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

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.

Keywords

• serious adverse reactions
• signal detection
• prediction model
• mRNA-based COVID-19 vaccine
• VAERS