基于真实世界监测数据的山东省儿童严重药品不良反应可视化分析  

Visualization Analysis of Severe Adverse Drug Reactions in Children of Shandong Based on Real-World Monitoring Data

作　　者：魏伟 权勤波 王维波 Wei Wei;Quan Qinbo;Wang Weibo(Dongying Institute for Food and Drug Control,Shandong Dongying 257000,China;Dongying People’s Hospital,Shandong Dongying 257091,China)

机构地区：[1]东营市食品药品检验研究院,山东东营257000 [2]东营市人民医院,山东东营257091

出　　处：《儿科药学杂志》2025年第2期18-22,共5页Journal of Pediatric Pharmacy

基　　金：山东省药品不良反应监测哨点课题,编号2023SDADRKY45。

摘　　要：目的:可视化分析展示儿童药品不良反应(ADR)的特点和规律,为推动儿童临床安全用药提供参考。方法:收集山东省在国家药品不良反应监测系统中儿童严重ADR报告进行统计分析,利用社会网络分析可视化展现ADR、系统器官分类(SOC)和联合用药网络中各要素的联系。结果:儿童严重ADR报告共6811份,患儿例数随年龄增长而减少。抗感染药物是引起儿童严重ADR最主要的药品类别。高频联合用药药品54例,高频ADR为47例,皮肤及其附件损害和全身性损害共同出现的次数最多。结论:应通过掌握患儿信息、熟悉药理特点、把握发生规律,合理选择药品并识别隐匿损害。加强药学监护、重视联合用药以预防和减少严重ADR,促进儿童安全用药。Objective:To visually analyze the characteristics and regularities of adverse drug reactions(ADR)in children,so as to provide reference for promoting the clinical safety of drug use in children.Methods:Statistical analysis was performed on severe ADR reports in children from the National Adverse Drug Reactions Monitoring System of Shandong.Social network analysis was performed to visualize correlation between the elements in ADR,system organ class(SOC)and drug combination networks.Results:Totally 6,811 severe ADR reports were retrieved.The number of pediatric patients decreased with age overall.Anti-infective drugs were the main category of drugs that cause severe ADR in children.There were 54 cases of high frequency drug combination,47 cases of high frequency ADR,and the common occurrence of skin and its appendages and systemic damage took the lead.Conclusion:Drugs should be selected rationally and hidden damage should be recognized by having general information about children,familiarizing with pharmacological characteristics,grasping the pattern of occurrence,strengthening pharmacological supervision and emphasizing drug combination to prevent and reduce severe ADR and promote the safe medication in children.

关 键 词：药品不良反应 儿童用药 信息可视化技术 社会网络分析 

分 类 号：R969.3[医药卫生—药理学]