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Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis
INTRODUCTION: Although messenger RNA (mRNA) vaccines have been developed and widely utilized to mitigate the coronavirus disease (COVID-19) pandemic, it is essential to describe the adverse events (AEs) following immunization. This study aimed to identify the patterns associated with serious AE repo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Healthcare
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753856/ https://www.ncbi.nlm.nih.gov/pubmed/36520333 http://dx.doi.org/10.1007/s40121-022-00742-5 |
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author | Lee, Min-Taek Choi, Wonbin You, Seung-Hun Park, Sewon Kim, Jeong-Yeon Nam, Dal Ri Lee, Ju Won Jung, Sun-Young |
author_facet | Lee, Min-Taek Choi, Wonbin You, Seung-Hun Park, Sewon Kim, Jeong-Yeon Nam, Dal Ri Lee, Ju Won Jung, Sun-Young |
author_sort | Lee, Min-Taek |
collection | PubMed |
description | INTRODUCTION: Although messenger RNA (mRNA) vaccines have been developed and widely utilized to mitigate the coronavirus disease (COVID-19) pandemic, it is essential to describe the adverse events (AEs) following immunization. This study aimed to identify the patterns associated with serious AE reports after mRNA COVID-19 vaccination in the World Health Organization (WHO)’s global scale database (VigiBase). METHODS: This study performed a latent class analysis (LCA) of reports of serious AEs following mRNA COVID-19 vaccination from VigiBase between December 28, 2020 , and February 28, 2022 (N = 312878). The Medical Dictionary for Regulatory Activities (MedDRA) System Organ Class (SOC) terms were selected for LCA. The reporting characteristics in accordance with the cluster were described. We used a multinomial logistic regression model to estimate the association between potential factors and each cluster. RESULTS: Five clusters of AE reports were distinguished through LCA: infection AEs (cluster 1), cardiac AEs (cluster 2), respiratory/thrombotic AEs (cluster 3), systemic AEs (cluster 4), and nervous system AEs (cluster 5). Compared to cluster 4, cluster 2 had a higher proportion of males (OR 2.98; 95% confidence interval (CI) 2.87–3.09), and cluster 1 had a longer time to onset than other AEs (≥ 14 days) (OR 16.2; 95% CI 15.5–16.9). CONCLUSION: Using LCA, we found five clusters of serious AEs following mRNA COVID-19 vaccination. Each cluster was distinguished by potential factors such as age, gender, region, and time to onset. We suggest that monitoring should carefully consider the patterns of young males with cardiac AEs and elderly individuals with thrombosis after respiratory AEs. Our findings could contribute to enhancing understanding of safety profiles and establishing management strategies for serious AEs of special interest following mRNA COVID-19 vaccination. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40121-022-00742-5. |
format | Online Article Text |
id | pubmed-9753856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Healthcare |
record_format | MEDLINE/PubMed |
spelling | pubmed-97538562022-12-15 Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis Lee, Min-Taek Choi, Wonbin You, Seung-Hun Park, Sewon Kim, Jeong-Yeon Nam, Dal Ri Lee, Ju Won Jung, Sun-Young Infect Dis Ther Original Research INTRODUCTION: Although messenger RNA (mRNA) vaccines have been developed and widely utilized to mitigate the coronavirus disease (COVID-19) pandemic, it is essential to describe the adverse events (AEs) following immunization. This study aimed to identify the patterns associated with serious AE reports after mRNA COVID-19 vaccination in the World Health Organization (WHO)’s global scale database (VigiBase). METHODS: This study performed a latent class analysis (LCA) of reports of serious AEs following mRNA COVID-19 vaccination from VigiBase between December 28, 2020 , and February 28, 2022 (N = 312878). The Medical Dictionary for Regulatory Activities (MedDRA) System Organ Class (SOC) terms were selected for LCA. The reporting characteristics in accordance with the cluster were described. We used a multinomial logistic regression model to estimate the association between potential factors and each cluster. RESULTS: Five clusters of AE reports were distinguished through LCA: infection AEs (cluster 1), cardiac AEs (cluster 2), respiratory/thrombotic AEs (cluster 3), systemic AEs (cluster 4), and nervous system AEs (cluster 5). Compared to cluster 4, cluster 2 had a higher proportion of males (OR 2.98; 95% confidence interval (CI) 2.87–3.09), and cluster 1 had a longer time to onset than other AEs (≥ 14 days) (OR 16.2; 95% CI 15.5–16.9). CONCLUSION: Using LCA, we found five clusters of serious AEs following mRNA COVID-19 vaccination. Each cluster was distinguished by potential factors such as age, gender, region, and time to onset. We suggest that monitoring should carefully consider the patterns of young males with cardiac AEs and elderly individuals with thrombosis after respiratory AEs. Our findings could contribute to enhancing understanding of safety profiles and establishing management strategies for serious AEs of special interest following mRNA COVID-19 vaccination. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40121-022-00742-5. Springer Healthcare 2022-12-15 2023-02 /pmc/articles/PMC9753856/ /pubmed/36520333 http://dx.doi.org/10.1007/s40121-022-00742-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/Open AccessThis article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Lee, Min-Taek Choi, Wonbin You, Seung-Hun Park, Sewon Kim, Jeong-Yeon Nam, Dal Ri Lee, Ju Won Jung, Sun-Young Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis |
title | Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis |
title_full | Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis |
title_fullStr | Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis |
title_full_unstemmed | Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis |
title_short | Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis |
title_sort | safety profiles of mrna covid-19 vaccines using world health organization global scale database (vigibase): a latent class analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9753856/ https://www.ncbi.nlm.nih.gov/pubmed/36520333 http://dx.doi.org/10.1007/s40121-022-00742-5 |
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