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Safety Profiles of mRNA COVID-19 Vaccines Using World Health Organization Global Scale Database (VigiBase): A Latent Class Analysis

Min‐Taek Lee, Wonbin Choi, Seung‐Hun You, Sewon Park, Jeong-Yeon Kim, Dal Ri Nam, Ju Won Lee, Sun‐Young Jung

2022Infectious Diseases and Therapy11 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

MedicineCoronavirus disease 2019 (COVID-19)Latent class model2019-20 coronavirus outbreakScale (ratio)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)DatabaseVirologyData sciencePathologyCartographyComputer scienceGeographyDiseaseOutbreakInfectious disease (medical specialty)Machine learningSARS-CoV-2 and COVID-19 ResearchHeparin-Induced Thrombocytopenia and ThrombosisCOVID-19 Impact on Reproduction