School of Pharmaceutical Sciences, Ewha Womans University, Seoul 03760, Republic of Korea.ORCID 0000-0003-2554-3370
Ewha Womans University · KR

Funding

Ministry of Education NRF-2020R1A6A1A03043528National Research Foundation of Korea 2020R1A2C1009224
6 · The paper itself

Abstract

We aimed to analyze the characteristics of serious adverse events following immunizations (AEFIs) to identify potential safety information and prediction features. We screened the individual case safety reports (ICSRs) in adults who received mRNA-based COVID-19 vaccines using the Vaccine Adverse Event Reporting System until December 2021. We identified the demographic and clinical characteristics of ICSRs and performed signal detection. We developed prediction models for serious AEFIs and identified the prognostic features using logistic regression. Serious ICSRs and serious AEFIs were 51,498 and 271,444, respectively. Hypertension was the most common comorbidity (22%). Signal detection indicated that the reporting odds ratio of acute myocardial infarction (AMI) was more than 10 times. Those who had experienced myocardial infarction (MI) were 5.7 times more likely to suffer from MI as an AEFI (95% CI 5.28-6.71). Moreover, patients who had atrial fibrillation (AF), acute kidney injury (AKI), cardiovascular accident (CVA), or pulmonary embolism (PE) were 7.02 times, 39.09 times, 6.03 times, or 3.97 times more likely to suffer from each AEFI, respectively. Our study suggests that vaccine recipients who had experienced MI, AF, AKI, CVA, or PE could require further evaluation and careful monitoring to prevent those serious AEFIs.

Indexed as

mRNA-based COVID-19 vaccineprediction modelserious adverse reactionssignal detectionVAERS

Identifiers

PMID38543142
PMCPMC10974993
OpenAlexW4392647052

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.