A real-world pharmacovigilance study of esketamine nasal spray.

Yaqing Chen, Hangye Gu, Wenwei Li, Yong Chen
Author Information
  1. Yaqing Chen: Key Specialty of Clinical Pharmacy, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, Guangdong, China.

Abstract

Mining and updating the post-marketing safety signals of esketamine nasal spray for better identification of adverse drug event (ADE) signals and medication monitoring during clinical use to ensure patient medication safety. Downloading data from the US Food and Drug Administration Adverse Event Reporting System from Q1 2019 to Q2 2023, the reporting odds ratio, proportional reporting ratio, Multi-item Gamma Poisson Shrinker, and Bayesian Confidence Propagation Neural Network methods of the disproportionality method were used to mine and analyze ADEs, and finally to screen for signals of ADEs with esketamine nasal spray as the primary suspected drug. The Preferred Terminology of the Medical Dictionary of Regulatory Activities (version 26.0) was used to standardize the description of ADEs and to attribute ADEs to the System Organ Classification. A total of 5132 ADEs reports of esketamine nasal spray as the primary suspected drug were obtained from the Food and Drug Administration Adverse Event Reporting System. The most frequently observed ADEs are dissociation, sedation, and hypertension, while some new rare signals have been detected, such as interstitial cystitis, substance abuse, and drug diversion. The present study identified significant new ADEs signals for esketamine nasal spray, which may provide a source for healthcare professionals to assess patients' symptoms and risk identification.

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MeSH Term

Humans
Ketamine
Pharmacovigilance
Nasal Sprays
United States
Adverse Drug Reaction Reporting Systems
Male
Adult
Female
Middle Aged
United States Food and Drug Administration
Bayes Theorem
Adolescent
Young Adult

Chemicals

Ketamine
Esketamine
Nasal Sprays

Word Cloud

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