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基于美国FAERS数据库的右佐匹克隆不良事件信号挖掘与分析

Data Mining of Adverse Drug Reaction Signals for Eszopiclone Based on FAERS Database
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摘要 目的:分析右佐匹克隆上市后的药品不良反应(ADR)信号,为临床用药安全提供参考。方法:利用美国食品药品监督管理局不良事件报告系统(FAERS)数据库,使用OpenVigil 2.1数据平台,收集右佐匹克隆从美国上市至2023年3月31日的ADR报告。采用频率法检测右佐匹克隆的ADR信号,并分别按照发生频次和信号强度进行排序。结果:获得右佐匹克隆相关的ADR报告9131份,检测到ADR信号分别为77个。按发生频次排序,发生最多的ADR是味觉障碍(3162例),可见于其药品说明书,自杀意念在药品说明书中未出现;按信号强度排序,右佐匹克隆的入睡困难(报告比值比为225.402)位列首位,毛发稀少未被其药品说明书提及。结论:建议临床不仅应关注药物最常见的精神系统系统ADR,还应关注药品说明书中未报道的ADR。 Objective:To analyze the signals of adverse drug reactions(ADR)after eszopiclone,and to provide reference for clinical drug safety.Methods:The OpenVigil 2.1 data platform was used to collect ADR reports of dexzopiclon from the launch of eszopiclone in the US until March 31,2023,using the FDA Adverse Event Reporting System(FAERS)database.The ADR signals of eszopiclone were detected by a frequency method and sorted according to frequency and signal intensity.Results:There were 9131 ADR reports related to eszopiclone,and 77 ADR signals were detected respectively.The ADR with the most frequent occurrence was abnormal taste(3162 cases),which could be seen in the drug instructions.Suicidal attempt did not appear in the drug instructions.In order of signal strength,eszopiclone’s initial insomnia(reported odds ratio of 225.402)was at the top of the list,and hypotrichosis was not mentioned in drug instructions.Conclusion:It is suggested that clinical attention should be paid not only to ADR of the most common psychiatric system,but also to ADR not reported in the drug package inserts.
作者 徐寅鹏 黄鹂 李方 周甜 XU Yinpeng;HUANG Li;LI Fang;ZHOU Tian(Department of Pharmacy,the Ninth People’s Hospital of Zhengzhou,Zhengzhou 450000,China;Department of Pharmacy,Women&infants Hospital of Zhengzhou,Zhengzhou 450000,China;Henan Children’s Hospital,Zhengzhou 450000,China)
出处 《药学与临床研究》 2024年第3期258-261,共4页 Pharmaceutical and Clinical Research
基金 河南省重点研发与推广专项科技攻关(222102310496)。
关键词 右佐匹克隆 不良反应 美国食品药品监督管理局药物不良事件报告系统 数据挖掘 Eszopiclone Adverse drug reaction FDA Adverse Drug Event Reporting System Data mining
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