Pharmacovigilance signals for congenital heart disease related to drug exposure: A disproportionality analysis based on the FAERS database.

Objectives: This real-world study aimed to identify pharmacovigilance signals for congenital heart disease (CHD) associated with drugs exposure and to characterize the phenotypic spectrum of CHD adverse event reports. Methods: Adverse event reports for drug potentially associated with CHD were collected from the US Food and Drug Administration Adverse Event Reporting System (FAERS) between January 2004 and September 2025. We used reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) to detect pharmacovigilance signals. The Bonferroni correction was employed to adjust for multiple comparisons and to further confirm the robustness of the signals. Results: We identified a total of 871 drugs with reported signals for CHD, of which 67 drugs met the criteria across all four disproportionality analysis methods. These drugs covered a wide range of categories, with nervous system agents and systemic antiinfectives being the most numerous. Further stratified analysis by therapeutic class revealed that antidepressive agents ( Conclusion: Through a comprehensive analysis of FAERS data, we identified pharmacovigilance signals for CHD associated with drug exposure and described the phenotypes of reported CHD events with suspected drug involvement. Our findings provide a valuable reference for hypothesis generation and future epidemiologic studies, and they support the ongoing pharmacovigilance of drug safety particularly during pregnancy.