Four major algorithms used for signal detection.

BackgroundMirtazapine is a pharmacological agent commonly utilized as a first-line treatment for major depressive disorder, exhibiting both noradrenergic and selective serotonergic activity. Currently, there is an absence of a comprehensive and systematic review of the adverse events (AEs) associated with mirtazapine. Consequently, this study aims to assess the safety profile of mirtazapine in real-world clinical practice by performing an in-depth analysis of data from the Food and Drug Administration’s Adverse Event Reporting System (FAERS).MethodsThis study collected all real-world adverse event data related to mirtazapine from the FAERS database spanning from Q1 2004 to Q4 2024. Disproportionality analysis methods were employed, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS), to assess the associations between mirtazapine and major medical events.ResultsOur study identified a total of 14,237 adverse event reports related to mirtazapine from the FAERS database, of which 2,954 had available data. The results identified several previously unreported adverse events, including prolonged QT interval on electrocardiogram, insomnia, coma, falls, and drug toxicity. AEs related to mirtazapine occurred across 27 system organ classes (SOCs), primarily including Nervous System Disorders, Investigations, and Surgical and Medical Procedures. The onset of adverse events typically occurred within one month of mirtazapine administration, though it is important to note that the risk of AEs persists even in the following year.ConclusionOur research findings are consistent with clinical observations. Additionally, we have identified new adverse reactions related to mirtazapine. These results provide valuable evidence for further guiding safety research on mirtazapine. They also help clinicians place greater emphasis on monitoring its AEs during use.