| アブストラクト | INTRODUCTION: The rapid development of COVID-19 vaccines has provided crucial tools for pandemic control, but the occurrence of vaccine-related adverse events (AEs) underscores the need for comprehensive monitoring. METHODS: This study analyzed the Vaccine Adverse Event Reporting System (VAERS) data from 2020-2022 using statistical methods such as zero-truncated Poisson regression and logistic regression to assess associations with age, gender groups, and vaccine manufacturers. RESULTS: Logistic regression identified 26 System Organ Classes (SOCs) significantly associated with age and gender. Females displayed especially higher odds in SOC 19 (Pregnancy, puerperium and perinatal conditions), while males had higher odds in SOC 25 (Surgical and medical procedures). Older adults (>65) were more prone to symptoms like Cardiac disorders, whereas those aged 18-65 showed susceptibility to AEs like Skin and subcutaneous tissue disorders. Moderna and Pfizer vaccines induced fewer SOC symptoms compared to Janssen and Novavax. The zero-truncated Poisson regression model estimated an average of 4.243 symptoms per individual. CONCLUSION: These findings offer vital insights into vaccine safety, guiding evidence-based vaccination strategies and monitoring programs for precise and effective outcomes. |
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| ジャーナル名 | Expert review of vaccines |
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| 投稿日 | 2023/12/8 |
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| 投稿者 | Li, Yiming; Lundin, Sori K; Li, Jianfu; Tao, Wei; Dang, Yifang; Chen, Yong; Tao, Cui |
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| 組織名 | McWilliams School of Biomedical Informatics, the University of Texas Health;Science Center at Houston, Houston, TX, USA.;Department of Biostatistics & Data Science, School of Public Health, the;University of Texas Health Science Center at Houston, Houston, TX, USA.;Department of Artificial Intelligence and Informatics, Mayo Clinic, Jacksonville,;FL, USA.;Department of Biostatistics, Epidemiology, and Informatics, Perelman School of;Medicine, University of Pennsylvania, Philadelphia, PA, USA. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/38063069/ |
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