目的 挖掘真实世界碳青霉烯类药物不良反应(adverse drug reaction，ADR)信号，分析其主要ADR产生的影响因素，为临床安全用药提供针对性的参考建议。方法 收集陕西省ADR监测中心2018-2022年的碳青霉烯类ADR报告，进行ADR信号挖掘及影响因素分析。结果 最终纳入美罗培南和亚胺培南ADR报告478份，严重ADR报告占21。13%，65岁以上患者占44。08%;美罗培南中儿童ADR报告占比较高(20。54%)。美罗培南检测到的强信号为转氨酶升高和肝功能异常，患者的用药疗程对发生肝胆系统损害有显著影响(P<0。01);亚胺培南的强信号是中枢系统损害，患者的性别和年龄影响显著(P<0。05)。结论 碳青霉烯类发生严重ADR的可能性较高，用药初期需重视ADR监测。对使用美罗培南的患者用药1周左右进行肝、肾功能检查，加强对0～14岁儿童的用药监护。对使用亚胺培南的男性、年龄≥65岁的患者，合理调整用药剂量，减少其中枢系统不良反应的发生。
Signal mining and influencing factor analysis of adverse reactions of carbapenems
Objective To explore the adverse drug reaction(ADR)signals of carbapenems in the real world,to analyze the main influencing factors of ADR arising,and to provide targeted reference suggestions for clinical safe medication.Methods The ADR reports of carbapenems from the ADR monitoring center of Shaanxi province from 2018 to 2022 were collected,and ADR signal mining and influencing factor analysis were performed.Results A total of 478 reports of meropenem and imipenem included,with severe ADR reports accounting for 21.13%and 44.08%of patients≥65.Among meropenem,children's ADR reports were relatively high(20.54%).The strong signals detected in meropenem were elevated transaminases and abnormal liver function.The duration of medication in patients had a significant impact on the occurrence of liver and biliary system damage(P<0.01).The strong signal in imipenem was central system damage,and the gender and age of patients showed a significant impact on the occurrence of central system damage(P<0.05).Conclusion The frequency of severe ADR in carbapenems was high,and ADR monitoring should be emphasized in the early stage of medication.For patients who use meropenem,liver and kidney function tests should be conducted around a week after medication,especially strengthening medication monitoring should be performed for children aged 0-14.For males and patients aged above 65 who use imipenem,the dosage of medication should be adjusted reasonably to reduce the occurrence of adverse reactions in the central nervous system.
carbapenemsmeropenemimipenemadverse drug reactionsignal mining
NETL
NSTL
万方数据
维普
