Article

Escitalopram Adverse Events in Real-World Databases: Signal Detection, Prediction Modeling, and Network Toxicology

2026-07-14

Abstract excerpt

<title>Abstract</title> <p>Aim This study aimed to identify the molecular mechanisms underlying escitalopram-related adverse events (AEs) and systematically assess pharmacovigilance signals. Methods Using the FAERS and JADER databases (2016Q1–2025Q4), we applied disproportionality analyses (ROR, PRR, BCPNN, MGPS) to detect AE signals. A machine learning framework incorporating six algorithms was developed to pr...

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Literature Corpus work: a435521f-fd56-5c4b-b695-78eb4d70dab5
DOI: 10.21203/rs.3.rs-10281900/v1

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