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β-内酰胺类抗菌药物不良反应监测及风险预测模型的建立
蒋俊杰1,王法财1,沈炳香1,聂松柳1,段自皞1,朱枝祥2
0
(1. 安徽医科大学附属六安医院,安徽六安 237005;2. 北京中 医药大学,北京 100029)
摘要:
目的:通过监测安徽医科大学附属六安医院患儿使用 β-内酰胺类抗菌药物所致药物不良反应(ADR),分析 ADR 发生情 况及影响因素,并建立其风险预测模型。 方法:选取 2018 年 5 月至 2022 年 2 月安徽医科大学附属六安医院儿科使用 β-内酰胺 类抗菌药物的患儿作为 ADR 监测对象,统计分析 ADR 患儿临床资料。 按使用 β-内酰胺类抗菌药物是否发生 ADR,分为 ADR 组和无 ADR(nADR)组,并采用 Logistic 回归分析筛选其独立危险因素,建立列线图预测模型。 结果:共监测使用 β-内酰胺类抗 菌药物的患儿 453 例,87 例发生 ADR(ADR 组),366 例未发生 ADR(nADR 组)。 单因素和 Logistic 回归多因素分析显示,过敏 史、给药频次不合理、高剂量、用药时间≥3 d、联合用药为 β-内酰胺类抗菌药物所致 ADR 的独立危险因素(P<0. 05)。 据此建立 预测 β-内酰胺类抗菌药物所致 ADR 的列线图模型,一致性指数高达 0. 749(95%CI 0. 691 ~ 0. 807),校正曲线趋近于理想曲线 (16% ~81%),列线图预测 β-内酰胺类抗菌药物引发患儿 ADR 风险净获益值较高,表明该模型临床预测效用良好。 结论:β-内 酰胺类抗菌药物所致 ADR 的危险因素包括过敏史、给药频次不合理、高剂量、用药时间≥3 d、联合用药,据此构建的列线图模 型能有效预测 β-内酰胺类抗菌药物致 ADR 的风险概率,具有一定临床价值。
关键词:  β-内酰胺类抗菌药物  药物不良反应  危险因素  列线图  模型预测
DOI:10. 13407/ j. cnki. jpp. 1672-108X. 2023. 11. 004
基金项目:
Adverse Drug Reaction Monitoring and Construction of Risk Prediction Model of β-Lactam Antibiotics
Jiang Junjie1 , Wang Facai1 , Shen Bingxiang1 , Nie Songliu1 , Duan Zihao1 , Zhu Zhixiang2
(1. Lu’an Hospital Affiliated to Anhui Medical University, Anhui Lu’an 237005, China; 2. Beijing University of Chinese Medicine, Beijing 100029, China)
Abstract:
Objective: To analyze the occurrence and influencing factors of adverse drug reactions ( ADR) induced by β-lactam antibiotics and establish the risk prediction model by monitoring ADR induced by β-lactam antibiotics in children from Lu’ an Hospital Affiliated to Anhui Medical University. Methods: Children who received β-lactam antibiotics in Lu’ an Hospital Affiliated to Anhui Medical University from May 2018 to Feb. 2022 were extracted as subjects for ADR monitoring. Clinical data of children with ADR were collected and analyzed. Based on the occurrence of ADR, children were divided into the ADR group and non-ADR ( nADR) group. Logistic regression analysis was used to identify independent risk factors and construct the nomogram prediction model. Results: A total of 453 children receiving β-lactam antibiotics were monitored, with 87 cases of ADR (ADR group), and 366 cases without ADR (nADR group). Univariate and multivariate Logistic regression analysis showed that history of allergy, inappropriate administration frequency, high dose, medication duration ⩾3 d and drug combination were independent risk factors for ADR induced by β-lactam antibiotics (P< 0. 05). Based on these findings, nomogram model for predicting ADR induced by β-lactam antibiotics was constructed, with C-index of 0. 749 (95% CI from 0. 691 to 0. 807). Correction curve was close to the ideal curve ( from 16% to 81%), and the net risk benefit value of ADR induced by β-lactam antibiotics predicted by the column graph was high, indicating that the model was good in clinical prediction. Conclusion: Risk factors of ADR induced by β-lactam antibiotics include history of allergy, inappropriate administration frequency, high dose, medication duration ⩾3 d and drug combination, and the constructed nomogram model can effectively predict the risk probability of ADR induced by β-lactam antibiotics, which is of some clinical value.
Key words:  β-lactam antibiotics  adverse drug reactions  influencing factors  nomogram  model prediction

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