目的 通过对清开灵注射液的不良反应（adverse reaction，ADR）信号进行挖掘与评价，为临床合理用药和药品上市许可持有人上市后研究提供参考与指导。方法 对河南省不良反应数据库中2016年1月—2020年12月收集到的清开灵注射液的ADR报告进行数据处理、统计，使用报告比值比法（reporting odds ratio，ROR）、综合标准法（Medicines and Healthcare Products Regulatory Agency，MHRA）和贝叶斯置信传播神经网络法（Bayesian confidence propagation neural network，BCPNN）分别对清开灵注射液进行ADR信号挖掘，并对挖掘出的ADR信号进行分析与评价。结果 共提取出以清开灵注射液为怀疑药品的ADR报告3855例，数据处理后共得到6111例次ADR，共涉及15个系统器官分类（systematic organ classification，SOC）。ADR报告中女性患者数量多于男性患者，45～64岁的患者用药后发生的ADR例数最多，患者原患疾病最多的为呼吸系统疾病（88.02%），91.05%的患者用药疗程为1 d，95.62%的患者用药当天即发生了ADR，99%的患者ADR转归良好。3种信号检测方法分别挖掘出35、20、29个清开灵注射液ADR信号，其中新的ADR信号分别为11、9、9个。哮喘是3种信号检测方法均挖掘出来的信号强度最高的已知ADR，体温升高、感到寒冷、胸部不适是3种信号检测方法均挖掘出来的信号强度较高的新ADR。结论 通过3种信号检测方法对清开灵注射液进行信号挖掘，可促进清开灵注射液药物警戒信号的深入研究，有利于临床合理用药，提高清开灵注射液的安全性。

Objective To explore and evaluate the adverse reaction (ADR) signals of Qingkailing Injection (清开灵注射液), so as to provide reference and guidance for clinical rational use of drugs and post-marketing studies of drug marketing authorization holders. Methods The ADR reports of Qingkailing Injection collected from January 2016 to December 2020 in Henan Province ADR database were processed and statistically analyzed. Reporting odds ratio (ROR), comprehensive standard method (Medicines and Healthcare Products Regulatory Agency, MHRA) and Bayesian confidence propagation neural network (BCPNN) were used to mine ADR signals of Qingkailing Injection, and the mined ADR signals were analyzed and evaluated. Results A total of 3855 ADR reports with Qingkailing Injection as suspected drug were extracted, and 6111 ADR cases were obtained after data processing, involving 15 systematic organ classification (SOC). In the ADR report, the number of female patients was more than that of male patients, and the number of ADR cases occurred in patients between 45 and 64 years old after medication was the most, the primary disease of patients was respiratory system disease (88.02%), 91.05% of patients had a course of medication for one day, 95.62% of patients had ADR on the same day of medication, and 99% of patients had good outcome of adverse reactions. The three signal detection methods excavated 35, 20 and 29 ADR signals for Qingkailing Injection, and the new ADR signals were 11, 9 and 9, respectively. Asthma was the known ADR with the highest signal intensity detected by all the three signal detection methods, while elevated body temperature, cold feeling and chest discomfort were the new ADR with higher signal intensity detected by all the three signal detection methods. Conclusion This study can promote the in-depth study of pharmacovigilance signals of Qingkailing Injection by three signal detection methods, which is conducive to clinical rational drug use and improve the safety of Qingkailing Injection.

R285.64

河南省科技攻关计划：河南省药品上市许可持有人药品不良反应风险分级与应用研究（212102311047）