| 刘幸,刘向芳,陈洁,陈永刚,孙辉,杨敏,刘媛.头孢哌酮钠他唑巴坦钠ADR分析与预测模型构建[J].中国药事,2021,35(7):776-783 |
| 头孢哌酮钠他唑巴坦钠ADR分析与预测模型构建 |
| Model Construction of the Analysis and Prediction of Adverse Drug Reactions of Cefoperazone Sodium and Tazobactam Sodium |
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| DOI：10.16153/j.1002-7777.2021.07.008 |
| 中文关键词: 注射用头孢哌酮钠他唑巴坦钠 药品不良反应 预测模型 |
| 英文关键词: cefoperazone sodium and tazobactam sodium for injection adverse drug reactions prediction models |
| 基金项目:昆明市卫生科技项目(编号 2020-16-01-001、2021-16-01-0010)，昆明市卫生科技人才培养项目“千”工程(编号 2020-SW[后备]-60) |
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| 中文摘要: |
| 目的：分析注射用头孢哌酮钠他唑巴坦钠在昆明市医疗机构中使用的安全性，探索其发生药品不良反应(adverse drug reaction，ADR)的影响因素，以及因素之间的相关性，构建其发生ADR的预测模型，为本品在临床合理应用提供参考。方法：提取2015年1月-2020年6月期间，昆明市ADR报告监测数据库中注射用头孢哌酮钠他唑巴坦钠ADR报告242份作为观察组，同期使用注射用头孢哌酮钠他唑巴坦钠未发生ADR的250份病例作为对照组，收集2组患者的临床资料，采用多因素logistic回归分析发生ADR的相关因素，根据结果拟合构建发生ADR的预测模型；由受试者工作特征(ROC)曲线评价预测模型的效能。结果：统计学计算结果显示，年龄与原患疾病的例次呈正相关关系(Kendall's tau-b=0.490，P＜0.01)；用药时间与住院时间呈负相关关系(r=-0.244，P＜0.05)；多因素logistic 回归分析结果显示：老年人、肝肾功能损伤患者、用药时间在(11~15)d是头孢哌酮钠他唑巴坦钠发生ADR的相关因素，其预测模型为Logit(P)=1.642+1.543×老年人+1.356×肝肾功能损伤+1.835×用药天数(11~15)，该模型ROC曲线下面积为0.829，预测模型的灵敏度为90.7%，特异度为73.7%。结论：老年人、肝肾功能损伤、用药时间是头孢哌酮钠他唑巴坦钠发生ADR的相关因素。 |
| 英文摘要: |
| Objective: To analyze the safety of cefoperazone sodium and tazobactam sodium for injection in Kunming medical institutions and to explore the influencing factors of adverse drug reaction (ADR) and the correlation between the factors. To construct the prediction model of adverse reactions and provide references for the rational application of cefoperazone sodium and tazobactam sodium in clinical practice. Methods: From January, 2015 to June, 2020, 242 ADR reports of cefoperazone sodium and tazobactam sodium for injection in Kunming ADR monitoring database were extracted as the observation group, and 250 cases without adverse reactions of cefoperazone sodium and tazobactam sodium for injection during the same period were selected as the control group. The clinical data of the two groups were collected. Multivariate logistic regression was used to analyze the related factors of adverse reactions, and the prediction model of adverse reactions wasestablished according to the results. The effectiveness of the prediction model was evaluated by receiver operating characteristic (ROC) curve. Results: Correlation analysis showed that there was a positive correlation between age and the number of primary diseases (Kendall's tau-b = 0.490, P＜0.01). There was a negative correlation between medication time and hospitalization time (r = -0.244, P＜0.05). The results of multivariate logistic regression analysis showed that elderly patients with liver and kidney function injury and medication time (11-15 days) were related factors of adverse reactions of cefoperazone sodium and tazobactam sodium. The prediction model was logit (P) = 1.642+1.543×seniors+1.356×liver and kidney function injury+1.835×medication days (11- 15). The area under ROC curve of the model was 0.829. The sensitivity and specificity were 90.7% and 73.7%, respectively. Conclusion: Seniors, liver and kidney dysfunction and medication time 11~15 days are the related factors of adverse reactions of cefoperazone sodium and tazobactam sodium. |
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